Latest release: October 15, 2019 • version 4.5.0 • CHANGELOG • Migrating From GRDB 3 to GRDB 4
Requirements: iOS 9.0+ / macOS 10.9+ / tvOS 9.0+ / watchOS 2.0+ • Swift 4.2+ / Xcode 10.0+
Swift version | GRDB version |
---|---|
Swift 5 | v4.5.0 |
Swift 4.2 | v4.5.0 |
Swift 4.1 | v3.7.0 |
Swift 4 | v2.10.0 |
Swift 3.2 | v1.3.0 |
Swift 3.1 | v1.3.0 |
Swift 3 | v1.0 |
Swift 2.3 | v0.81.2 |
Swift 2.2 | v0.80.2 |
Contact:
- Release announcements and usage tips: follow @groue on Twitter.
- Report bugs in a Github issue. Make sure you check the existing issues first.
- A question? Looking for advice? Do you wonder how to contribute? Fancy a chat? Go to the GRDB forums, or open a Github issue.
GRDB provides raw access to SQL and advanced SQLite features, because one sometimes enjoys a sharp tool. It has robust concurrency primitives, so that multi-threaded applications can efficiently use their databases. It grants your application models with persistence and fetching methods, so that you don't have to deal with SQL and raw database rows when you don't want to.
Compared to SQLite.swift or FMDB, GRDB can spare you a lot of glue code. Compared to Core Data or Realm, it can simplify your multi-threaded applications.
It comes with up-to-date documentation, general guides, and it is fast.
See Why Adopt GRDB? if you are looking for your favorite database library.
Features • Usage • Installation • Documentation • Demo Application • FAQ
GRDB ships with:
- Access to raw SQL and SQLite
- Records: Fetching and persistence methods for your custom structs and class hierarchies.
- Query Interface: A swift way to avoid the SQL language.
- Associations: Relations and joins between record types.
- WAL Mode Support: Extra performance for multi-threaded applications.
- Migrations: Transform your database as your application evolves.
- Database Observation: Observe database changes and transactions.
- Full-Text Search
- Encryption
- Support for Custom SQLite Builds
Companion libraries that enhance and extend GRDB:
- GRDBCombine: track database changes in a reactive way, with Combine.
- RxGRDB: track database changes in a reactive way, with RxSwift.
- GRDBObjc: FMDB-compatible bindings to GRDB.
Connect to an SQLite database
import GRDB
// Simple database connection
let dbQueue = try DatabaseQueue(path: "/path/to/database.sqlite")
// Enhanced multithreading based on SQLite's WAL mode
let dbPool = try DatabasePool(path: "/path/to/database.sqlite")
Execute SQL statements
try dbQueue.write { db in
try db.execute(sql: """
CREATE TABLE place (
id INTEGER PRIMARY KEY AUTOINCREMENT,
title TEXT NOT NULL,
favorite BOOLEAN NOT NULL DEFAULT 0,
latitude DOUBLE NOT NULL,
longitude DOUBLE NOT NULL)
""")
try db.execute(sql: """
INSERT INTO place (title, favorite, latitude, longitude)
VALUES (?, ?, ?, ?)
""", arguments: ["Paris", true, 48.85341, 2.3488])
let parisId = db.lastInsertedRowID
// Swift 5 only
try db.execute(literal: """
INSERT INTO place (title, favorite, latitude, longitude)
VALUES (\("Madrid"), \(true), \(40.41678), \(-3.70379))
""")
}
Fetch database rows and values
try dbQueue.read { db in
// Fetch database rows
let rows = try Row.fetchCursor(db, sql: "SELECT * FROM place")
while let row = try rows.next() {
let title: String = row["title"]
let isFavorite: Bool = row["favorite"]
let coordinate = CLLocationCoordinate2D(
latitude: row["latitude"],
longitude: row["longitude"])
}
// Fetch values
let placeCount = try Int.fetchOne(db, sql: "SELECT COUNT(*) FROM place")! // Int
let placeTitles = try String.fetchAll(db, sql: "SELECT title FROM place") // [String]
}
let placeCount = try dbQueue.read { db in
try Int.fetchOne(db, sql: "SELECT COUNT(*) FROM place")!
}
See Fetch Queries
Store custom models aka "records"
struct Place {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D
}
// snip: turn Place into a "record" by adopting the protocols that
// provide fetching and persistence methods.
try dbQueue.write { db in
// Create database table
try db.create(table: "place") { t in
t.autoIncrementedPrimaryKey("id")
t.column("title", .text).notNull()
t.column("favorite", .boolean).notNull().defaults(to: false)
t.column("longitude", .double).notNull()
t.column("latitude", .double).notNull()
}
var berlin = Place(
id: nil,
title: "Berlin",
isFavorite: false,
coordinate: CLLocationCoordinate2D(latitude: 52.52437, longitude: 13.41053))
try berlin.insert(db)
berlin.id // some value
berlin.isFavorite = true
try berlin.update(db)
}
See Records
Fetch records and values with the Swift query interface
try dbQueue.read { db in
// Place?
let paris = try Place.fetchOne(db, key: 1)
// Place?
let berlin = try Place.filter(Column("title") == "Berlin").fetchOne(db)
// [Place]
let favoritePlaces = try Place
.filter(Column("favorite") == true)
.order(Column("title"))
.fetchAll(db)
// Int
let favoriteCount = try Place.filter(Column("favorite")).fetchCount(db)
// SQL is always welcome
let places = try Place.fetchAll(db, sql: "SELECT * FROM place")
}
See the Query Interface
Be notified of database changes
let observation = ValueObservation.tracking { db in
try Place.fetchAll(db)
}
observation.start(
in: dbQueue,
onError: { error in
print("fresh places could not be fetched")
}
onChange: { (places: [Place]) in
print("Places have changed.")
})
GRDB runs on top of SQLite: you should get familiar with the SQLite FAQ. For general and detailed information, jump to the SQLite Documentation.
- GRDB Reference (generated by Jazzy)
- Installation
- Demo Application
- Database Connections: Connect to SQLite databases
- SQLite API: The low-level SQLite API • executing updates • fetch queries • SQL Interpolation
- Records: Fetching and persistence methods for your custom structs and class hierarchies
- Query Interface: A swift way to generate SQL • table creation • requests • associations between record types
- Migrations: Transform your database as your application evolves.
- Full-Text Search: Perform efficient and customizable full-text searches.
- Joined Queries Support: Consume complex joined queries.
- Database Changes Observation: Observe database changes and transactions.
- Encryption: Encrypt your database with SQLCipher.
- Backup: Dump the content of a database to another.
- Avoiding SQL Injection
- Error Handling
- Unicode
- Memory Management
- Data Protection
- Concurrency
- Performance
- 💡 Good Practices for Designing Record Types
- 💡 Migrating From GRDB 3 to GRDB 4
- 💡 Issues tagged "best practices"
- ❓ Issues tagged "question"
- 📘 Why Adopt GRDB?
- 📘 How to build an iOS application with SQLite and GRDB.swift
- 📘 Four different ways to handle SQLite concurrency
- 📘 Unexpected SQLite with Swift
The installation procedures below have GRDB use the version of SQLite that ships with the target operating system.
See Encryption for the installation procedure of GRDB with SQLCipher.
See Custom SQLite builds for the installation procedure of GRDB with a customized build of SQLite 3.28.0.
See Enabling FTS5 Support for the installation procedure of GRDB with support for the FTS5 full-text engine.
CocoaPods is a dependency manager for Xcode projects. To use GRDB with CocoaPods (version 1.2 or higher), specify in your Podfile
:
pod 'GRDB.swift'
GRDB can be installed as a framework, or a static library.
The Swift Package Manager automates the distribution of Swift code. To use GRDB with SPM, add a dependency to your Package.swift
file:
let package = Package(
dependencies: [
.package(url: "https://github.com/groue/GRDB.swift.git", .upToNextMajor(from: "4.5.0"))
]
)
Note that Linux is not currently supported.
Carthage is unsupported. For some context about this decision, see #433.
-
Download a copy of GRDB, or clone its repository and make sure you use the latest tagged version with the
git checkout v4.5.0
command. -
Embed the
GRDB.xcodeproj
project in your own project. -
Add the
GRDBOSX
,GRDBiOS
,GRDBtvOS
, orGRDBWatchOS
target in the Target Dependencies section of the Build Phases tab of your application target (extension target for WatchOS). -
Add the
GRDB.framework
from the targetted platform to the Embedded Binaries section of the General tab of your application target (extension target for WatchOS).
💡 Tip: see the Demo Application for an example of such integration.
The repository comes with a Demo Application that shows you:
- how to setup a database in an iOS app
- how to define a simple Codable Record
- how to track database changes with ValueObservation.
GRDB provides two classes for accessing SQLite databases: DatabaseQueue
and DatabasePool
:
import GRDB
// Pick one:
let dbQueue = try DatabaseQueue(path: "/path/to/database.sqlite")
let dbPool = try DatabasePool(path: "/path/to/database.sqlite")
The differences are:
- Database pools allow concurrent database accesses (this can improve the performance of multithreaded applications).
- Database pools open your SQLite database in the WAL mode (unless read-only).
- Database queues support in-memory databases.
If you are not sure, choose DatabaseQueue. You will always be able to switch to DatabasePool later.
Open a database queue with the path to a database file:
import GRDB
let dbQueue = try DatabaseQueue(path: "/path/to/database.sqlite")
let inMemoryDBQueue = DatabaseQueue()
SQLite creates the database file if it does not already exist. The connection is closed when the database queue gets deallocated.
A database queue can be used from any thread. The write
and read
methods are synchronous, and block the current thread until your database statements are executed in a protected dispatch queue:
// Modify the database:
try dbQueue.write { db in
try db.create(table: "place") { ... }
try Place(...).insert(db)
}
// Read values:
try dbQueue.read { db in
let places = try Place.fetchAll(db)
let placeCount = try Place.fetchCount(db)
}
Database access methods can return values:
let placeCount = try dbQueue.read { db in
try Place.fetchCount(db)
}
let newPlaceCount = try dbQueue.write { db -> Int in
try Place(...).insert(db)
return try Place.fetchCount(db)
}
A database queue serializes accesses to the database, which means that there is never more than one thread that uses the database.
-
When you don't need to modify the database, prefer the
read
method. It prevents any modification to the database. -
The
write
method wraps your database statements in a transaction that commits if and only if no error occurs. On the first unhandled error, all changes are reverted, the whole transaction is rollbacked, and the error is rethrown.When precise transaction handling is required, see Transactions and Savepoints.
A database queue needs your application to follow rules in order to deliver its safety guarantees. Please refer to the Concurrency chapter.
💡 Tip: see the Demo Application for a sample code that sets up a database queue on iOS.
var config = Configuration()
config.readonly = true
config.foreignKeysEnabled = true // Default is already true
config.trace = { print($0) } // Prints all SQL statements
config.label = "MyDatabase" // Useful when your app opens multiple databases
let dbQueue = try DatabaseQueue(
path: "/path/to/database.sqlite",
configuration: config)
See Configuration for more details.
A database pool allows concurrent database accesses.
import GRDB
let dbPool = try DatabasePool(path: "/path/to/database.sqlite")
SQLite creates the database file if it does not already exist. The connection is closed when the database pool gets deallocated.
☝️ Note: unless read-only, a database pool opens your database in the SQLite "WAL mode". The WAL mode does not fit all situations. Please have a look at https://www.sqlite.org/wal.html.
A database pool can be used from any thread. The write
and read
methods are synchronous, and block the current thread until your database statements are executed in a protected dispatch queue:
// Modify the database:
try dbPool.write { db in
try db.create(table: "place") { ... }
try Place(...).insert(db)
}
// Read values:
try dbPool.read { db in
let places = try Place.fetchAll(db)
let placeCount = try Place.fetchCount(db)
}
Database access methods can return values:
let placeCount = try dbPool.read { db in
try Place.fetchCount(db)
}
let newPlaceCount = try dbPool.write { db -> Int in
try Place(...).insert(db)
return try Place.fetchCount(db)
}
Database pools allow several threads to access the database at the same time:
-
When you don't need to modify the database, prefer the
read
method, because several threads can perform reads in parallel.Reads are generally non-blocking, unless the maximum number of concurrent reads has been reached. In this case, a read has to wait for another read to complete. That maximum number can be configured.
-
Reads are guaranteed an immutable view of the last committed state of the database, regardless of concurrent writes. This kind of isolation is called snapshot isolation.
-
Unlike reads, writes are serialized. There is never more than a single thread that is writing into the database.
-
The
write
method wraps your database statements in a transaction that commits if and only if no error occurs. On the first unhandled error, all changes are reverted, the whole transaction is rollbacked, and the error is rethrown.When precise transaction handling is required, see Transactions and Savepoints.
-
Database pools can take snapshots of the database.
A database pool needs your application to follow rules in order to deliver its safety guarantees. See the Concurrency chapter for more details about database pools, how they differ from database queues, and advanced use cases.
💡 Tip: see the Demo Application for a sample code that sets up a database queue on iOS, and just replace DatabaseQueue with DatabasePool.
var config = Configuration()
config.readonly = true
config.foreignKeysEnabled = true // Default is already true
config.trace = { print($0) } // Prints all SQL statements
config.label = "MyDatabase" // Useful when your app opens multiple databases
config.maximumReaderCount = 10 // The default is 5
let dbPool = try DatabasePool(
path: "/path/to/database.sqlite",
configuration: config)
See Configuration for more details.
Database pools are more memory-hungry than database queues. See Memory Management for more information.
In this section of the documentation, we will talk SQL. Jump to the query interface if SQL is not your cup of tea.
Advanced topics:
- Prepared Statements
- Custom SQL Functions and Aggregates
- Database Schema Introspection
- Row Adapters
- Raw SQLite Pointers
Once granted with a database connection, the execute
method executes the SQL statements that do not return any database row, such as CREATE TABLE
, INSERT
, DELETE
, ALTER
, etc.
For example:
try dbQueue.write { db in
try db.execute(sql: """
CREATE TABLE player (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
score INT)
""")
try db.execute(
sql: "INSERT INTO player (name, score) VALUES (?, ?)",
arguments: ["Barbara", 1000])
try db.execute(
sql: "UPDATE player SET score = :score WHERE id = :id",
arguments: ["score": 1000, "id": 1])
}
}
The ?
and colon-prefixed keys like :score
in the SQL query are the statements arguments. You pass arguments with arrays or dictionaries, as in the example above. See Values for more information on supported arguments types (Bool, Int, String, Date, Swift enums, etc.), and StatementArguments for a detailed documentation of SQLite arguments.
In Swift 5, you can embed query arguments right into your SQL queries, with the literal
argument label, as in the example below. See SQL Interpolation for more details.
// Swift 5
try dbQueue.write { db in
try db.execute(literal: """
INSERT INTO player (name, score)
VALUES (\("O'Brien"), \(550))
""")
}
Never ever embed values directly in your raw SQL strings. See Avoiding SQL Injection for more information:
// WRONG: don't embed values in raw SQL strings
let id = 123
let name = textField.text
try db.execute(
sql: "UPDATE player SET name = '\(name)' WHERE id = \(id)")
// CORRECT: use SQL Interpolation (Swift 5)
try db.execute(
literal: "UPDATE player SET name = \(name) WHERE id = \(id)")
// CORRECT: use arguments dictionary
try db.execute(
sql: "UPDATE player SET name = :name WHERE id = :id",
arguments: ["name": name, "id": id])
// CORRECT: use arguments array
try db.execute(
sql: "UPDATE player SET name = ? WHERE id = ?",
arguments: [name, id])
Join multiple statements with a semicolon:
try db.execute(sql: """
INSERT INTO player (name, score) VALUES (?, ?);
INSERT INTO player (name, score) VALUES (?, ?);
""", arguments: ["Arthur", 750, "Barbara", 1000])
// Swift 5
try db.execute(literal: """
INSERT INTO player (name, score) VALUES (\("Arthur"), \(750));
INSERT INTO player (name, score) VALUES (\("Barbara"), \(1000));
""")
When you want to make sure that a single statement is executed, use Prepared Statements.
After an INSERT statement, you can get the row ID of the inserted row:
try db.execute(
sql: "INSERT INTO player (name, score) VALUES (?, ?)",
arguments: ["Arthur", 1000])
let playerId = db.lastInsertedRowID
Don't miss Records, that provide classic persistence methods:
var player = Player(name: "Arthur", score: 1000)
try player.insert(db)
let playerId = player.id
Database connections let you fetch database rows, plain values, and custom models aka "records".
Rows are the raw results of SQL queries:
try dbQueue.read { db in
if let row = try Row.fetchOne(db, sql: "SELECT * FROM wine WHERE id = ?", arguments: [1]) {
let name: String = row["name"]
let color: Color = row["color"]
print(name, color)
}
}
Values are the Bool, Int, String, Date, Swift enums, etc. stored in row columns:
try dbQueue.read { db in
let urls = try URL.fetchCursor(db, sql: "SELECT url FROM wine")
while let url = try urls.next() {
print(url)
}
}
Records are your application objects that can initialize themselves from rows:
let wines = try dbQueue.read { db in
try Wine.fetchAll(db, sql: "SELECT * FROM wine")
}
Throughout GRDB, you can always fetch cursors, arrays, or single values of any fetchable type (database row, simple value, or custom record):
try Row.fetchCursor(...) // A Cursor of Row
try Row.fetchAll(...) // [Row]
try Row.fetchOne(...) // Row?
-
fetchCursor
returns a cursor over fetched values:let rows = try Row.fetchCursor(db, sql: "SELECT ...") // A Cursor of Row
-
fetchAll
returns an array:let players = try Player.fetchAll(db, sql: "SELECT ...") // [Player]
-
fetchOne
returns a single optional value, and consumes a single database row (if any).let count = try Int.fetchOne(db, sql: "SELECT COUNT(*) ...") // Int?
Whenever you consume several rows from the database, you can fetch an Array, or a Cursor.
The fetchAll()
method returns a regular Swift array, that you iterate like all other arrays:
try dbQueue.read { db in
// [Player]
let players = try Player.fetchAll(db, sql: "SELECT ...")
for player in players {
// use player
}
}
Unlike arrays, cursors returned by fetchCursor()
load their results step after step:
try dbQueue.read { db in
// Cursor of Player
let players = try Player.fetchCursor(db, sql: "SELECT ...")
while let player = try players.next() {
// use player
}
}
Both arrays and cursors can iterate over database results. How do you choose one or the other? Look at the differences:
-
Cursors can not be used on any thread: you must consume a cursor on the dispatch queue it was created in. Particularly, don't extract a cursor out of a database access method:
// Wrong let cursor = try dbQueue.read { db in try Player.fetchCursor(db, ...) } while let player = try cursor.next() { ... }
Conversely, arrays may be consumed on any thread:
// OK let array = try dbQueue.read { db in try Player.fetchAll(db, ...) } for player in array { ... }
-
Cursors can be iterated only one time. Arrays can be iterated many times.
-
Cursors iterate database results in a lazy fashion, and don't consume much memory. Arrays contain copies of database values, and may take a lot of memory when there are many fetched results.
-
Cursors are granted with direct access to SQLite, unlike arrays that have to take the time to copy database values. If you look after extra performance, you may prefer cursors over arrays.
-
Cursors adopt the Cursor protocol, which looks a lot like standard lazy sequences of Swift. As such, cursors come with many convenience methods:
compactMap
,contains
,dropFirst
,dropLast
,drop(while:)
,enumerated
,filter
,first
,flatMap
,forEach
,joined
,joined(separator:)
,max
,max(by:)
,min
,min(by:)
,map
,prefix
,prefix(while:)
,reduce
,reduce(into:)
,suffix
:// Prints all Github links try URL .fetchCursor(db, sql: "SELECT url FROM link") .filter { url in url.host == "github.com" } .forEach { url in print(url) } // An efficient cursor of coordinates: let locations = try Row. .fetchCursor(db, sql: "SELECT latitude, longitude FROM place") .map { row in CLLocationCoordinate2D(latitude: row[0], longitude: row[1]) } // Turn cursors into arrays or sets: let array = try Array(cursor) let set = try Set(cursor)
-
Cursors are not Swift sequences. That's because Swift sequences can't handle iteration errors, when reading SQLite results may fail at any time. SQL functions may throw errors. On iOS, data protection may block access to the database file in the background. On macOS, your application users may mess with the file system.
-
Cursors require a little care:
-
Don't modify the results during a cursor iteration:
// Undefined behavior while let player = try players.next() { try db.execute(sql: "DELETE ...") }
-
Don't turn a cursor of
Row
into an array. You would not get the distinct rows you expect. To get a array of rows, useRow.fetchAll(...)
. Generally speaking, make sure you copy a row whenever you extract it from a cursor for later use:row.copy()
.
-
If you don't see, or don't care about the difference, use arrays. If you care about memory and performance, use cursors when appropriate.
Fetch cursors of rows, arrays, or single rows (see fetching methods):
try dbQueue.read { db in
try Row.fetchCursor(db, sql: "SELECT ...", arguments: ...) // A Cursor of Row
try Row.fetchAll(db, sql: "SELECT ...", arguments: ...) // [Row]
try Row.fetchOne(db, sql: "SELECT ...", arguments: ...) // Row?
let rows = try Row.fetchCursor(db, sql: "SELECT * FROM wine")
while let row = try rows.next() {
let name: String = row["name"]
let color: Color = row["color"]
print(name, color)
}
}
let rows = try dbQueue.read { db in
try Row.fetchAll(db, sql: "SELECT * FROM player")
}
Arguments are optional arrays or dictionaries that fill the positional ?
and colon-prefixed keys like :name
in the query:
let rows = try Row.fetchAll(db,
sql: "SELECT * FROM player WHERE name = ?",
arguments: ["Arthur"])
let rows = try Row.fetchAll(db,
sql: "SELECT * FROM player WHERE name = :name",
arguments: ["name": "Arthur"])
See Values for more information on supported arguments types (Bool, Int, String, Date, Swift enums, etc.), and StatementArguments for a detailed documentation of SQLite arguments.
Unlike row arrays that contain copies of the database rows, row cursors are close to the SQLite metal, and require a little care:
☝️ Don't turn a cursor of
Row
into an array. You would not get the distinct rows you expect. To get a array of rows, useRow.fetchAll(...)
. Generally speaking, make sure you copy a row whenever you extract it from a cursor for later use:row.copy()
.
Read column values by index or column name:
let name: String = row[0] // 0 is the leftmost column
let name: String = row["name"] // Leftmost matching column - lookup is case-insensitive
let name: String = row[Column("name")] // Using query interface's Column
Make sure to ask for an optional when the value may be NULL:
let name: String? = row["name"]
The row[]
subscript returns the type you ask for. See Values for more information on supported value types:
let bookCount: Int = row["bookCount"]
let bookCount64: Int64 = row["bookCount"]
let hasBooks: Bool = row["bookCount"] // false when 0
let string: String = row["date"] // "2015-09-11 18:14:15.123"
let date: Date = row["date"] // Date
self.date = row["date"] // Depends on the type of the property.
You can also use the as
type casting operator:
row[...] as Int
row[...] as Int?
⚠️ Warning: avoid theas!
andas?
operators:if let int = row[...] as? Int { ... } // BAD - doesn't work if let int = row[...] as Int? { ... } // GOOD
Generally speaking, you can extract the type you need, provided it can be converted from the underlying SQLite value:
-
Successful conversions include:
- All numeric SQLite values to all numeric Swift types, and Bool (zero is the only false boolean).
- Text SQLite values to Swift String.
- Blob SQLite values to Foundation Data.
See Values for more information on supported types (Bool, Int, String, Date, Swift enums, etc.)
-
NULL returns nil.
let row = try Row.fetchOne(db, sql: "SELECT NULL")! row[0] as Int? // nil row[0] as Int // fatal error: could not convert NULL to Int.
There is one exception, though: the DatabaseValue type:
row[0] as DatabaseValue // DatabaseValue.null
-
Missing columns return nil.
let row = try Row.fetchOne(db, sql: "SELECT 'foo' AS foo")! row["missing"] as String? // nil row["missing"] as String // fatal error: no such column: missing
You can explicitly check for a column presence with the
hasColumn
method. -
Invalid conversions throw a fatal error.
let row = try Row.fetchOne(db, sql: "SELECT 'Mom’s birthday'")! row[0] as String // "Mom’s birthday" row[0] as Date? // fatal error: could not convert "Mom’s birthday" to Date. row[0] as Date // fatal error: could not convert "Mom’s birthday" to Date. let row = try Row.fetchOne(db, sql: "SELECT 256")! row[0] as Int // 256 row[0] as UInt8? // fatal error: could not convert 256 to UInt8. row[0] as UInt8 // fatal error: could not convert 256 to UInt8.
Those conversion fatal errors can be avoided with the DatabaseValue type:
let row = try Row.fetchOne(db, sql: "SELECT 'Mom’s birthday'")! let dbValue: DatabaseValue = row[0] if dbValue.isNull { // Handle NULL } else if let date = Date.fromDatabaseValue(dbValue) { // Handle valid date } else { // Handle invalid date }
This extra verbosity is the consequence of having to deal with an untrusted database: you may consider fixing the content of your database instead. See Fatal Errors for more information.
-
SQLite has a weak type system, and provides convenience conversions that can turn String to Int, Double to Blob, etc.
GRDB will sometimes let those conversions go through:
let rows = try Row.fetchCursor(db, sql: "SELECT '20 small cigars'") while let row = try rows.next() { row[0] as Int // 20 }
Don't freak out: those conversions did not prevent SQLite from becoming the immensely successful database engine you want to use. And GRDB adds safety checks described just above. You can also prevent those convenience conversions altogether by using the DatabaseValue type.
DatabaseValue is an intermediate type between SQLite and your values, which gives information about the raw value stored in the database.
You get DatabaseValue just like other value types:
let dbValue: DatabaseValue = row[0]
let dbValue: DatabaseValue? = row["name"] // nil if and only if column does not exist
// Check for NULL:
dbValue.isNull // Bool
// The stored value:
dbValue.storage.value // Int64, Double, String, Data, or nil
// All the five storage classes supported by SQLite:
switch dbValue.storage {
case .null: print("NULL")
case .int64(let int64): print("Int64: \(int64)")
case .double(let double): print("Double: \(double)")
case .string(let string): print("String: \(string)")
case .blob(let data): print("Data: \(data)")
}
You can extract regular values (Bool, Int, String, Date, Swift enums, etc.) from DatabaseValue with the DatabaseValueConvertible.fromDatabaseValue() method:
let dbValue: DatabaseValue = row["bookCount"]
let bookCount = Int.fromDatabaseValue(dbValue) // Int?
let bookCount64 = Int64.fromDatabaseValue(dbValue) // Int64?
let hasBooks = Bool.fromDatabaseValue(dbValue) // Bool?, false when 0
let dbValue: DatabaseValue = row["date"]
let string = String.fromDatabaseValue(dbValue) // "2015-09-11 18:14:15.123"
let date = Date.fromDatabaseValue(dbValue) // Date?
fromDatabaseValue
returns nil for invalid conversions:
let row = try Row.fetchOne(db, sql: "SELECT 'Mom’s birthday'")!
let dbValue: DatabaseValue = row[0]
let string = String.fromDatabaseValue(dbValue) // "Mom’s birthday"
let int = Int.fromDatabaseValue(dbValue) // nil
let date = Date.fromDatabaseValue(dbValue) // nil
Row adopts the standard RandomAccessCollection protocol, and can be seen as a dictionary of DatabaseValue:
// All the (columnName, dbValue) tuples, from left to right:
for (columnName, dbValue) in row {
...
}
You can build rows from dictionaries (standard Swift dictionaries and NSDictionary). See Values for more information on supported types:
let row: Row = ["name": "foo", "date": nil]
let row = Row(["name": "foo", "date": nil])
let row = Row(/* [AnyHashable: Any] */) // nil if invalid dictionary
Yet rows are not real dictionaries: they may contain duplicate columns:
let row = try Row.fetchOne(db, sql: "SELECT 1 AS foo, 2 AS foo")!
row.columnNames // ["foo", "foo"]
row.databaseValues // [1, 2]
row["foo"] // 1 (leftmost matching column)
for (columnName, dbValue) in row { ... } // ("foo", 1), ("foo", 2)
When you build a dictionary from a row, you have to disambiguate identical columns, and choose how to present database values. For example:
-
A
[String: DatabaseValue]
dictionary that keeps leftmost value in case of duplicated column name:let dict = Dictionary(row, uniquingKeysWith: { (left, _) in left })
-
A
[String: AnyObject]
dictionary which keeps rightmost value in case of duplicated column name. This dictionary is identical to FMResultSet's resultDictionary from FMDB. It contains NSNull values for null columns, and can be shared with Objective-C:let dict = Dictionary( row.map { (column, dbValue) in (column, dbValue.storage.value as AnyObject) }, uniquingKeysWith: { (_, right) in right })
-
A
[String: Any]
dictionary that can feed, for example, JSONSerialization:let dict = Dictionary( row.map { (column, dbValue) in (column, dbValue.storage.value) }, uniquingKeysWith: { (left, _) in left })
See the documentation of Dictionary.init(_:uniquingKeysWith:)
for more information.
Instead of rows, you can directly fetch values. Like rows, fetch them as cursors, arrays, or single values (see fetching methods). Values are extracted from the leftmost column of the SQL queries:
try dbQueue.read { db in
try Int.fetchCursor(db, sql: "SELECT ...", arguments: ...) // A Cursor of Int
try Int.fetchAll(db, sql: "SELECT ...", arguments: ...) // [Int]
try Int.fetchOne(db, sql: "SELECT ...", arguments: ...) // Int?
// When database may contain NULL:
try Optional<Int>.fetchCursor(db, sql: "SELECT ...", arguments: ...) // A Cursor of Int?
try Optional<Int>.fetchAll(db, sql: "SELECT ...", arguments: ...) // [Int?]
}
let playerCount = try dbQueue.read { db in
try Int.fetchOne(db, sql: "SELECT COUNT(*) FROM player")!
}
fetchOne
returns an optional value which is nil in two cases: either the SELECT statement yielded no row, or one row with a NULL value.
There are many supported value types (Bool, Int, String, Date, Swift enums, etc.). See Values for more information:
let count = try Int.fetchOne(db, sql: "SELECT COUNT(*) FROM player")! // Int
let urls = try URL.fetchAll(db, sql: "SELECT url FROM link") // [URL]
GRDB ships with built-in support for the following value types:
-
Swift Standard Library: Bool, Double, Float, all signed and unsigned integer types, String, Swift enums.
-
Foundation: Data, Date, DateComponents, NSNull, NSNumber, NSString, URL, UUID.
-
CoreGraphics: CGFloat.
-
DatabaseValue, the type which gives information about the raw value stored in the database.
-
Full-Text Patterns: FTS3Pattern and FTS5Pattern.
-
Generally speaking, all types that adopt the DatabaseValueConvertible protocol.
Values can be used as statement arguments:
let url: URL = ...
let verified: Bool = ...
try db.execute(
sql: "INSERT INTO link (url, verified) VALUES (?, ?)",
arguments: [url, verified])
Values can be extracted from rows:
let rows = try Row.fetchCursor(db, sql: "SELECT * FROM link")
while let row = try rows.next() {
let url: URL = row["url"]
let verified: Bool = row["verified"]
}
Values can be directly fetched:
let urls = try URL.fetchAll(db, sql: "SELECT url FROM link") // [URL]
Use values in Records:
struct Link: FetchableRecord {
var url: URL
var isVerified: Bool
init(row: Row) {
url = row["url"]
isVerified = row["verified"]
}
}
Use values in the query interface:
let url: URL = ...
let link = try Link.filter(Column("url") == url).fetchOne(db)
Data suits the BLOB SQLite columns. It can be stored and fetched from the database just like other values:
let rows = try Row.fetchCursor(db, sql: "SELECT data, ...")
while let row = try rows.next() {
let data: Data = row["data"]
}
At each step of the request iteration, the row[]
subscript creates two copies of the database bytes: one fetched by SQLite, and another, stored in the Swift Data value.
You have the opportunity to save memory by not copying the data fetched by SQLite:
while let row = try rows.next() {
let data = row.dataNoCopy(named: "data") // Data?
}
The non-copied data does not live longer than the iteration step: make sure that you do not use it past this point.
Date and DateComponents can be stored and fetched from the database.
Here is how GRDB supports the various date formats supported by SQLite:
SQLite format | Date | DateComponents |
---|---|---|
YYYY-MM-DD | Read ¹ | Read/Write |
YYYY-MM-DD HH:MM | Read ¹ | Read/Write |
YYYY-MM-DD HH:MM:SS | Read ¹ | Read/Write |
YYYY-MM-DD HH:MM:SS.SSS | Read/Write ¹ | Read/Write |
YYYY-MM-DDTHH:MM | Read ¹ | Read |
YYYY-MM-DDTHH:MM:SS | Read ¹ | Read |
YYYY-MM-DDTHH:MM:SS.SSS | Read ¹ | Read |
HH:MM | Read/Write | |
HH:MM:SS | Read/Write | |
HH:MM:SS.SSS | Read/Write | |
Timestamps since unix epoch | Read ² | |
now |
¹ Dates are stored and read in the UTC time zone. Missing components are assumed to be zero.
² GRDB 2+ interprets numerical values as timestamps that fuel Date(timeIntervalSince1970:)
. Previous GRDB versions used to interpret numbers as julian days. Julian days are still supported, with the Date(julianDay:)
initializer.
Date can be stored and fetched from the database just like other values:
try db.execute(
sql: "INSERT INTO player (creationDate, ...) VALUES (?, ...)",
arguments: [Date(), ...])
let row = try Row.fetchOne(db, ...)!
let creationDate: Date = row["creationDate"]
Dates are stored using the format "YYYY-MM-DD HH:MM:SS.SSS" in the UTC time zone. It is precise to the millisecond.
☝️ Note: this format was chosen because it is the only format that is:
- Comparable (
ORDER BY date
works)- Comparable with the SQLite keyword CURRENT_TIMESTAMP (
WHERE date > CURRENT_TIMESTAMP
works)- Able to feed SQLite date & time functions
- Precise enough
When the default format does not fit your needs, customize date conversions. For example:
try db.execute(
sql: "INSERT INTO player (creationDate, ...) VALUES (?, ...)",
arguments: [Date().timeIntervalSinceReferenceDate, ...])
let row = try Row.fetchOne(db, ...)!
let creationDate = Date(timeIntervalSinceReferenceDate: row["creationDate"])
See Codable Records for more date customization options.
DateComponents is indirectly supported, through the DatabaseDateComponents helper type.
DatabaseDateComponents reads date components from all date formats supported by SQLite, and stores them in the format of your choice, from HH:MM to YYYY-MM-DD HH:MM:SS.SSS.
DatabaseDateComponents can be stored and fetched from the database just like other values:
let components = DateComponents()
components.year = 1973
components.month = 9
components.day = 18
// Store "1973-09-18"
let dbComponents = DatabaseDateComponents(components, format: .YMD)
try db.execute(
sql: "INSERT INTO player (birthDate, ...) VALUES (?, ...)",
arguments: [dbComponents, ...])
// Read "1973-09-18"
let row = try Row.fetchOne(db, sql: "SELECT birthDate ...")!
let dbComponents: DatabaseDateComponents = row["birthDate"]
dbComponents.format // .YMD (the actual format found in the database)
dbComponents.dateComponents // DateComponents
NSNumber can be stored and fetched from the database just like other values. Floating point NSNumbers are stored as Double. Integer and boolean, as Int64. Integers that don't fit Int64 won't be stored: you'll get a fatal error instead. Be cautious when an NSNumber contains an UInt64, for example.
NSDecimalNumber deserves a longer discussion:
SQLite has no support for decimal numbers. Given the table below, SQLite will actually store integers or doubles:
CREATE TABLE transfer (
amount DECIMAL(10,5) -- will store integer or double, actually
)
This means that computations will not be exact:
try db.execute(sql: "INSERT INTO transfer (amount) VALUES (0.1)")
try db.execute(sql: "INSERT INTO transfer (amount) VALUES (0.2)")
let sum = try NSDecimalNumber.fetchOne(db, sql: "SELECT SUM(amount) FROM transfer")!
// Yikes! 0.3000000000000000512
print(sum)
Don't blame SQLite or GRDB, and instead store your decimal numbers differently.
A classic technique is to store integers instead, since SQLite performs exact computations of integers. For example, don't store Euros, but store cents instead:
// Write
let amount = NSDecimalNumber(string: "0.10")
let integerAmount = amount.multiplying(byPowerOf10: 2).int64Value
try db.execute(sql: "INSERT INTO transfer (amount) VALUES (?)", arguments: [integerAmount])
// Read
let integerAmount = try Int64.fetchOne(db, sql: "SELECT SUM(amount) FROM transfer")!
let amount = NSDecimalNumber(value: integerAmount).multiplying(byPowerOf10: -2) // 0.10
UUID can be stored and fetched from the database just like other values.
GRDB stores uuids as 16-bytes data blobs, and decodes them from both 16-bytes data blobs and strings such as "E621E1F8-C36C-495A-93FC-0C247A3E6E5F".
Swift enums and generally all types that adopt the RawRepresentable protocol can be stored and fetched from the database just like their raw values:
enum Color : Int {
case red, white, rose
}
enum Grape : String {
case chardonnay, merlot, riesling
}
// Declare empty DatabaseValueConvertible adoption
extension Color : DatabaseValueConvertible { }
extension Grape : DatabaseValueConvertible { }
// Store
try db.execute(
sql: "INSERT INTO wine (grape, color) VALUES (?, ?)",
arguments: [Grape.merlot, Color.red])
// Read
let rows = try Row.fetchCursor(db, sql: "SELECT * FROM wine")
while let row = try rows.next() {
let grape: Grape = row["grape"]
let color: Color = row["color"]
}
When a database value does not match any enum case, you get a fatal error. This fatal error can be avoided with the DatabaseValue type:
let row = try Row.fetchOne(db, sql: "SELECT 'syrah'")!
row[0] as String // "syrah"
row[0] as Grape? // fatal error: could not convert "syrah" to Grape.
row[0] as Grape // fatal error: could not convert "syrah" to Grape.
let dbValue: DatabaseValue = row[0]
if dbValue.isNull {
// Handle NULL
} else if let grape = Grape.fromDatabaseValue(dbValue) {
// Handle valid grape
} else {
// Handle unknown grape
}
Conversion to and from the database is based on the DatabaseValueConvertible
protocol:
protocol DatabaseValueConvertible {
/// Returns a value that can be stored in the database.
var databaseValue: DatabaseValue { get }
/// Returns a value initialized from dbValue, if possible.
static func fromDatabaseValue(_ dbValue: DatabaseValue) -> Self?
}
All types that adopt this protocol can be used like all other values (Bool, Int, String, Date, Swift enums, etc.)
The databaseValue
property returns DatabaseValue, a type that wraps the five values supported by SQLite: NULL, Int64, Double, String and Data. Since DatabaseValue has no public initializer, use DatabaseValue.null
, or another type that already adopts the protocol: 1.databaseValue
, "foo".databaseValue
, etc. Conversion to DatabaseValue must not fail.
The fromDatabaseValue()
factory method returns an instance of your custom type if the database value contains a suitable value. If the database value does not contain a suitable value, such as "foo" for Date, fromDatabaseValue
must return nil (GRDB will interpret this nil result as a conversion error, and react accordingly).
A transaction is a fundamental tool of SQLite that guarantees data consistency as well as proper isolation between application threads and database connections.
GRDB generally opens transactions for you, as a way to enforce its concurrency guarantees, and provide maximal security for both your application data and application logic:
// BEGIN TRANSACTION
// INSERT INTO credit ...
// INSERT INTO debit ...
// COMMIT
try dbQueue.write { db in
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
}
// BEGIN TRANSACTION
// INSERT INTO credit ...
// INSERT INTO debit ...
// COMMIT
try dbPool.write { db in
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
}
Yet you may need to exactly control when transactions take place:
DatabaseQueue.inDatabase()
and DatabasePool.writeWithoutTransaction()
execute your database statements outside of any transaction:
// INSERT INTO credit ...
// INSERT INTO debit ...
try dbQueue.inDatabase { db in
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
}
// INSERT INTO credit ...
// INSERT INTO debit ...
try dbPool.writeWithoutTransaction { db in
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
}
Writing outside of any transaction is dangerous, for two reasons:
-
In our credit/debit example, you may successfully insert a credit, but fail inserting the debit, and end up with unbalanced accounts (oops).
// UNSAFE DATABASE INTEGRITY try dbQueue.inDatabase { db in // or dbPool.writeWithoutTransaction try Credit(destinationAccount, amount).insert(db) // may succeed try Debit(sourceAccount, amount).insert(db) // may fail }
Transactions avoid this kind of bug.
-
Database pool concurrent reads can see an inconsistent state of the database:
// UNSAFE CONCURRENCY try dbPool.writeWithoutTransaction { db in try Credit(destinationAccount, amount).insert(db) // <- Concurrent dbPool.read sees a partial db update here try Debit(sourceAccount, amount).insert(db) }
Transactions avoid this kind of bug, too.
To open explicit transactions, use one of the Database.inTransaction
, DatabaseQueue.inTransaction
, or DatabasePool.writeInTransaction
methods:
// BEGIN TRANSACTION
// INSERT INTO credit ...
// INSERT INTO debit ...
// COMMIT
try dbQueue.inDatabase { db in // or dbPool.writeWithoutTransaction
try db.inTransaction {
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
return .commit
}
}
// BEGIN TRANSACTION
// INSERT INTO credit ...
// INSERT INTO debit ...
// COMMIT
try dbQueue.inTransaction { db in // or dbPool.writeInTransaction
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
return .commit
}
If an error is thrown from the transaction block, the transaction is rollbacked and the error is rethrown by the inTransaction
method. If you return .rollback
instead of .commit
, the transaction is also rollbacked, but no error is thrown.
You can also perform manual transaction management:
try dbQueue.inDatabase { db in // or dbPool.writeWithoutTransaction
try db.beginTransaction()
...
try db.commit()
try db.execute(sql: "BEGIN TRANSACTION")
...
try db.execute(sql: "ROLLBACK")
}
Transactions can't be left opened unless you set the allowsUnsafeTransactions configuration flag:
// fatal error: A transaction has been left opened at the end of a database access
try dbQueue.inDatabase { db in
try db.execute(sql: "BEGIN TRANSACTION")
// <- no commit or rollback
}
You can ask if a transaction is currently opened:
func myCriticalMethod(_ db: Database) throws {
precondition(db.isInsideTransaction, "This method requires a transaction")
try ...
}
Yet, you have a better option than checking for transactions: critical database sections should use savepoints, described below:
func myCriticalMethod(_ db: Database) throws {
try db.inSavepoint {
// Here the database is guaranteed to be inside a transaction.
try ...
}
}
Statements grouped in a savepoint can be rollbacked without invalidating a whole transaction:
try dbQueue.write { db in
// Makes sure both inserts succeed, or none:
try db.inSavepoint {
try Credit(destinationAccount, amount).insert(db)
try Debit(sourceAccount, amount).insert(db)
return .commit
}
// Other savepoints, etc...
}
If an error is thrown from the savepoint block, the savepoint is rollbacked and the error is rethrown by the inSavepoint
method. If you return .rollback
instead of .commit
, the savepoint is also rollbacked, but no error is thrown.
Unlike transactions, savepoints can be nested. They implicitly open a transaction if no one was opened when the savepoint begins. As such, they behave just like nested transactions. Yet the database changes are only written to disk when the outermost transaction is committed:
try dbQueue.inDatabase { db in
try db.inSavepoint {
...
try db.inSavepoint {
...
return .commit
}
...
return .commit // writes changes to disk
}
}
SQLite savepoints are more than nested transactions, though. For advanced uses, use SQLite savepoint documentation.
SQLite supports three kinds of transactions: deferred (the default), immediate, and exclusive.
The transaction kind can be changed in the database configuration, or for each transaction:
// 1) Default configuration:
let dbQueue = try DatabaseQueue(path: "...")
// BEGIN DEFERED TRANSACTION ...
dbQueue.write { db in ... }
// BEGIN EXCLUSIVE TRANSACTION ...
dbQueue.inTransaction(.exclusive) { db in ... }
// 2) Customized default transaction kind:
var config = Configuration()
config.defaultTransactionKind = .immediate
let dbQueue = try DatabaseQueue(path: "...", configuration: config)
// BEGIN IMMEDIATE TRANSACTION ...
dbQueue.write { db in ... }
// BEGIN EXCLUSIVE TRANSACTION ...
dbQueue.inTransaction(.exclusive) { db in ... }
Prepared Statements let you prepare an SQL query and execute it later, several times if you need, with different arguments.
There are two kinds of prepared statements: select statements, and update statements:
try dbQueue.write { db in
let updateSQL = "INSERT INTO player (name, score) VALUES (:name, :score)"
let updateStatement = try db.makeUpdateStatement(sql: updateSQL)
let selectSQL = "SELECT * FROM player WHERE name = ?"
let selectStatement = try db.makeSelectStatement(sql: selectSQL)
}
The ?
and colon-prefixed keys like :name
in the SQL query are the statement arguments. You set them with arrays or dictionaries (arguments are actually of type StatementArguments, which happens to adopt the ExpressibleByArrayLiteral and ExpressibleByDictionaryLiteral protocols).
updateStatement.arguments = ["name": "Arthur", "score": 1000]
selectStatement.arguments = ["Arthur"]
After arguments are set, you can execute the prepared statement:
try updateStatement.execute()
Select statements can be used wherever a raw SQL query string would fit (see fetch queries):
let rows = try Row.fetchCursor(selectStatement) // A Cursor of Row
let players = try Player.fetchAll(selectStatement) // [Player]
let player = try Player.fetchOne(selectStatement) // Player?
You can set the arguments at the moment of the statement execution:
try updateStatement.execute(arguments: ["name": "Arthur", "score": 1000])
let player = try Player.fetchOne(selectStatement, arguments: ["Arthur"])
☝️ Note: it is a programmer error to reuse a prepared statement that has failed: GRDB may crash if you do so.
See row queries, value queries, and Records for more information.
When the same query will be used several times in the lifetime of your application, you may feel a natural desire to cache prepared statements.
Don't cache statements yourself.
☝️ Note: This is because you don't have the necessary tools. Statements are tied to specific SQLite connections and dispatch queues which you don't manage yourself, especially when you use database pools. A change in the database schema may, or may not invalidate a statement. On systems earlier than OSX 10.10 that don't have the sqlite3_close_v2 function, SQLite connections won't close properly if statements have been kept alive.
Instead, use the cachedUpdateStatement
and cachedSelectStatement
methods. GRDB does all the hard caching and memory management stuff for you:
let updateStatement = try db.cachedUpdateStatement(sql: sql)
let selectStatement = try db.cachedSelectStatement(sql: sql)
Should a cached prepared statement throw an error, don't reuse it (it is a programmer error). Instead, reload it from the cache.
SQLite lets you define SQL functions and aggregates.
A custom SQL function or aggregate extends SQLite:
SELECT reverse(name) FROM player; -- custom function
SELECT maxLength(name) FROM player; -- custom aggregate
let reverse = DatabaseFunction("reverse", argumentCount: 1, pure: true) { (values: [DatabaseValue]) in
// Extract string value, if any...
guard let string = String.fromDatabaseValue(values[0]) else {
return nil
}
// ... and return reversed string:
return String(string.reversed())
}
dbQueue.add(function: reverse) // Or dbPool.add(function: ...)
try dbQueue.read { db in
// "oof"
try String.fetchOne(db, sql: "SELECT reverse('foo')")!
}
The function argument takes an array of DatabaseValue, and returns any valid value (Bool, Int, String, Date, Swift enums, etc.) The number of database values is guaranteed to be argumentCount.
SQLite has the opportunity to perform additional optimizations when functions are "pure", which means that their result only depends on their arguments. So make sure to set the pure argument to true when possible.
Functions can take a variable number of arguments:
When you don't provide any explicit argumentCount, the function can take any number of arguments:
let averageOf = DatabaseFunction("averageOf", pure: true) { (values: [DatabaseValue]) in
let doubles = values.compactMap { Double.fromDatabaseValue($0) }
return doubles.reduce(0, +) / Double(doubles.count)
}
dbQueue.add(function: averageOf)
try dbQueue.read { db in
// 2.0
try Double.fetchOne(db, sql: "SELECT averageOf(1, 2, 3)")!
}
Functions can throw:
let sqrt = DatabaseFunction("sqrt", argumentCount: 1, pure: true) { (values: [DatabaseValue]) in
guard let double = Double.fromDatabaseValue(values[0]) else {
return nil
}
guard double >= 0 else {
throw DatabaseError(message: "invalid negative number")
}
return sqrt(double)
}
dbQueue.add(function: sqrt)
// SQLite error 1 with statement `SELECT sqrt(-1)`: invalid negative number
try dbQueue.read { db in
try Double.fetchOne(db, sql: "SELECT sqrt(-1)")!
}
Use custom functions in the query interface:
// SELECT reverseString("name") FROM player
Player.select(reverseString.apply(nameColumn))
GRDB ships with built-in SQL functions that perform unicode-aware string transformations. See Unicode.
Before registering a custom aggregate, you need to define a type that adopts the DatabaseAggregate
protocol:
protocol DatabaseAggregate {
// Initializes an aggregate
init()
// Called at each step of the aggregation
mutating func step(_ dbValues: [DatabaseValue]) throws
// Returns the final result
func finalize() throws -> DatabaseValueConvertible?
}
For example:
struct MaxLength : DatabaseAggregate {
var maxLength: Int = 0
mutating func step(_ dbValues: [DatabaseValue]) {
// At each step, extract string value, if any...
guard let string = String.fromDatabaseValue(dbValues[0]) else {
return
}
// ... and update the result
let length = string.count
if length > maxLength {
maxLength = length
}
}
func finalize() -> DatabaseValueConvertible? {
return maxLength
}
}
let maxLength = DatabaseFunction(
"maxLength",
argumentCount: 1,
pure: true,
aggregate: MaxLength.self)
dbQueue.add(function: maxLength) // Or dbPool.add(function: ...)
try dbQueue.read { db in
// Some Int
try Int.fetchOne(db, sql: "SELECT maxLength(name) FROM player")!
}
The step
method of the aggregate takes an array of DatabaseValue. This array contains as many values as the argumentCount parameter (or any number of values, when argumentCount is omitted).
The finalize
method of the aggregate returns the final aggregated value (Bool, Int, String, Date, Swift enums, etc.).
SQLite has the opportunity to perform additional optimizations when aggregates are "pure", which means that their result only depends on their inputs. So make sure to set the pure argument to true when possible.
Use custom aggregates in the query interface:
// SELECT maxLength("name") FROM player
let request = Player.select(maxLength.apply(nameColumn))
try Int.fetchOne(db, request) // Int?
GRDB comes with a set of schema introspection methods:
try dbQueue.read { db in
// Bool, true if the table exists
try db.tableExists("player")
// [ColumnInfo], the columns in the table
try db.columns(in: "player")
// PrimaryKeyInfo
try db.primaryKey("player")
// [ForeignKeyInfo], the foreign keys defined on the table
try db.foreignKeys(on: "player")
// [IndexInfo], the indexes defined on the table
try db.indexes(on: "player")
// Bool, true if column(s) is a unique key (primary key or unique index)
try db.table("player", hasUniqueKey: ["email"])
}
// Bool, true if argument is the name of an internal SQLite table
Database.isSQLiteInternalTable(...)
// Bool, true if argument is the name of an internal GRDB table
Database.isGRDBInternalTable(...)
Row adapters let you present database rows in the way expected by the row consumers.
They basically help two incompatible row interfaces to work together. For example, a row consumer expects a column named "consumed", but the produced row has a column named "produced".
In this case, the ColumnMapping
row adapter comes in handy:
// Fetch a 'produced' column, and consume a 'consumed' column:
let adapter = ColumnMapping(["consumed": "produced"])
let row = try Row.fetchOne(db, sql: "SELECT 'Hello' AS produced", adapter: adapter)!
row["consumed"] // "Hello"
row["produced"] // nil
Row adapters are values that adopt the RowAdapter protocol. You can implement your own custom adapters (🔥 EXPERIMENTAL), or use one of the four built-in adapters, described below.
To see how row adapters can be used, see Joined Queries Support.
ColumnMapping renames columns. Build one with a dictionary whose keys are adapted column names, and values the column names in the raw row:
// [newName:"Hello"]
let adapter = ColumnMapping(["newName": "oldName"])
let row = try Row.fetchOne(db, sql: "SELECT 'Hello' AS oldName", adapter: adapter)!
SuffixRowAdapter
hides the first columns in a row:
// [b:1 c:2]
let adapter = SuffixRowAdapter(fromIndex: 1)
let row = try Row.fetchOne(db, sql: "SELECT 0 AS a, 1 AS b, 2 AS c", adapter: adapter)!
RangeRowAdapter
only exposes a range of columns.
// [b:1]
let adapter = RangeRowAdapter(1..<2)
let row = try Row.fetchOne(db, sql: "SELECT 0 AS a, 1 AS b, 2 AS c", adapter: adapter)!
EmptyRowAdapter
hides all columns.
let adapter = EmptyRowAdapter()
let row = try Row.fetchOne(db, sql: "SELECT 0 AS a, 1 AS b, 2 AS c", adapter: adapter)!
row.isEmpty // true
This limit adapter may turn out useful in some narrow use cases. You'll be happy to find it when you need it.
ScopeAdapter
defines row scopes:
let adapter = ScopeAdapter([
"left": RangeRowAdapter(0..<2),
"right": RangeRowAdapter(2..<4)])
let row = try Row.fetchOne(db, sql: "SELECT 0 AS a, 1 AS b, 2 AS c, 3 AS d", adapter: adapter)!
ScopeAdapter does not change the columns and values of the fetched row. Instead, it defines scopes, which you access through the Row.scopes
property:
row // [a:0 b:1 c:2 d:3]
row.scopes["left"] // [a:0 b:1]
row.scopes["right"] // [c:2 d:3]
row.scopes["missing"] // nil
Scopes can be nested:
let adapter = ScopeAdapter([
"left": ScopeAdapter([
"left": RangeRowAdapter(0..<1),
"right": RangeRowAdapter(1..<2)]),
"right": ScopeAdapter([
"left": RangeRowAdapter(2..<3),
"right": RangeRowAdapter(3..<4)])
])
let row = try Row.fetchOne(db, sql: "SELECT 0 AS a, 1 AS b, 2 AS c, 3 AS d", adapter: adapter)!
let leftRow = row.scopes["left"]!
leftRow.scopes["left"] // [a:0]
leftRow.scopes["right"] // [b:1]
let rightRow = row.scopes["right"]!
rightRow.scopes["left"] // [c:2]
rightRow.scopes["right"] // [d:3]
Any adapter can be extended with scopes:
let baseAdapter = RangeRowAdapter(0..<2)
let adapter = ScopeAdapter(base: baseAdapter, scopes: [
"remainder": SuffixRowAdapter(fromIndex: 2)])
let row = try Row.fetchOne(db, sql: "SELECT 0 AS a, 1 AS b, 2 AS c, 3 AS d", adapter: adapter)!
row // [a:0 b:1]
row.scopes["remainder"] // [c:2 d:3]
If not all SQLite APIs are exposed in GRDB, you can still use the SQLite C Interface and call SQLite C functions.
Those functions are embedded right into the GRDBCustom module. Otherwise, you'll need to import SQLite3
, SQLCipher
, or CSQLite
, depending on the GRDB flavor you are using:
// Swift Package Manager
import CSQLite
// SQLCipher
import SQLCipher
// System SQLite
import SQLite3
let sqliteVersion = String(cString: sqlite3_libversion())
Raw pointers to database connections and statements are available through the Database.sqliteConnection
and Statement.sqliteStatement
properties:
try dbQueue.read { db in
// The raw pointer to a database connection:
let sqliteConnection = db.sqliteConnection
// The raw pointer to a statement:
let statement = try db.makeSelectStatement(sql: "SELECT ...")
let sqliteStatement = statement.sqliteStatement
}
☝️ Notes
- Those pointers are owned by GRDB: don't close connections or finalize statements created by GRDB.
- GRDB opens SQLite connections in the "multi-thread mode", which (oddly) means that they are not thread-safe. Make sure you touch raw databases and statements inside their dedicated dispatch queues.
- Use the raw SQLite C Interface at your own risk. GRDB won't prevent you from shooting yourself in the foot.
On top of the SQLite API, GRDB provides protocols and a class that help manipulating database rows as regular objects named "records":
try dbQueue.write { db in
if var place = try Place.fetchOne(db, key: 1) {
place.isFavorite = true
try place.update(db)
}
}
Of course, you need to open a database connection, and create database tables first.
To define your custom records, you subclass the ready-made Record
class, or you extend your structs and classes with protocols that come with focused sets of features: fetching methods, persistence methods, record comparison...
Extending structs with record protocols is more "swifty". Subclassing the Record class is more "classic". You can choose either way. See some examples of record definitions, and the list of record methods for an overview.
☝️ Note: if you are familiar with Core Data's NSManagedObject or Realm's Object, you may experience a cultural shock: GRDB records are not uniqued, do not auto-update, and do not lazy-load. This is both a purpose, and a consequence of protocol-oriented programming. You should read How to build an iOS application with SQLite and GRDB.swift for a general introduction.
💡 Tip: after you have read this chapter, check the Good Practices for Designing Record Types Guide.
💡 Tip: see the Demo Application for a sample app that uses records.
Overview
Protocols and the Record Class
- Record Protocols Overview
- FetchableRecord Protocol
- TableRecord Protocol
- PersistableRecord Protocol
- Codable Records
- Record Class
- Record Comparison
- Record Customization Options
Records in a Glance
To insert a record in the database, call the insert
method:
let player = Player(name: "Arthur", email: "arthur@example.com")
try player.insert(db)
👉 insert
is available for subclasses of the Record class, and types that adopt the PersistableRecord protocol.
To fetch records from the database, call a fetching method:
let arthur = try Player.fetchOne(db, // Player?
sql: "SELECT * FROM players WHERE name = ?",
arguments: ["Arthur"])
let bestPlayers = try Player // [Player]
.order(Column("score").desc)
.limit(10)
.fetchAll(db)
let spain = try Country.fetchOne(db, key: "ES") // Country?
👉 Fetching from raw SQL is available for subclasses of the Record class, and types that adopt the FetchableRecord protocol.
👉 Fetching without SQL, using the query interface, is available for subclasses of the Record class, and types that adopt both FetchableRecord and TableRecord protocol.
To update a record in the database, call the update
method:
if let player = try Player.fetchOne(db, key: 1)
player.score = 1000
try player.update(db)
}
It is possible to avoid useless updates:
if var player = try Player.fetchOne(db, key: 1) {
// does not hit the database if score has not changed
try player.updateChanges(db) {
$0.score = 1000
}
}
For batch updates, execute an SQL query:
try db.execute(sql: "UPDATE player SET synchronized = 1")
👉 update methods are available for subclasses of the Record class, and types that adopt the PersistableRecord protocol.
To delete a record in the database, call the delete
method:
if let player = try Player.fetchOne(db, key: 1) {
try player.delete(db)
}
You can also delete by primary key, or any unique index:
try Player.deleteOne(db, key: 1)
try Player.deleteOne(db, key: ["email": "arthur@example.com"])
try Country.deleteAll(db, keys: ["FR", "US"])
For batch deletes, execute an SQL query, or see the query interface:
try Player
.filter(Column("email") == nil)
.deleteAll(db)
👉 delete methods are available for subclasses of the Record class, and types that adopt the PersistableRecord protocol.
To count records, call the fetchCount
method:
let playerCount: Int = try Player.fetchCount(db)
let playerWithEmailCount: Int = try Player
.filter(Column("email") == nil)
.fetchCount(db)
👉 fetchCount
is available for subclasses of the Record class, and types that adopt the TableRecord protocol.
Details follow:
- Record Protocols Overview
- FetchableRecord Protocol
- TableRecord Protocol
- PersistableRecord Protocol
- Codable Records
- Record Class
- Record Comparison
- Record Customization Options
- Examples of Record Definitions
- List of Record Methods
GRDB ships with three record protocols. Your own types will adopt one or several of them, according to the abilities you want to extend your types with.
-
FetchableRecord is able to decode database rows.
It is always possible to decode rows without this protocol:
struct Place { ... } try dbQueue.read { db in let rows = try Row.fetchAll(db, sql: "SELECT * FROM place") let places: [Place] = rows.map { row in return Place( id: row["id"], title: row["title"], coordinate: CLLocationCoordinate2D( latitude: row["latitude"], longitude: row["longitude"])) ) } }
But FetchableRecord lets you write code that is easier to read, and more efficient as well, both in terms of performance and memory usage:
struct Place: FetchableRecord { ... } try dbQueue.read { db in let places = try Place.fetchAll(db, sql: "SELECT * FROM place") }
💡 Tip: FetchableRecord can derive its implementation from the standard Decodable protocol. See Codable Records for more information.
FetchableRecord can decode database rows, but it is not able to build SQL requests for you. For that, you also need TableRecord:
-
TableRecord is able to generate SQL queries:
struct Place: TableRecord { ... } // SELECT * FROM place ORDER BY title let request = Place.order(Column("title"))
When a type adopts both TableRecord and FetchableRecord, it can load from those requests:
struct Place: TableRecord, FetchableRecord { ... } try dbQueue.read { db in let places = try Place.order(Column("title")).fetchAll(db) let paris = try Place.fetchOne(key: 1) }
-
PersistableRecord is able to write: it can create, update, and delete rows in the database:
struct Place : PersistableRecord { ... } try dbQueue.write { db in try Place.delete(db, key: 1) try Place(...).insert(db) }
A persistable record can also compare itself against other records, and avoid useless database updates.
💡 Tip: PersistableRecord can derive its implementation from the standard Encodable protocol. See Codable Records for more information.
The FetchableRecord protocol grants fetching methods to any type that can be built from a database row:
protocol FetchableRecord {
/// Row initializer
init(row: Row)
}
To use FetchableRecord, subclass the Record class, or adopt it explicitly. For example:
struct Place {
var id: Int64?
var title: String
var coordinate: CLLocationCoordinate2D
}
extension Place : FetchableRecord {
init(row: Row) {
id = row["id"]
title = row["title"]
coordinate = CLLocationCoordinate2D(
latitude: row["latitude"],
longitude: row["longitude"])
}
}
Rows also accept column enums:
extension Place : FetchableRecord {
enum Columns: String, ColumnExpression {
case id, title, latitude, longitude
}
init(row: Row) {
id = row[Columns.id]
title = row[Columns.title]
coordinate = CLLocationCoordinate2D(
latitude: row[Columns.latitude],
longitude: row[Columns.longitude])
}
}
See column values for more information about the row[]
subscript.
When your record type adopts the standard Decodable protocol, you don't have to provide the implementation for init(row:)
. See Codable Records for more information:
// That's all
struct Player: Decodable, FetchableRecord {
var id: Int64
var name: String
var score: Int
}
FetchableRecord allows adopting types to be fetched from SQL queries:
try Place.fetchCursor(db, sql: "SELECT ...", arguments:...) // A Cursor of Place
try Place.fetchAll(db, sql: "SELECT ...", arguments:...) // [Place]
try Place.fetchOne(db, sql: "SELECT ...", arguments:...) // Place?
See fetching methods for information about the fetchCursor
, fetchAll
and fetchOne
methods. See StatementArguments for more information about the query arguments.
☝️ Note: for performance reasons, the same row argument to
init(row:)
is reused during the iteration of a fetch query. If you want to keep the row for later use, make sure to store a copy:self.row = row.copy()
.
☝️ Note: The
FetchableRecord.init(row:)
initializer fits the needs of most applications. But some application are more demanding than others. When FetchableRecord does not exactly provide the support you need, have a look at the Beyond FetchableRecord chapter.
The TableRecord protocol generates SQL for you. To use TableRecord, subclass the Record class, or adopt it explicitly:
protocol TableRecord {
static var databaseTableName: String { get }
static var databaseSelection: [SQLSelectable] { get }
}
The databaseSelection
type property is optional, and documented in the Columns Selected by a Request chapter.
The databaseTableName
type property is the name of a database table. By default, it is derived from the type name:
struct Place: TableRecord { }
print(Place.databaseTableName) // prints "place"
For example:
- Place:
place
- Country:
country
- PostalAddress:
postalAddress
- HTTPRequest:
httpRequest
- TOEFL:
toefl
You can still provide a custom table name:
struct Place: TableRecord {
static let databaseTableName = "location"
}
print(Place.databaseTableName) // prints "location"
Subclasses of the Record class must always override their superclass's databaseTableName
property:
class Place: Record {
override class var databaseTableName: String {
return "place"
}
}
print(Place.databaseTableName) // prints "place"
When a type adopts both TableRecord and FetchableRecord, it can be fetched using the query interface:
// SELECT * FROM place WHERE name = 'Paris'
let paris = try Place.filter(nameColumn == "Paris").fetchOne(db)
TableRecord can also fetch records by primary key:
try Player.fetchOne(db, key: 1) // Player?
try Player.fetchAll(db, keys: [1, 2, 3]) // [Player]
try Country.fetchOne(db, key: "FR") // Country?
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]
When the table has no explicit primary key, GRDB uses the hidden "rowid" column:
// SELECT * FROM document WHERE rowid = 1
try Document.fetchOne(db, key: 1) // Document?
For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:
// SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
try Citizenship.fetchOne(db, key: ["citizenId": 1, "countryCode": "FR"]) // Citizenship?
GRDB record types can create, update, and delete rows in the database.
Those abilities are granted by three protocols:
// Defines how a record encodes itself into the database
protocol EncodableRecord {
/// Defines the values persisted in the database
func encode(to container: inout PersistenceContainer)
}
// Adds persistence methods
protocol MutablePersistableRecord: TableRecord, EncodableRecord {
/// Optional method that lets your adopting type store its rowID upon
/// successful insertion. Don't call it directly: it is called for you.
mutating func didInsert(with rowID: Int64, for column: String?)
}
// Adds immutability
protocol PersistableRecord: MutablePersistableRecord {
/// Non-mutating version of the optional didInsert(with:for:)
func didInsert(with rowID: Int64, for column: String?)
}
Yes, three protocols instead of one. Here is how you pick one or the other:
-
If your type is a class, choose
PersistableRecord
. On top of that, implementdidInsert(with:for:)
if the database table has an auto-incremented primary key. -
If your type is a struct, and the database table has an auto-incremented primary key, choose
MutablePersistableRecord
, and implementdidInsert(with:for:)
. -
Otherwise, choose
PersistableRecord
, and ignoredidInsert(with:for:)
.
The encode(to:)
method defines which values (Bool, Int, String, Date, Swift enums, etc.) are assigned to database columns.
The optional didInsert
method lets the adopting type store its rowID after successful insertion, and is only useful for tables that have an auto-incremented primary key. It is called from a protected dispatch queue, and serialized with all database updates.
To use the persistable protocols, subclass the Record class, or adopt one of them explicitly. For example:
extension Place : MutablePersistableRecord {
/// The values persisted in the database
func encode(to container: inout PersistenceContainer) {
container["id"] = id
container["title"] = title
container["latitude"] = coordinate.latitude
container["longitude"] = coordinate.longitude
}
// Update auto-incremented id upon successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
var paris = Place(
id: nil,
title: "Paris",
coordinate: CLLocationCoordinate2D(latitude: 48.8534100, longitude: 2.3488000))
try paris.insert(db)
paris.id // some value
Persistence containers also accept column enums:
extension Place : MutablePersistableRecord {
enum Columns: String, ColumnExpression {
case id, title, latitude, longitude
}
func encode(to container: inout PersistenceContainer) {
container[Columns.id] = id
container[Columns.title] = title
container[Columns.latitude] = coordinate.latitude
container[Columns.longitude] = coordinate.longitude
}
}
When your record type adopts the standard Encodable protocol, you don't have to provide the implementation for encode(to:)
. See Codable Records for more information:
// That's all
struct Player: Encodable, MutablePersistableRecord {
var id: Int64?
var name: String
var score: Int
// Update auto-incremented id upon successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
Record subclasses and types that adopt PersistableRecord are given default implementations for methods that insert, update, and delete:
// Instance methods
try place.save(db) // INSERT or UPDATE
try place.insert(db) // INSERT
try place.update(db) // UPDATE
try place.update(db, columns: ...) // UPDATE
try place.updateChanges(db, from: ...) // Maybe UPDATE
try place.updateChanges(db) { ... } // Maybe UPDATE
try place.updateChanges(db) // Maybe UPDATE (Record class only)
try place.delete(db) // DELETE
try place.exists(db)
// Type methods
try Place.deleteAll(db) // DELETE
try Place.deleteAll(db, keys:...) // DELETE
try Place.deleteOne(db, key:...) // DELETE
-
insert
,update
,save
anddelete
can throw a DatabaseError. -
update
andupdateChanges
can also throw a PersistenceError, should the update fail because there is no matching row in the database.When saving an object that may or may not already exist in the database, prefer the
save
method: -
save
makes sure your values are stored in the database.It performs an UPDATE if the record has a non-null primary key, and then, if no row was modified, an INSERT. It directly perfoms an INSERT if the record has no primary key, or a null primary key.
Despite the fact that it may execute two SQL statements,
save
behaves as an atomic operation: GRDB won't allow any concurrent thread to sneak in (see concurrency). -
delete
returns whether a database row was deleted or not.
All primary keys are supported, including composite primary keys that span several columns, and the implicit rowid primary key.
Your custom type may want to perform extra work when the persistence methods are invoked.
For example, it may want to have its UUID automatically set before inserting. Or it may want to validate its values before saving.
When you subclass Record, you simply have to override the customized method, and call super
:
class Player : Record {
var uuid: UUID?
override func insert(_ db: Database) throws {
if uuid == nil {
uuid = UUID()
}
try super.insert(db)
}
}
If you use the raw PersistableRecord protocol, use one of the special methods performInsert
, performUpdate
, performSave
, performDelete
, or performExists
:
struct Link : PersistableRecord {
var url: URL
func insert(_ db: Database) throws {
try validate()
try performInsert(db)
}
func update(_ db: Database, columns: Set<String>) throws {
try validate()
try performUpdate(db, columns: columns)
}
func validate() throws {
if url.host == nil {
throw ValidationError("url must be absolute.")
}
}
}
☝️ Note: the special methods
performInsert
,performUpdate
, etc. are reserved for your custom implementations. Do not use them elsewhere. Do not provide another implementation for those methods.☝️ Note: it is recommended that you do not implement your own version of the
save
method. Its default implementation forwards the job toupdate
orinsert
: these are the methods that may need customization, notsave
.
Record types that adopt an archival protocol (Codable, Encodable or Decodable) get free database support just by declaring conformance to the desired record protocols:
// Declare a record...
struct Player: Codable, FetchableRecord, PersistableRecord {
var name: String
var score: Int
}
// ...and there you go:
try dbQueue.write { db in
try Player(name: "Arthur", score: 100).insert(db)
let players = try Player.fetchAll(db)
}
Codable records encode and decode their properties according to their own implementation of the Encodable and Decodable protocols. Yet databases have specific requirements:
- Properties are always coded according to their preferred database representation, when they have one (all values that adopt the DatabaseValueConvertible protocol).
- You can customize the encoding and decoding of dates and uuids.
- Complex properties (arrays, dictionaries, nested structs, etc.) are stored as JSON.
For more information about Codable records, see:
- JSON Columns
- Date and UUID Coding Strategies
- The userInfo Dictionary
- Tip: Derive Columns from Coding Keys
💡 Tip: see the Demo Application for a sample app that uses Codable records.
When a Codable record contains a property that is not a simple value (Bool, Int, String, Date, Swift enums, etc.), that value is encoded and decoded as a JSON string. For example:
enum AchievementColor: String, Codable {
case bronze, silver, gold
}
struct Achievement: Codable {
var name: String
var color: AchievementColor
}
struct Player: Codable, FetchableRecord, PersistableRecord {
var name: String
var score: Int
var achievements: [Achievement] // stored in a JSON column
}
try! dbQueue.write { db in
// INSERT INTO player (name, score, achievements)
// VALUES (
// 'Arthur',
// 100,
// '[{"color":"gold","name":"Use Codable Records"}]')
let achievement = Achievement(name: "Use Codable Records", color: .gold)
let player = Player(name: "Arthur", score: 100, achievements: [achievement])
try player.insert(db)
}
GRDB uses the standard JSONDecoder and JSONEncoder from Foundation. By default, Data values are handled with the .base64
strategy, Date with the .millisecondsSince1970
strategy, and non conforming floats with the .throw
strategy.
You can customize the JSON format by implementing those methods:
protocol FetchableRecord {
static func databaseJSONDecoder(for column: String) -> JSONDecoder
}
protocol EncodableRecord {
static func databaseJSONEncoder(for column: String) -> JSONEncoder
}
💡 Tip: Make sure you set the JSONEncoder
sortedKeys
option, available from iOS 11.0+, macOS 10.13+, tvOS 9.0+ and watchOS 4.0+. This option makes sure that the JSON output is stable. This stability is required for Record Comparison to work as expected, and database observation tools such as ValueObservation to accurately recognize changed records.
By default, Codable Records encode and decode their Date and UUID properties as described in the general Date and DateComponents and UUID chapters.
To sum up: dates encode themselves in the "YYYY-MM-DD HH:MM:SS.SSS" format, in the UTC time zone, and decode a variety of date formats and timestamps. UUIDs encode themselves as 16-bytes data blobs, and decode both 16-bytes data blobs and strings such as "E621E1F8-C36C-495A-93FC-0C247A3E6E5F".
Those behaviors can be overridden:
protocol FetchableRecord {
static var databaseDateDecodingStrategy: DatabaseDateDecodingStrategy { get }
}
protocol EncodableRecord {
static var databaseDateEncodingStrategy: DatabaseDateEncodingStrategy { get }
static var databaseUUIDEncodingStrategy: DatabaseUUIDEncodingStrategy { get }
}
See DatabaseDateDecodingStrategy, DatabaseDateEncodingStrategy, and DatabaseUUIDEncodingStrategy to learn about all available strategies.
☝️ Note: there is no customization of uuid decoding, because UUID can already decode all its encoded variants (16-bytes blobs, and uuid strings).
Your Codable Records can be stored in the database, but they may also have other purposes. In this case, you may need to customize their implementations of Decodable.init(from:)
and Encodable.encode(to:)
, depending on the context.
The standard way to provide such context is the userInfo
dictionary. Implement those properties:
protocol FetchableRecord {
static var databaseDecodingUserInfo: [CodingUserInfoKey: Any] { get }
}
protocol EncodableRecord {
static var databaseEncodingUserInfo: [CodingUserInfoKey: Any] { get }
}
For example, here is a Player type that customizes its decoding:
// A key that holds a decoder's name
let decoderName = CodingUserInfoKey(rawValue: "decoderName")!
struct Player: FetchableRecord, Decodable {
init(from decoder: Decoder) throws {
// Print the decoder name
let decoderName = decoder.userInfo[decoderName] as? String
print("Decoded from \(decoderName ?? "unknown decoder")")
...
}
}
You can have a specific decoding from JSON...
// prints "Decoded from JSON"
let decoder = JSONDecoder()
decoder.userInfo = [decoderName: "JSON"]
let player = try decoder.decode(Player.self, from: jsonData)
... and another one from database rows:
extension Player: FetchableRecord {
static let databaseDecodingUserInfo: [CodingUserInfoKey: Any] = [decoderName: "database row"]
}
// prints "Decoded from database row"
let player = try Player.fetchOne(db, ...)
☝️ Note: make sure the
databaseDecodingUserInfo
anddatabaseEncodingUserInfo
properties are explicitly declared as[CodingUserInfoKey: Any]
. If they are not, the Swift compiler may silently miss the protocol requirement, resulting in sticky empty userInfo.
Codable types are granted with a CodingKeys enum. You can use them to safely define database columns:
struct Player: Codable {
var id: Int64
var name: String
var score: Int
}
extension Player: FetchableRecord, PersistableRecord {
enum Columns {
static let id = Column(CodingKeys.id)
static let name = Column(CodingKeys.name)
static let score = Column(CodingKeys.score)
}
}
See the query interface and Good Practices for Designing Record Types for further information.
Record is a class that is designed to be subclassed. It inherits its features from the FetchableRecord, TableRecord, and PersistableRecord protocols. On top of that, Record instances can compare against previous versions of themselves in order to avoid useless updates.
Record subclasses define their custom database relationship by overriding database methods. For example:
class Place: Record {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D
init(id: Int64?, title: String, isFavorite: Bool, coordinate: CLLocationCoordinate2D) {
self.id = id
self.title = title
self.isFavorite = isFavorite
self.coordinate = coordinate
super.init()
}
/// The table name
override class var databaseTableName: String {
return "place"
}
/// The table columns
enum Columns: String, ColumnExpression {
case id, title, favorite, latitude, longitude
}
/// Creates a record from a database row
required init(row: Row) {
id = row[Columns.id]
title = row[Columns.title]
isFavorite = row[Columns.favorite]
coordinate = CLLocationCoordinate2D(
latitude: row[Columns.latitude],
longitude: row[Columns.longitude])
super.init(row: row)
}
/// The values persisted in the database
override func encode(to container: inout PersistenceContainer) {
container[Columns.id] = id
container[Columns.title] = title
container[Columns.favorite] = isFavorite
container[Columns.latitude] = coordinate.latitude
container[Columns.longitude] = coordinate.longitude
}
/// Update record ID after a successful insertion
override func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
Records that adopt the EncodableRecord protocol can compare against other records, or against previous versions of themselves.
This helps avoiding costly UPDATE statements when a record has not been edited.
- The
updateChanges
Methods - The
databaseEquals
Method - The
databaseChanges
andhasDatabaseChanges
Methods
The updateChanges
methods perform a database update of the changed columns only (and does nothing if record has no change).
-
updateChanges(_:from:)
This method lets you compare two records:
if let oldPlayer = try Player.fetchOne(db, key: 42) { var newPlayer = oldPlayer newPlayer.score = 100 if try newPlayer.updateChanges(db, from: oldPlayer) { print("player was modified, and updated in the database") } else { print("player was not modified, and database was not hit") } }
-
updateChanges(_:with:)
This method lets you update a record in place:
if var player = try Player.fetchOne(db, key: 42) { let modified = try player.updateChanges(db) { $0.score = 100 } if modified { print("player was modified, and updated in the database") } else { print("player was not modified, and database was not hit") } }
-
updateChanges(_:)
(Record class only)Instances of the Record class are able to compare against themselves, and know if they have changes that have not been saved since the last fetch or saving:
// Record class only if let player = try Player.fetchOne(db, key: 42) { player.score = 100 if try player.updateChanges(db) { print("player was modified, and updated in the database") } else { print("player was not modified, and database was not hit") } }
This method returns whether two records have the same database representation:
let oldPlayer: Player = ...
var newPlayer: Player = ...
if newPlayer.databaseEquals(oldPlayer) == false {
try newPlayer.save(db)
}
☝️ Note: The comparison is performed on the database representation of records. As long as your record type adopts the EncodableRecord protocol, you don't need to care about Equatable.
databaseChanges(from:)
returns a dictionary of differences between two records:
let oldPlayer = Player(id: 1, name: "Arthur", score: 100)
let newPlayer = Player(id: 1, name: "Arthur", score: 1000)
for (column, oldValue) in newPlayer.databaseChanges(from: oldPlayer) {
print("\(column) was \(oldValue)")
}
// prints "score was 100"
The Record class is able to compare against itself:
// Record class only
let player = Player(id: 1, name: "Arthur", score: 100)
try player.insert(db)
player.score = 1000
for (column, oldValue) in player.databaseChanges {
print("\(column) was \(oldValue)")
}
// prints "score was 100"
Record instances also have a hasDatabaseChanges
property:
// Record class only
player.score = 1000
if player.hasDatabaseChanges {
try player.save(db)
}
Record.hasDatabaseChanges
is false after a Record instance has been fetched or saved into the database. Subsequent modifications may set it, or not: hasDatabaseChanges
is based on value comparison. Setting a property to the same value does not set the changed flag:
let player = Player(name: "Barbara", score: 750)
player.hasDatabaseChanges // true
try player.insert(db)
player.hasDatabaseChanges // false
player.name = "Barbara"
player.hasDatabaseChanges // false
player.score = 1000
player.hasDatabaseChanges // true
player.databaseChanges // ["score": 750]
For an efficient algorithm which synchronizes the content of a database table with a JSON payload, check JSONSynchronization.playground.
GRDB records come with many default behaviors, that are designed to fit most situations. Many of those defaults can be customized for your specific needs:
- Customizing the Persistence Methods: define what happens when you call a persistance method such as
player.insert(db)
- Conflict Resolution: Run
INSERT OR REPLACE
queries, and generally define what happens when a persistence method violates a unique index. - The Implicit RowID Primary Key: all about the special
rowid
column. - Columns Selected by a Request: define which columns are selected by requests such as
Player.fetchAll(db)
. - Beyond FetchableRecord: the FetchableRecord protocol is not the end of the story.
Codable Records have a few extra options:
- JSON Columns: control the format of JSON columns.
- Date and UUID Coding Strategies: control the format of Date and UUID properties in your Codable records.
- The userInfo Dictionary: adapt your Codable implementation for the database.
Insertions and updates can create conflicts: for example, a query may attempt to insert a duplicate row that violates a unique index.
Those conflicts normally end with an error. Yet SQLite let you alter the default behavior, and handle conflicts with specific policies. For example, the INSERT OR REPLACE
statement handles conflicts with the "replace" policy which replaces the conflicting row instead of throwing an error.
The five different policies are: abort (the default), replace, rollback, fail, and ignore.
SQLite let you specify conflict policies at two different places:
-
In the definition of the database table:
// CREATE TABLE player ( // id INTEGER PRIMARY KEY AUTOINCREMENT, // email TEXT UNIQUE ON CONFLICT REPLACE // ) try db.create(table: "player") { t in t.autoIncrementedPrimaryKey("id") t.column("email", .text).unique(onConflict: .replace) // <-- } // Despite the unique index on email, both inserts succeed. // The second insert replaces the first row: try db.execute(sql: "INSERT INTO player (email) VALUES (?)", arguments: ["arthur@example.com"]) try db.execute(sql: "INSERT INTO player (email) VALUES (?)", arguments: ["arthur@example.com"])
-
In each modification query:
// CREATE TABLE player ( // id INTEGER PRIMARY KEY AUTOINCREMENT, // email TEXT UNIQUE // ) try db.create(table: "player") { t in t.autoIncrementedPrimaryKey("id") t.column("email", .text).unique() } // Again, despite the unique index on email, both inserts succeed. try db.execute(sql: "INSERT OR REPLACE INTO player (email) VALUES (?)", arguments: ["arthur@example.com"]) try db.execute(sql: "INSERT OR REPLACE INTO player (email) VALUES (?)", arguments: ["arthur@example.com"])
When you want to handle conflicts at the query level, specify a custom persistenceConflictPolicy
in your type that adopts the PersistableRecord protocol. It will alter the INSERT and UPDATE queries run by the insert
, update
and save
persistence methods:
protocol MutablePersistableRecord {
/// The policy that handles SQLite conflicts when records are
/// inserted or updated.
///
/// This property is optional: its default value uses the ABORT
/// policy for both insertions and updates, so that GRDB generate
/// regular INSERT and UPDATE queries.
static var persistenceConflictPolicy: PersistenceConflictPolicy { get }
}
struct Player : MutablePersistableRecord {
static let persistenceConflictPolicy = PersistenceConflictPolicy(
insert: .replace,
update: .replace)
}
// INSERT OR REPLACE INTO player (...) VALUES (...)
try player.insert(db)
☝️ Note: the
ignore
policy does not play well at all with thedidInsert
method which notifies the rowID of inserted records. Choose your poison:
- if you specify the
ignore
policy in the database table definition, don't implement thedidInsert
method: it will be called with some random id in case of failed insert.- if you specify the
ignore
policy at the query level, thedidInsert
method is never called.☝️ Note: The
replace
policy may have to delete rows so that inserts and updates can succeed. Those deletions are not reported to transaction observers (this might change in a future release of SQLite).
All SQLite tables have a primary key. Even when the primary key is not explicit:
// No explicit primary key
try db.create(table: "event") { t in
t.column("message", .text)
t.column("date", .datetime)
}
// No way to define an explicit primary key
try db.create(virtualTable: "book", using: FTS4()) { t in
t.column("title")
t.column("author")
t.column("body")
}
The implicit primary key is stored in the hidden column rowid
. Hidden means that SELECT *
does not select it, and yet it can be selected and queried: SELECT *, rowid ... WHERE rowid = 1
.
Some GRDB methods will automatically use this hidden column when a table has no explicit primary key:
// SELECT * FROM event WHERE rowid = 1
let event = try Event.fetchOne(db, key: 1)
// DELETE FROM book WHERE rowid = 1
try Book.deleteOne(db, key: 1)
By default, a record type that wraps a table without any explicit primary key doesn't know about the hidden rowid column.
Without primary key, records don't have any identity, and the persistence method can behave in undesired fashion: update()
throws errors, save()
always performs insertions and may break constraints, exists()
is always false.
When SQLite won't let you provide an explicit primary key (as in full-text tables, for example), you may want to make your record type fully aware of the hidden rowid column:
-
Have the
databaseSelection
static property (from the TableRecord protocol) return the hidden rowid column:struct Event : TableRecord { static let databaseSelection: [SQLSelectable] = [AllColumns(), Column.rowID] } // When you subclass Record, you need an override: class Book : Record { override class var databaseSelection: [SQLSelectable] { return [AllColums(), Column.rowID] } }
GRDB will then select the
rowid
column by default:// SELECT *, rowid FROM event let events = try Event.fetchAll(db)
-
Have
init(row:)
from the FetchableRecord protocol consume the "rowid" column:struct Event : FetchableRecord { var id: Int64? init(row: Row) { id = row[Column.rowID] } }
Your fetched records will then know their ids:
let event = try Event.fetchOne(db)! event.id // some value
-
Encode the rowid in
encode(to:)
, and keep it in thedidInsert(with:for:)
method (both from the PersistableRecord and MutablePersistableRecord protocols):struct Event : MutablePersistableRecord { var id: Int64? func encode(to container: inout PersistenceContainer) { container[Column.rowID] = id container["message"] = message container["date"] = date } // Update auto-incremented id upon successful insertion mutating func didInsert(with rowID: Int64, for column: String?) { id = rowID } }
You will then be able to track your record ids, update them, or check for their existence:
let event = Event(message: "foo", date: Date()) // Insertion sets the record id: try event.insert(db) event.id // some value // Record can be updated: event.message = "bar" try event.update(db) // Record knows if it exists: event.exists(db) // true
Some GRDB users eventually discover that the FetchableRecord protocol does not fit all situations. Use cases that are not well handled by FetchableRecord include:
-
Your application needs polymorphic row decoding: it decodes some type or another, depending on the values contained in a database row.
-
Your application needs to decode rows with a context: each decoded value should be initialized with some extra value that does not come from the database.
-
Your application needs a record type that supports untrusted databases, and may fail at decoding database rows (throw an error when a row contains invalid values).
Since those use cases are not well handled by FetchableRecord, don't try to implement them on top of this protocol: you'll just fight the framework.
Instead, please have a look at the CustomizedDecodingOfDatabaseRows playground. You'll run some sample code, and learn how to escape FetchableRecord when you need. And remember that leaving FetchableRecord will not deprive you of query interface requests and generally all SQL generation features of the TableRecord and PersistableRecord protocols.
We will show below how to declare a record type for the following database table:
try dbQueue.write { db in
try db.create(table: "place") { t in
t.autoIncrementedPrimaryKey("id")
t.column("title", .text).notNull()
t.column("isFavorite", .boolean).notNull().defaults(to: false)
t.column("longitude", .double).notNull()
t.column("latitude", .double).notNull()
}
}
Each one of the three examples below is correct. You will pick one or the other depending on your personal preferences and the requirements of your application:
Define a Codable struct, and adopt the record protocols you need
This is the shortest way to define a record type.
See the Record Protocols Overview, and Codable Records for more information.
struct Place: Codable {
var id: Int64?
var title: String
var isFavorite: Bool
private var latitude: CLLocationDegrees
private var longitude: CLLocationDegrees
var coordinate: CLLocationCoordinate2D {
get {
return CLLocationCoordinate2D(
latitude: latitude,
longitude: longitude)
}
set {
latitude = newValue.latitude
longitude = newValue.longitude
}
}
}
// SQL generation
extension Place: TableRecord {
/// The table columns
enum Columns {
static let id = Column(CodingKeys.id)
static let title = Column(CodingKeys.title)
static let isFavorite = Column(CodingKeys.isFavorite)
static let latitude = Column(CodingKeys.latitude)
static let longitude = Column(CodingKeys.longitude)
}
}
// Fetching methods
extension Place: FetchableRecord { }
// Persistence methods
extension Place: MutablePersistableRecord {
// Update auto-incremented id upon successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
Define a plain struct, and adopt the record protocols you need
See the Record Protocols Overview for more information.
struct Place {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D
}
// SQL generation
extension Place: TableRecord {
/// The table columns
enum Columns: String, ColumnExpression {
case id, title, isFavorite, latitude, longitude
}
}
// Fetching methods
extension Place: FetchableRecord {
/// Creates a record from a database row
init(row: Row) {
id = row[Columns.id]
title = row[Columns.title]
isFavorite = row[Columns.isFavorite]
coordinate = CLLocationCoordinate2D(
latitude: row[Columns.latitude],
longitude: row[Columns.longitude])
}
}
// Persistence methods
extension Place: MutablePersistableRecord {
/// The values persisted in the database
func encode(to container: inout PersistenceContainer) {
container[Columns.id] = id
container[Columns.title] = title
container[Columns.isFavorite] = isFavorite
container[Columns.latitude] = coordinate.latitude
container[Columns.longitude] = coordinate.longitude
}
// Update auto-incremented id upon successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
Define a plain struct optimized for fetching performance
This struct derives is persistence methpds from the standard Encodable protocol (see Codable Records), but performs optimized row decoding by accessing database columns with numeric indexes.
See the Record Protocols Overview for more information.
struct Place: Encodable {
var id: Int64?
var title: String
var isFavorite: Bool
private var latitude: CLLocationDegrees
private var longitude: CLLocationDegrees
var coordinate: CLLocationCoordinate2D {
get {
return CLLocationCoordinate2D(
latitude: latitude,
longitude: longitude)
}
set {
latitude = newValue.latitude
longitude = newValue.longitude
}
}
}
// SQL generation
extension Place: TableRecord {
/// The table columns
enum Columns {
static let id = Column(CodingKeys.id)
static let title = Column(CodingKeys.title)
static let isFavorite = Column(CodingKeys.isFavorite)
static let latitude = Column(CodingKeys.latitude)
static let longitude = Column(CodingKeys.longitude)
}
/// Arrange the selected columns and lock their order
static let databaseSelection: [SQLSelectable] = [
Columns.id,
Columns.title,
Columns.favorite,
Columns.latitude,
Columns.longitude]
}
// Fetching methods
extension Place: FetchableRecord {
/// Creates a record from a database row
init(row: Row) {
// For high performance, use numeric indexes that match the
// order of Place.databaseSelection
id = row[0]
title = row[1]
isFavorite = row[2]
coordinate = CLLocationCoordinate2D(
latitude: row[3],
longitude: row[4])
}
}
// Persistence methods
extension Place: MutablePersistableRecord {
// Update auto-incremented id upon successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
Subclass the Record
class
See the Record class for more information.
class Place: Record {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D
init(id: Int64?, title: String, isFavorite: Bool, coordinate: CLLocationCoordinate2D) {
self.id = id
self.title = title
self.isFavorite = isFavorite
self.coordinate = coordinate
super.init()
}
/// The table name
override class var databaseTableName: String {
return "place"
}
/// The table columns
enum Columns: String, ColumnExpression {
case id, title, isFavorite, latitude, longitude
}
/// Creates a record from a database row
required init(row: Row) {
id = row[Columns.id]
title = row[Columns.title]
isFavorite = row[Columns.isFavorite]
coordinate = CLLocationCoordinate2D(
latitude: row[Columns.latitude],
longitude: row[Columns.longitude])
super.init(row: row)
}
/// The values persisted in the database
override func encode(to container: inout PersistenceContainer) {
container[Columns.id] = id
container[Columns.title] = title
container[Columns.isFavorite] = isFavorite
container[Columns.latitude] = coordinate.latitude
container[Columns.longitude] = coordinate.longitude
}
// Update auto-incremented id upon successful insertion
override func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
This is the list of record methods, along with their required protocols. The Record class adopts all these protocols, and adds a few extra methods.
Method | Protocols | Notes |
---|---|---|
Core Methods | ||
init(row:) |
FetchableRecord | |
Type.databaseTableName |
TableRecord | |
Type.databaseSelection |
TableRecord | * |
Type.persistenceConflictPolicy |
PersistableRecord | * |
record.encode(to:) |
EncodableRecord | |
record.didInsert(with:for:) |
PersistableRecord | |
Insert and Update Records | ||
record.insert(db) |
PersistableRecord | |
record.save(db) |
PersistableRecord | |
record.update(db) |
PersistableRecord | |
record.update(db, columns:...) |
PersistableRecord | |
record.updateChanges(db, from:...) |
PersistableRecord | * |
record.updateChanges(db) { ... } |
PersistableRecord | * |
record.updateChanges(db) |
Record | * |
Delete Records | ||
record.delete(db) |
PersistableRecord | |
Type.deleteOne(db, key:...) |
PersistableRecord | ¹ |
Type.deleteAll(db) |
PersistableRecord | |
Type.deleteAll(db, keys:...) |
PersistableRecord | ¹ |
Type.filter(...).deleteAll(db) |
PersistableRecord | ² |
Check Record Existence | ||
record.exists(db) |
PersistableRecord | |
Convert Record to Dictionary | ||
record.databaseDictionary |
EncodableRecord | |
Count Records | ||
Type.fetchCount(db) |
TableRecord | |
Type.filter(...).fetchCount(db) |
TableRecord | ² |
Fetch Record Cursors | ||
Type.fetchCursor(db) |
FetchableRecord & TableRecord | |
Type.fetchCursor(db, keys:...) |
FetchableRecord & TableRecord | ¹ |
Type.fetchCursor(db, sql: sql) |
FetchableRecord | ³ |
Type.fetchCursor(statement) |
FetchableRecord | ⁴ |
Type.filter(...).fetchCursor(db) |
FetchableRecord & TableRecord | ² |
Fetch Record Arrays | ||
Type.fetchAll(db) |
FetchableRecord & TableRecord | |
Type.fetchAll(db, keys:...) |
FetchableRecord & TableRecord | ¹ |
Type.fetchAll(db, sql: sql) |
FetchableRecord | ³ |
Type.fetchAll(statement) |
FetchableRecord | ⁴ |
Type.filter(...).fetchAll(db) |
FetchableRecord & TableRecord | ² |
Fetch Individual Records | ||
Type.fetchOne(db) |
FetchableRecord & TableRecord | |
Type.fetchOne(db, key:...) |
FetchableRecord & TableRecord | ¹ |
Type.fetchOne(db, sql: sql) |
FetchableRecord | ³ |
Type.fetchOne(statement) |
FetchableRecord | ⁴ |
Type.filter(...).fetchOne(db) |
FetchableRecord & TableRecord | ² |
Codable Records | ||
Type.databaseDecodingUserInfo |
FetchableRecord | * |
Type.databaseJSONDecoder(for:) |
FetchableRecord | * |
Type.databaseDateDecodingStrategy |
FetchableRecord | * |
Type.databaseEncodingUserInfo |
EncodableRecord | * |
Type.databaseJSONEncoder(for:) |
EncodableRecord | * |
Type.databaseDateEncodingStrategy |
EncodableRecord | * |
Type.databaseUUIDEncodingStrategy |
EncodableRecord | * |
Define Associations | ||
Type.belongsTo(...) |
TableRecord | * |
Type.hasMany(...) |
TableRecord | * |
Type.hasOne(...) |
TableRecord | * |
Type.hasManyThrough(...) |
TableRecord | * |
Type.hasOneThrough(...) |
TableRecord | * |
Building Query Interface Requests | ||
record.request(for:...) |
TableRecord & EncodableRecord | * |
Type.all() |
TableRecord | ² |
Type.none() |
TableRecord | ² |
Type.select(...) |
TableRecord | ² |
Type.select(..., as:...) |
TableRecord | ² |
Type.annotated(with:...) |
TableRecord | ² |
Type.filter(...) |
TableRecord | ² |
Type.matching(...) |
TableRecord | ² |
Type.including(all:) |
TableRecord | ² |
Type.including(optional:) |
TableRecord | ² |
Type.including(required:) |
TableRecord | ² |
Type.joining(optional:) |
TableRecord | ² |
Type.joining(required:) |
TableRecord | ² |
Type.order(...) |
TableRecord | ² |
Type.orderByPrimaryKey() |
TableRecord | ² |
Type.having(...) |
TableRecord | ² |
Type.limit(...) |
TableRecord | ² |
Record Comparison | ||
record.databaseEquals(...) |
EncodableRecord | |
record.databaseChanges(from:...) |
EncodableRecord | |
record.updateChanges(db, from:...) |
PersistableRecord | |
record.updateChanges(db) { ... } |
PersistableRecord | |
record.hasDatabaseChanges |
Record | |
record.databaseChanges |
Record | |
record.updateChanges(db) |
Record |
¹ All unique keys are supported: primary keys (single-column, composite, implicit RowID) and unique indexes:
try Player.fetchOne(db, key: 1) // Player?
try Player.fetchOne(db, key: ["email": "arthur@example.com"]) // Player?
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]
² See Fetch Requests:
let request = Player.filter(emailColumn != nil).order(nameColumn)
let players = try request.fetchAll(db) // [Player]
let count = try request.fetchCount(db) // Int
³ See SQL queries:
let player = try Player.fetchOne(db, sql: "SELECT * FROM player WHERE id = ?", arguments: [1]) // Player?
⁴ See Prepared Statements:
let statement = try db.makeSelectStatement(sql: "SELECT * FROM player WHERE id = ?")
let player = try Player.fetchOne(statement, arguments: [1]) // Player?
The query interface lets you write pure Swift instead of SQL:
try dbQueue.write { db in
// Update database schema
try db.create(table: "wine") { t in ... }
// Fetch records
let wines = try Wine.filter(origin == "Burgundy").order(price).fetchAll(db)
// Count
let count = try Wine.filter(color == Color.red).fetchCount(db)
// Delete
try Wine.filter(corked == true).deleteAll(db)
}
You need to open a database connection before you can query the database.
Please bear in mind that the query interface can not generate all possible SQL queries. You may also prefer writing SQL, and this is just OK. From little snippets to full queries, your SQL skills are welcome:
try dbQueue.write { db in
// Update database schema (with SQL)
try db.execute(sql: "CREATE TABLE wine (...)")
// Fetch records (with SQL)
let wines = try Wine.fetchAll(db,
sql: "SELECT * FROM wine WHERE origin = ? ORDER BY price",
arguments: ["Burgundy"])
// Count (with an SQL snippet)
let count = try Wine
.filter(sql: "color = ?", arguments: [Color.red])
.fetchCount(db)
// Delete (with SQL)
try db.execute(sql: "DELETE FROM wine WHERE corked")
}
So don't miss the SQL API.
☝️ Note: the generated SQL may change between GRDB releases, without notice: don't have your application rely on any specific SQL output.
- Database Schema
- Requests
- Expressions
- Fetching from Requests
- Fetching by Key
- Fetching Aggregated Values
- Delete Requests
- Custom Requests
- Associations and Joins
Once granted with a database connection, you can setup your database schema without writing SQL:
// CREATE TABLE place (
// id INTEGER PRIMARY KEY AUTOINCREMENT,
// title TEXT,
// favorite BOOLEAN NOT NULL DEFAULT 0,
// latitude DOUBLE NOT NULL,
// longitude DOUBLE NOT NULL
// )
try db.create(table: "place") { t in
t.autoIncrementedPrimaryKey("id")
t.column("title", .text)
t.column("favorite", .boolean).notNull().defaults(to: false)
t.column("longitude", .double).notNull()
t.column("latitude", .double).notNull()
}
The create(table:)
method covers nearly all SQLite table creation features. For virtual tables, see Full-Text Search, or use raw SQL.
SQLite itself has many reference documents about table creation: CREATE TABLE, Datatypes In SQLite Version 3, SQLite Foreign Key Support, ON CONFLICT, The WITHOUT ROWID Optimization.
Configure table creation:
// CREATE TABLE example ( ... )
try db.create(table: "example") { t in ... }
// CREATE TEMPORARY TABLE example IF NOT EXISTS (
try db.create(table: "example", temporary: true, ifNotExists: true) { t in ... }
💡 Tip: database table names should be singular, and camel-cased. Make them look like Swift identifiers:
place
,country
,postalAddress
, 'httpRequest'.This will help you using Associations when you need them. Database table names that follow another naming convention are totally OK, but you will need to perform extra configuration.
Add regular columns with their name and eventual type (text, integer, double, numeric, boolean, blob, date and datetime) - see SQLite data types:
// CREATE TABLE example (
// a,
// name TEXT,
// creationDate DATETIME,
try db.create(table: "example") { t in
t.column("a")
t.column("name", .text)
t.column("creationDate", .datetime)
Define not null columns, and set default values:
// email TEXT NOT NULL,
t.column("email", .text).notNull()
// name TEXT NOT NULL DEFAULT 'Anonymous',
t.column("name", .text).notNull().defaults(to: "Anonymous")
Use an individual column as primary, unique, or foreign key. When defining a foreign key, the referenced column is the primary key of the referenced table (unless you specify otherwise):
// id INTEGER PRIMARY KEY AUTOINCREMENT,
t.autoIncrementedPrimaryKey("id")
// uuid TEXT PRIMARY KEY,
t.column("uuid", .text).primaryKey()
// email TEXT UNIQUE,
t.column("email", .text).unique()
// countryCode TEXT REFERENCES country(code) ON DELETE CASCADE,
t.column("countryCode", .text).references("country", onDelete: .cascade)
💡 Tip: when you need an integer primary key that automatically generates unique values, it is highly recommended that you use the
autoIncrementedPrimaryKey
method:try db.create(table: "example") { t in t.autoIncrementedPrimaryKey("id") ... }The reason for this recommendation is that auto-incremented primary keys prevent the reuse of ids. This prevents your app or database observation tools to think that a row was updated, when it was actually deleted, then replaced. Depending on your application needs, this may be acceptable. But usually it is not.
Create an index on the column:
t.column("score", .integer).indexed()
For extra index options, see Create Indexes below.
Perform integrity checks on individual columns, and SQLite will only let conforming rows in. In the example below, the $0
closure variable is a column which lets you build any SQL expression.
// name TEXT CHECK (LENGTH(name) > 0)
// score INTEGER CHECK (score > 0)
t.column("name", .text).check { length($0) > 0 }
t.column("score", .integer).check(sql: "score > 0")
Other table constraints can involve several columns:
// PRIMARY KEY (a, b),
t.primaryKey(["a", "b"])
// UNIQUE (a, b) ON CONFLICT REPLACE,
t.uniqueKey(["a", "b"], onConfict: .replace)
// FOREIGN KEY (a, b) REFERENCES parents(c, d),
t.foreignKey(["a", "b"], references: "parents")
// CHECK (a + b < 10),
t.check(Column("a") + Column("b") < 10)
// CHECK (a + b < 10)
t.check(sql: "a + b < 10")
}
SQLite lets you rename tables, and add columns to existing tables:
// ALTER TABLE referer RENAME TO referrer
try db.rename(table: "referer", to: "referrer")
// ALTER TABLE player ADD COLUMN url TEXT
try db.alter(table: "player") { t in
t.add(column: "url", .text)
}
☝️ Note: SQLite restricts the possible table alterations, and may require you to recreate dependent triggers or views. See the documentation of the ALTER TABLE for details. See Advanced Database Schema Changes for a way to lift restrictions.
Drop tables with the drop(table:)
method:
try db.drop(table: "obsolete")
Create indexes with the create(index:)
method:
// CREATE UNIQUE INDEX byEmail ON users(email)
try db.create(index: "byEmail", on: "users", columns: ["email"], unique: true)
Relevant SQLite documentation:
The query interface requests let you fetch values from the database:
let request = Player.filter(emailColumn != nil).order(nameColumn)
let players = try request.fetchAll(db) // [Player]
let count = try request.fetchCount(db) // Int
All requests start from a type that adopts the TableRecord
protocol, such as a Record
subclass (see Records):
class Player : Record { ... }
Declare the table columns that you want to use for filtering, or sorting:
let idColumn = Column("id")
let nameColumn = Column("name")
You can also declare column enums, if you prefer:
// Columns.id and Columns.name can be used just as
// idColumn and nameColumn declared above.
enum Columns: String, ColumnExpression {
case id
case name
}
You can now build requests with the following methods: all
, none
, select
, distinct
, filter
, matching
, group
, having
, order
, reversed
, limit
, joining
, including
. All those methods return another request, which you can further refine by applying another method: Player.select(...).filter(...).order(...)
.
-
all()
,none()
: the requests for all rows, or no row.// SELECT * FROM player Player.all()
The hidden
rowid
column can be selected as well when you need it. -
select(...)
andselect(..., as:)
define the selected columns. See Columns Selected by a Request.// SELECT name FROM player Player.select(nameColumn, as: String.self)
-
annotated(with: ...)
extends the selection with association aggregates.// SELECT team.*, COUNT(DISTINCT player.rowid) AS playerCount // FROM team // LEFT JOIN player ON player.teamId = team.id // GROUP BY team.id Team.annotated(with: Team.players.count)
-
distinct()
performs uniquing.// SELECT DISTINCT name FROM player Player.select(nameColumn, as: String.self).distinct()
-
filter(expression)
applies conditions.// SELECT * FROM player WHERE id IN (1, 2, 3) Player.filter([1,2,3].contains(idColumn)) // SELECT * FROM player WHERE (name IS NOT NULL) AND (height > 1.75) Player.filter(nameColumn != nil && heightColumn > 1.75)
-
filter(key:)
andfilter(keys:)
apply conditions on primary keys and unique keys:// SELECT * FROM player WHERE id = 1 Player.filter(key: 1) // SELECT * FROM country WHERE isoCode IN ('FR', 'US') Country.filter(keys: ["FR", "US"]) // SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR' Citizenship.filter(key: ["citizenId": 1, "countryCode": "FR"]) // SELECT * FROM player WHERE email = 'arthur@example.com' Player.filter(key: ["email": "arthur@example.com"])
-
matching(pattern)
performs full-text search.// SELECT * FROM document WHERE document MATCH 'sqlite database' let pattern = FTS3Pattern(matchingAllTokensIn: "SQLite database") Document.matching(pattern)
When the pattern is nil, no row will match.
-
group(expression, ...)
groups rows.// SELECT name, MAX(score) FROM player GROUP BY name Player .select(nameColumn, max(scoreColumn)) .group(nameColumn)
-
having(expression)
applies conditions on grouped rows.// SELECT team, MAX(score) FROM player GROUP BY team HAVING MIN(score) >= 1000 Player .select(teamColumn, max(scoreColumn)) .group(teamColumn) .having(min(scoreColumn) >= 1000)
-
having(aggregate)
applies conditions on grouped rows, according to an association aggregate.// SELECT team.* // FROM team // LEFT JOIN player ON player.teamId = team.id // GROUP BY team.id // HAVING COUNT(DISTINCT player.rowid) >= 5 Team.having(Team.players.count >= 5)
-
order(ordering, ...)
sorts.// SELECT * FROM player ORDER BY name Player.order(nameColumn) // SELECT * FROM player ORDER BY score DESC, name Player.order(scoreColumn.desc, nameColumn)
Each
order
call clears any previous ordering:// SELECT * FROM player ORDER BY name Player.order(scoreColumn).order(nameColumn)
-
orderByPrimaryKey()
sorts by primary key:// SELECT * FROM player ORDER BY id Player.orderByPrimaryKey() // SELECT * FROM country ORDER BY code Country.orderByPrimaryKey() // SELECT * FROM citizenship ORDER BY citizenId, countryCode Citizenship.orderByPrimaryKey()
-
reversed()
reverses the eventual orderings.// SELECT * FROM player ORDER BY score ASC, name DESC Player.order(scoreColumn.desc, nameColumn).reversed()
If no ordering was already specified, this method has no effect:
// SELECT * FROM player Player.all().reversed()
-
limit(limit, offset: offset)
limits and pages results.// SELECT * FROM player LIMIT 5 Player.limit(5) // SELECT * FROM player LIMIT 5 OFFSET 10 Player.limit(5, offset: 10)
-
joining(...)
andincluding(...)
fetch and join records through Associations.// SELECT player.*, team.* // FROM player // JOIN team ON team.id = player.teamId Player.including(required: Player.team)
You can refine requests by chaining those methods:
// SELECT * FROM player WHERE (email IS NOT NULL) ORDER BY name
Player.order(nameColumn).filter(emailColumn != nil)
The select
, order
, group
, and limit
methods ignore and replace previously applied selection, orderings, grouping, and limits. On the opposite, filter
, matching
, and having
methods extend the query:
Player // SELECT * FROM player
.filter(nameColumn != nil) // WHERE (name IS NOT NULL)
.filter(emailColumn != nil) // AND (email IS NOT NULL)
.order(nameColumn) // - ignored -
.reversed() // - ignored -
.order(scoreColumn) // ORDER BY score
.limit(20, offset: 40) // - ignored -
.limit(10) // LIMIT 10
Raw SQL snippets are also accepted, with eventual arguments:
// SELECT DATE(creationDate), COUNT(*) FROM player WHERE name = 'Arthur' GROUP BY date(creationDate)
Player
.select(sql: "DATE(creationDate), COUNT(*)")
.filter(sql: "name = ?", arguments: ["Arthur"])
.group(sql: "DATE(creationDate)")
By default, query interface requests select all columns:
// SELECT * FROM player
let request = Player.all()
The selection can be changed for each individual requests, or for all requests built from a given type.
The select(...)
and select(..., as:)
methods change the selection of a single request (see Fetching from Requests for detailed information):
let request = Player.select(max(Column("score")))
let maxScore: Int? = try Int.fetchOne(db, request)
The default selection for a record type is controlled by the databaseSelection
property:
struct RestrictedPlayer : TableRecord {
static let databaseTableName = "player"
static let databaseSelection: [SQLSelectable] = [Column("id"), Column("name")]
}
struct ExtendedPlayer : TableRecord {
static let databaseTableName = "player"
static let databaseSelection: [SQLSelectable] = [AllColumns(), Column.rowID]
}
// SELECT id, name FROM player
let request = RestrictedPlayer.all()
// SELECT *, rowid FROM player
let request = ExtendedPlayer.all()
☝️ Note: make sure the
databaseSelection
property is explicitly declared as[SQLSelectable]
. If it is not, the Swift compiler may silently miss the protocol requirement, resulting in stickySELECT *
requests. To verify your setup, see the How do I print a request as SQL? FAQ.
Feed requests with SQL expressions built from your Swift code:
-
=
,<>
,<
,<=
,>
,>=
,IS
,IS NOT
Comparison operators are based on the Swift operators
==
,!=
,===
,!==
,<
,<=
,>
,>=
:// SELECT * FROM player WHERE (name = 'Arthur') Player.filter(nameColumn == "Arthur") // SELECT * FROM player WHERE (name IS NULL) Player.filter(nameColumn == nil) // SELECT * FROM player WHERE (score IS 1000) Player.filter(scoreColumn === 1000) // SELECT * FROM rectangle WHERE width < height Rectangle.filter(widthColumn < heightColumn)
☝️ Note: SQLite string comparison, by default, is case-sensitive and not Unicode-aware. See string comparison if you need more control.
-
*
,/
,+
,-
SQLite arithmetic operators are derived from their Swift equivalent:
// SELECT ((temperature * 1.8) + 32) AS farenheit FROM planet Planet.select((temperatureColumn * 1.8 + 32).forKey("farenheit"))
☝️ Note: an expression like
nameColumn + "rrr"
will be interpreted by SQLite as a numerical addition (with funny results), not as a string concatenation. -
AND
,OR
,NOT
The SQL logical operators are derived from the Swift
&&
,||
and!
:// SELECT * FROM player WHERE ((NOT verified) OR (score < 1000)) Player.filter(!verifiedColumn || scoreColumn < 1000)
When you want to join a sequence of expressions with
AND
orOR
operators, usejoined(operator:)
:// SELECT * FROM player WHERE (verified AND (score >= 1000) AND (name IS NOT NULL)) let conditions = [ verifiedColumn, scoreColumn >= 1000, nameColumn != nil] Player.filter(conditions.joined(operator: .and))
When the sequence is empty,
joined(operator: .and)
returns true, andjoined(operator: .or)
returns false:// SELECT * FROM player WHERE 1 Player.filter([].joined(operator: .and)) // SELECT * FROM player WHERE 0 Player.filter([].joined(operator: .or))
-
BETWEEN
,IN
,NOT IN
To check inclusion in a Swift sequence (array, set, range…), call the
contains
method:// SELECT * FROM player WHERE id IN (1, 2, 3) Player.filter([1, 2, 3].contains(idColumn)) // SELECT * FROM player WHERE id NOT IN (1, 2, 3) Player.filter(![1, 2, 3].contains(idColumn)) // SELECT * FROM player WHERE score BETWEEN 0 AND 1000 Player.filter((0...1000).contains(scoreColumn)) // SELECT * FROM player WHERE (score >= 0) AND (score < 1000) Player.filter((0..<1000).contains(scoreColumn)) // SELECT * FROM player WHERE initial BETWEEN 'A' AND 'N' Player.filter(("A"..."N").contains(initialColumn)) // SELECT * FROM player WHERE (initial >= 'A') AND (initial < 'N') Player.filter(("A"..<"N").contains(initialColumn))
☝️ Note: SQLite string comparison, by default, is case-sensitive and not Unicode-aware. See string comparison if you need more control.
-
LIKE
The SQLite LIKE operator is available as the
like
method:// SELECT * FROM player WHERE (email LIKE '%@example.com') Player.filter(emailColumn.like("%@example.com"))
☝️ Note: the SQLite LIKE operator is case-insensitive but not Unicode-aware. For example, the expression
'a' LIKE 'A'
is true but'æ' LIKE 'Æ'
is false. -
MATCH
The full-text MATCH operator is available through FTS3Pattern (for FTS3 and FTS4 tables) and FTS5Pattern (for FTS5):
FTS3 and FTS4:
let pattern = FTS3Pattern(matchingAllTokensIn: "SQLite database") // SELECT * FROM document WHERE document MATCH 'sqlite database' Document.matching(pattern) // SELECT * FROM document WHERE content MATCH 'sqlite database' Document.filter(contentColumn.match(pattern))
FTS5:
let pattern = FTS5Pattern(matchingAllTokensIn: "SQLite database") // SELECT * FROM document WHERE document MATCH 'sqlite database' Document.matching(pattern)
-
ABS
,AVG
,COUNT
,LENGTH
,MAX
,MIN
,SUM
:Those are based on the
abs
,average
,count
,length
,max
,min
andsum
Swift functions:// SELECT MIN(score), MAX(score) FROM player Player.select(min(scoreColumn), max(scoreColumn)) // SELECT COUNT(name) FROM player Player.select(count(nameColumn)) // SELECT COUNT(DISTINCT name) FROM player Player.select(count(distinct: nameColumn))
-
IFNULL
Use the Swift
??
operator:// SELECT IFNULL(name, 'Anonymous') FROM player Player.select(nameColumn ?? "Anonymous") // SELECT IFNULL(name, email) FROM player Player.select(nameColumn ?? emailColumn)
-
LOWER
,UPPER
The query interface does not give access to those SQLite functions. Nothing against them, but they are not unicode aware.
Instead, GRDB extends SQLite with SQL functions that call the Swift built-in string functions
capitalized
,lowercased
,uppercased
,localizedCapitalized
,localizedLowercased
andlocalizedUppercased
:Player.select(nameColumn.uppercased())
☝️ Note: When comparing strings, you'd rather use a collation:
let name: String = ... // Not recommended nameColumn.uppercased() == name.uppercased() // Better nameColumn.collating(.caseInsensitiveCompare) == name
-
Custom SQL functions and aggregates
You can apply your own custom SQL functions and aggregates:
let f = DatabaseFunction("f", ...) // SELECT f(name) FROM player Player.select(f.apply(nameColumn))
Once you have a request, you can fetch the records at the origin of the request:
// Some request based on `Player`
let request = Player.filter(...)... // QueryInterfaceRequest<Player>
// Fetch players:
try request.fetchCursor(db) // A Cursor of Player
try request.fetchAll(db) // [Player]
try request.fetchOne(db) // Player?
For example:
let allPlayers = try Player.fetchAll(db) // [Player]
let arthur = try Player.filter(nameColumn == "Arthur").fetchOne(db) // Player?
See fetching methods for information about the fetchCursor
, fetchAll
and fetchOne
methods.
You sometimes want to fetch other values.
The simplest way is to use the request as an argument to a fetching method of the desired type:
// Fetch an Int
let request = Player.select(max(scoreColumn))
let maxScore = try Int.fetchOne(db, request) // Int?
// Fetch a Row
let request = Player.select(min(scoreColumn), max(scoreColumn))
let row = try Row.fetchOne(db, request)! // Row
let minScore = row[0] as Int?
let maxScore = row[1] as Int?
You can also change the request so that it knows the type it has to fetch:
-
With
asRequest(of:)
, useful when you use Associations:struct BookInfo: FetchableRecord, Decodable { var book: Book var author: Author } // A request of BookInfo let request = Book .including(required: Book.author) .asRequest(of: BookInfo.self) let bookInfos = try dbQueue.read { db in try request.fetchAll(db) // [BookInfo] }
-
With
select(..., as:)
, which is handy when you change the selection:// A request of Int let request = Player.select(max(scoreColumn), as: Int.self) let maxScore = try dbQueue.read { db in try request.fetchOne(db) // Int? }
Fetching records according to their primary key is a very common task. It has a shortcut which accepts any single-column primary key:
// SELECT * FROM player WHERE id = 1
try Player.fetchOne(db, key: 1) // Player?
// SELECT * FROM player WHERE id IN (1, 2, 3)
try Player.fetchAll(db, keys: [1, 2, 3]) // [Player]
// SELECT * FROM country WHERE isoCode = 'FR'
try Country.fetchOne(db, key: "FR") // Country?
// SELECT * FROM country WHERE isoCode IN ('FR', 'US')
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]
When the table has no explicit primary key, GRDB uses the hidden "rowid" column:
// SELECT * FROM document WHERE rowid = 1
try Document.fetchOne(db, key: 1) // Document?
For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:
// SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
try Citizenship.fetchOne(db, key: ["citizenId": 1, "countryCode": "FR"]) // Citizenship?
// SELECT * FROM player WHERE email = 'arthur@example.com'
try Player.fetchOne(db, key: ["email": "arthur@example.com"]) // Player?
When you want to build a request and plan to fetch from it later, use the filter(key:)
and filter(keys:)
methods:
// SELECT * FROM player WHERE id = 1
let request = Player.filter(key: 1)
let player = try request.fetchOne(db) // Player?
// SELECT * FROM player WHERE id IN (1, 2, 3)
let request = Player.filter(keys: [1, 2, 3])
let players = try request.fetchAll(db) // [Player]
// SELECT * FROM country WHERE isoCode = 'FR'
let request = Country.filter(key: "FR")
let country = try request.fetchOne(db) // Country?
// SELECT * FROM country WHERE isoCode IN ('FR', 'US')
let request = Country.filter(keys: ["FR", "US"])
let countries = try request.fetchAll(db) // [Country]
// SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
let request = Citizenship.filter(key: ["citizenId": 1, "countryCode": "FR"])
let citizenship = request.fetchOne(db) // Citizenship?
// SELECT * FROM player WHERE email = 'arthur@example.com'
let request = Player.filter(key: ["email": "arthur@example.com"])
let player = try request.fetchOne(db) // Player?
Requests can count. The fetchCount()
method returns the number of rows that would be returned by a fetch request:
// SELECT COUNT(*) FROM player
let count = try Player.fetchCount(db) // Int
// SELECT COUNT(*) FROM player WHERE email IS NOT NULL
let count = try Player.filter(emailColumn != nil).fetchCount(db)
// SELECT COUNT(DISTINCT name) FROM player
let count = try Player.select(nameColumn).distinct().fetchCount(db)
// SELECT COUNT(*) FROM (SELECT DISTINCT name, score FROM player)
let count = try Player.select(nameColumn, scoreColumn).distinct().fetchCount(db)
Other aggregated values can also be selected and fetched (see SQL Functions):
let request = Player.select(max(scoreColumn))
let maxScore = try Int.fetchOne(db, request) // Int?
let request = Player.select(min(scoreColumn), max(scoreColumn))
let row = try Row.fetchOne(db, request)! // Row
let minScore = row[0] as Int?
let maxScore = row[1] as Int?
Requests can delete records, with the deleteAll()
method:
// DELETE FROM player WHERE email IS NULL
let request = Player.filter(emailColumn == nil)
try request.deleteAll(db)
☝️ Note Deletion methods are only available for records that adopts the PersistableRecord protocol.
Deleting records according to their primary key is also quite common. It has a shortcut which accepts any single-column primary key:
// DELETE FROM player WHERE id = 1
try Player.deleteOne(db, key: 1)
// DELETE FROM player WHERE id IN (1, 2, 3)
try Player.deleteAll(db, keys: [1, 2, 3])
// DELETE FROM country WHERE isoCode = 'FR'
try Country.deleteOne(db, key: "FR")
// DELETE FROM country WHERE isoCode IN ('FR', 'US')
try Country.deleteAll(db, keys: ["FR", "US"])
When the table has no explicit primary key, GRDB uses the hidden "rowid" column:
// DELETE FROM document WHERE rowid = 1
try Document.deleteOne(db, key: 1)
For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:
// DELETE FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
try Citizenship.deleteOne(db, key: ["citizenId": 1, "countryCode": "FR"])
// DELETE FROM player WHERE email = 'arthur@example.com'
Player.deleteOne(db, key: ["email": "arthur@example.com"])
Until now, we have seen requests created from any type that adopts the TableRecord protocol:
let request = Player.all() // QueryInterfaceRequest<Player>
Those requests of type QueryInterfaceRequest
can fetch and count:
try request.fetchCursor(db) // A Cursor of Player
try request.fetchAll(db) // [Player]
try request.fetchOne(db) // Player?
try request.fetchCount(db) // Int
When the query interface can not generate the SQL you need, you can still fallback to raw SQL:
// Custom SQL is always welcome
try Player.fetchAll(db, sql: "SELECT ...") // [Player]
But you may prefer to bring some elegance back in, and build custom requests:
// No custom SQL in sight
try Player.customRequest().fetchAll(db) // [Player]
FetchRequest is the protocol for all requests that run from a single select statement, and know how fetched rows should be interpreted:
protocol FetchRequest: DatabaseRegionConvertible {
/// The type that tells how fetched rows should be decoded
associatedtype RowDecoder
/// Returns a PreparedRequest made of a prepared statement that is ready to
/// be executed, and an eventual row adapter.
func makePreparedRequest(_ db: Database, forSingleResult singleResult: Bool) throws -> PreparedRequest
/// The number of rows fetched by the request.
func fetchCount(_ db: Database) throws -> Int
}
When the RowDecoder
associated type is Row, or a value, or a type that conforms to FetchableRecord, the request can fetch: see Fetching From Custom Requests below.
The makePreparedRequest(_:forSingleResult:)
method accepts a database connection, a singleResult
hint, and returns a "prepared request" made of a prepared statement and an optional row adapter. Conforming types can use the singleResult
hint as an optimization opportunity, and return a statement that fetches at most one row, with a LIMIT
SQL clause, when possible.
The fetchCount
method has a default implementation that builds a correct but naive SQL query from the statement returned by prepare
: SELECT COUNT(*) FROM (...)
. Adopting types can refine the counting SQL by customizing their fetchCount
implementation.
The base DatabaseRegionConvertible
protocol is involved in database observation. For more information, see DatabaseRegion, DatabaseRegionObservation, and ValueObservation.
The FetchRequest protocol is adopted, for example, by query interface requests:
// A FetchRequest whose RowDecoder associated type is Player:
let request = Player.all()
To build custom requests, you can use one of the built-in requests, derive requests from other requests, or create your own request type that adopts the FetchRequest protocol.
-
SQLRequest is a fetch request built from raw SQL. For example:
extension Player { static func filter(color: Color) -> SQLRequest<Player> { return SQLRequest<Player>( sql: "SELECT * FROM player WHERE color = ?" arguments: [color]) } } // [Player] try Player.filter(color: .red).fetchAll(db)
In Swift 5, you can build SQLRequest with SQL Interpolation:
// Swift 5 extension Player { static func filter(color: Color) -> SQLRequest<Player> { return "SELECT * FROM player WHERE color = \(color)" } }
-
The
asRequest(of:)
method changes the type fetched by the request. It is useful, for example, when you use Associations:struct BookInfo: FetchableRecord, Decodable { var book: Book var author: Author } let request = Book .including(required: Book.author) .asRequest(of: BookInfo.self) // [BookInfo] try request.fetchAll(db)
-
The
adapted(_:)
method eases the consumption of complex rows with row adapters. See Joined Queries Support for some sample code that uses this method. -
AnyFetchRequest: a type-erased request.
A type adopting FetchRequest knows exactly what it has to do when its RowDecoder associated type can decode database rows (Row itself, values, or FetchableRecord):
let rowRequest = ... // Some FetchRequest that fetches Row
try request.fetchCursor(db) // A cursor of rows
let playerRequest = ... // Some FetchRequest that fetches Player
try request.fetchAll(db) // [Player]
let intRequest = ... // Some FetchRequest that fetches Int
try request.fetchOne(db) // Int?
For example:
let playerRequest = SQLRequest<Player>(
sql: "SELECT * FROM player WHERE color = ?"
arguments: [color])
try request.fetchAll(db) // [Player]
See fetching methods for information about the fetchCursor
, fetchAll
and fetchOne
methods.
The RowDecoder type associated with the FetchRequest does not have to be Row, DatabaseValueConvertible, or FetchableRecord. See the Beyond FetchableRecord chapter for more information.
Migrations are a convenient way to alter your database schema over time in a consistent and easy way.
Migrations run in order, once and only once. When a user upgrades your application, only non-applied migrations are run.
Inside each migration, you typically define and update your database tables according to your evolving application needs:
var migrator = DatabaseMigrator()
// 1st migration
migrator.registerMigration("v1") { db in
try db.create(table: "author") { t in ... }
try db.create(table: "book") { t in ... }
try db.create(index: ...)
}
// 2nd migration
migrator.registerMigration("v2") { db in
try db.alter(table: "author") { t in ... }
}
// Migrations for future versions will be inserted here:
//
// // 3rd migration
// migrator.registerMigration("...") { db in
// ...
// }
Each migration runs in a separate transaction. Should one throw an error, its transaction is rollbacked, subsequent migrations do not run, and the error is eventually thrown by migrator.migrate(dbQueue)
.
The memory of applied migrations is stored in the database itself (in a reserved table).
You migrate the database up to the latest version with the migrate(_:)
method:
try migrator.migrate(dbQueue) // or migrator.migrate(dbPool)
To migrate a database up to a specific version, use migrate(_:upTo:)
:
try migrator.migrate(dbQueue, upTo: "v2")
Migrations can only run forward:
try migrator.migrate(dbQueue, upTo: "v2")
try migrator.migrate(dbQueue, upTo: "v1")
// fatal error: database is already migrated beyond migration "v1"
Check if a migration has been applied:
let appliedMigrations = try migrator.appliedMigrations(in: dbQueue)
if appliedMigrations.contains("v2") {
// "v2" migration has been applied
}
A DatabaseMigrator can automatically wipe out the full database content, and recreate the whole database from scratch, if it detects that a migration has changed its definition:
var migrator = DatabaseMigrator()
migrator.eraseDatabaseOnSchemaChange = true
Beware! This flag can destroy your precious users' data!
Yet it may be useful in those two situations:
-
During application development, as you are still designing migrations, and the schema changes often.
In this case, it is recommended that this flag does not ship in the distributed application:
var migrator = DatabaseMigrator() #if DEBUG // Speed up development by nuking the database when migrations change migrator.eraseDatabaseOnSchemaChange = true #endif
-
When the database content can easily be recreated, such as a cache for some downloaded data.
The eraseDatabaseOnSchemaChange
option triggers a recreation of the database if the migrator detects a schema change. A schema change is any difference in the sqlite_master
table, which contains the SQL used to create database tables, indexes, triggers, and views.
SQLite does not support many schema changes, and won't let you drop a table column with "ALTER TABLE ... DROP COLUMN ...", for example.
Yet any kind of schema change is still possible. The SQLite documentation explains in detail how to do so: https://www.sqlite.org/lang_altertable.html#otheralter. This technique requires the temporary disabling of foreign key checks, and is supported by the registerMigrationWithDeferredForeignKeyCheck
function:
// Add a NOT NULL constraint on player.name:
migrator.registerMigrationWithDeferredForeignKeyCheck("AddNotNullCheckOnName") { db in
try db.create(table: "new_player") { t in
t.autoIncrementedPrimaryKey("id")
t.column("name", .text).notNull()
}
try db.execute(sql: "INSERT INTO new_player SELECT * FROM player")
try db.drop(table: "player")
try db.rename(table: "new_player", to: "player")
}
While your migration code runs with disabled foreign key checks, those are re-enabled and checked at the end of the migration, regardless of eventual errors.
Full-Text Search is an efficient way to search a corpus of textual documents.
// Create full-text tables
try db.create(virtualTable: "book", using: FTS4()) { t in // or FTS3(), or FTS5()
t.column("author")
t.column("title")
t.column("body")
}
// Populate full-text table with records or SQL
try Book(...).insert(db)
try db.execute(
sql: "INSERT INTO book (author, title, body) VALUES (?, ?, ?)",
arguments: [...])
// Build search patterns
let pattern = FTS3Pattern(matchingPhrase: "Moby-Dick")
// Search with the query interface or SQL
let books = try Book.matching(pattern).fetchAll(db)
let books = try Book.fetchAll(db,
sql: "SELECT * FROM book WHERE book MATCH ?",
arguments: [pattern])
- Choosing the Full-Text Engine
- Enabling FTS5 Support
- Create Full-Text Virtual Tables: FTS3/4, FTS5
- Choosing a Tokenizer: FTS3/4, FTS5
- Search Patterns: FTS3/4, FTS5
- Sorting by Relevance: FTS5
- External Content Full-Text Tables: FTS4/5
- Full-Text Records: FTS3/4/5
- Unicode Full-Text Gotchas: FTS3/4/5. Unicorns don't exist.
- Custom Tokenizers: FTS5. Leverage extra full-text features such as synonyms or stop words. Avoid unicode gotchas.
- Sample Code: WWDC Companion, an iOS app that stores, displays, and lets the user search the WWDC 2016 sessions.
SQLite supports three full-text engines: FTS3, FTS4 and FTS5.
Generally speaking, FTS5 is better than FTS4 which improves on FTS3. But this does not really tell which engine to choose for your application. Instead, make your choice depend on:
-
The full-text features needed by the application:
Full-Text Needs FTS3 FTS4 FTS5 ❓ Queries Words searches (documents that contain "database") X X X Prefix searches (documents that contain a word starting with "data") X X X Phrases searches (documents that contain the phrase "SQLite database") X X X Boolean searches (documents that contain "SQLite" or "database") X X X Proximity search (documents that contain "SQLite" near "database") X X X ✂️ Tokenization Ascii case insensitivity (have "DATABASE" match "database") X X X Unicode case insensitivity (have "ÉLÉGANCE" match "élégance") X X X Latin diacritics insensitivity (have "elegance" match "élégance") X X X English Stemming (have "frustration" match "frustrated") X X X English Stemming and Ascii case insensitivity X X X English Stemming and Unicode case insensitivity X English Stemming and Latin diacritics insensitivity X Synonyms (have "1st" match "first") ¹ ¹ X ² Pinyin and Romaji (have "romaji" match "ローマ字") ¹ ¹ X ² Stop words (don't index, and don't match words like "and" and "the") ¹ ¹ X ² Spell checking (have "alamaba" match "alabama") ¹ ¹ ¹ Other Features
Ranking (sort results by relevance) ¹ ¹ X Snippets (display a few words around a match) X X X ¹ Requires extra setup, possibly hard to implement.
² Requires a custom tokenizer.
For a full feature list, read the SQLite documentation. Some missing features can be achieved with extra application code.
-
The speed versus disk space constraints. Roughly speaking, FTS4 and FTS5 are faster than FTS3, but use more space. FTS4 only supports content compression.
-
The location of the indexed text in your database schema. Only FTS4 and FTS5 support "contentless" and "external content" tables.
-
The SQLite library integrated in your application. The version of SQLite that ships with iOS, macOS, tvOS and watchOS supports FTS3 and FTS4 out of the box, but not always FTS5. To use FTS5, see Enabling FTS5 Support.
-
See FST3 vs. FTS4 and FTS5 vs. FTS3/4 for more differences.
☝️ Note: In case you were still wondering, it is recommended to read the SQLite documentation: FTS3 & FTS4 and FTS5.
FTS3 and FTS4 full-text tables store and index textual content.
Create tables with the create(virtualTable:using:)
method:
// CREATE VIRTUAL TABLE document USING fts3(content)
try db.create(virtualTable: "document", using: FTS3()) { t in
t.column("content")
}
// CREATE VIRTUAL TABLE document USING fts4(content)
try db.create(virtualTable: "document", using: FTS4()) { t in
t.column("content")
}
All columns in a full-text table contain text. If you need to index a table that contains other kinds of values, you need an "external content" full-text table.
You can specify a tokenizer:
// CREATE VIRTUAL TABLE book USING fts4(
// tokenize=porter,
// author,
// title,
// body
// )
try db.create(virtualTable: "book", using: FTS4()) { t in
t.tokenizer = .porter
t.column("author")
t.column("title")
t.column("body")
}
FTS4 supports options:
// CREATE VIRTUAL TABLE book USING fts4(
// content,
// uuid,
// content="",
// compress=zip,
// uncompress=unzip,
// prefix="2,4",
// notindexed=uuid,
// languageid=lid
// )
try db.create(virtualTable: "document", using: FTS4()) { t in
t.content = ""
t.compress = "zip"
t.uncompress = "unzip"
t.prefixes = [2, 4]
t.column("content")
t.column("uuid").notIndexed()
t.column("lid").asLanguageId()
}
The content
option is involved in "contentless" and "external content" full-text tables. GRDB can help you defining full-text tables that automatically synchronize with their content table. See External Content Full-Text Tables.
See SQLite documentation for more information.
A tokenizer defines what "matching" means. Depending on the tokenizer you choose, full-text searches won't return the same results.
SQLite ships with three built-in FTS3/4 tokenizers: simple
, porter
and unicode61
that use different algorithms to match queries with indexed content:
try db.create(virtualTable: "book", using: FTS4()) { t in
// Pick one:
t.tokenizer = .simple // default
t.tokenizer = .porter
t.tokenizer = .unicode61(...)
}
See below some examples of matches:
content | query | simple | porter | unicode61 |
---|---|---|---|---|
Foo | Foo | X | X | X |
Foo | FOO | X | X | X |
Jérôme | Jérôme | X ¹ | X ¹ | X ¹ |
Jérôme | JÉRÔME | X ¹ | ||
Jérôme | Jerome | X ¹ | ||
Database | Databases | X | ||
Frustration | Frustrated | X |
¹ Don't miss Unicode Full-Text Gotchas
-
simple
try db.create(virtualTable: "book", using: FTS4()) { t in t.tokenizer = .simple // default }
The default "simple" tokenizer is case-insensitive for ASCII characters. It matches "foo" with "FOO", but not "Jérôme" with "JÉRÔME".
It does not provide stemming, and won't match "databases" with "database".
It does not strip diacritics from latin script characters, and won't match "jérôme" with "jerome".
-
porter
try db.create(virtualTable: "book", using: FTS4()) { t in t.tokenizer = .porter }
The "porter" tokenizer compares English words according to their roots: it matches "database" with "databases", and "frustration" with "frustrated".
It does not strip diacritics from latin script characters, and won't match "jérôme" with "jerome".
-
unicode61
try db.create(virtualTable: "book", using: FTS4()) { t in t.tokenizer = .unicode61() t.tokenizer = .unicode61(diacritics: .keep) }
The "unicode61" tokenizer is case-insensitive for unicode characters. It matches "Jérôme" with "JÉRÔME".
It strips diacritics from latin script characters by default, and matches "jérôme" with "jerome". This behavior can be disabled, as in the example above.
It does not provide stemming, and won't match "databases" with "database".
See SQLite tokenizers for more information.
Full-text search in FTS3 and FTS4 tables is performed with search patterns:
database
matches all documents that contain "database"data*
matches all documents that contain a word starting with "data"SQLite database
matches all documents that contain both "SQLite" and "database"SQLite OR database
matches all documents that contain "SQLite" or "database""SQLite database"
matches all documents that contain the "SQLite database" phrase
Not all search patterns are valid: they must follow the Full-Text Index Queries Grammar.
The FTS3Pattern type helps you validating patterns, and building valid patterns from untrusted strings (such as strings typed by users):
struct FTS3Pattern {
init(rawPattern: String) throws
init?(matchingAnyTokenIn string: String)
init?(matchingAllTokensIn string: String)
init?(matchingPhrase string: String)
}
The first initializer validates your raw patterns against the query grammar, and may throw a DatabaseError:
// OK: FTS3Pattern
let pattern = try FTS3Pattern(rawPattern: "sqlite AND database")
// DatabaseError: malformed MATCH expression: [AND]
let pattern = try FTS3Pattern(rawPattern: "AND")
The three other initializers don't throw. They build a valid pattern from any string, including strings provided by users of your application. They let you find documents that match all given words, any given word, or a full phrase, depending on the needs of your application:
let query = "SQLite database"
// Matches documents that contain "SQLite" or "database"
let pattern = FTS3Pattern(matchingAnyTokenIn: query)
// Matches documents that contain both "SQLite" and "database"
let pattern = FTS3Pattern(matchingAllTokensIn: query)
// Matches documents that contain "SQLite database"
let pattern = FTS3Pattern(matchingPhrase: query)
They return nil when no pattern could be built from the input string:
let pattern = FTS3Pattern(matchingAnyTokenIn: "") // nil
let pattern = FTS3Pattern(matchingAnyTokenIn: "*") // nil
FTS3Pattern are regular values. You can use them as query arguments:
let documents = try Document.fetchAll(db,
sql: "SELECT * FROM document WHERE content MATCH ?",
arguments: [pattern])
Use them in the query interface:
// Search in all columns
let documents = try Document.matching(pattern).fetchAll(db)
// Search in a specific column:
let documents = try Document.filter(Column("content").match(pattern)).fetchAll(db)
When the FTS3 and FTS4 full-text engines don't suit your needs, you may want to use FTS5. See Choosing the Full-Text Engine to help you make a decision.
The version of SQLite that ships with iOS, macOS, tvOS and watchOS does not always support the FTS5 engine. To enable FTS5 support, you'll need to install GRDB with one of those installation techniques:
-
Use the GRDB.swift CocoaPod with a custom compilation option, as below. It uses the system SQLite, which is compiled with FTS5 support, but only on iOS 11.4+ / macOS 10.13+ / tvOS 11.4+ / watchOS 4.3+:
pod 'GRDB.swift' platform :ios, '11.4' # or above post_install do |installer| installer.pods_project.targets.select { |target| target.name == "GRDB.swift" }.each do |target| target.build_configurations.each do |config| config.build_settings['OTHER_SWIFT_FLAGS'] = "$(inherited) -D SQLITE_ENABLE_FTS5" end end end
⚠️ Warning: make sure you use the right platform version! You will get runtime errors on devices with a lower version.☝️ Note: there used to be a GRDBPlus CocoaPod with pre-enabled FTS5 support. This CocoaPod is deprecated: please switch to the above technique.
-
Use the GRDB.swift/SQLCipher CocoaPod subspec (see encryption):
pod 'GRDB.swift/SQLCipher'
-
Use a custom SQLite build and activate the
SQLITE_ENABLE_FTS5
compilation option.
FTS5 full-text tables store and index textual content.
To use FTS5, you'll need a custom SQLite build that activates the SQLITE_ENABLE_FTS5
compilation option.
Create FTS5 tables with the create(virtualTable:using:)
method:
// CREATE VIRTUAL TABLE document USING fts5(content)
try db.create(virtualTable: "document", using: FTS5()) { t in
t.column("content")
}
All columns in a full-text table contain text. If you need to index a table that contains other kinds of values, you need an "external content" full-text table.
You can specify a tokenizer:
// CREATE VIRTUAL TABLE book USING fts5(
// tokenize='porter',
// author,
// title,
// body
// )
try db.create(virtualTable: "book", using: FTS5()) { t in
t.tokenizer = .porter()
t.column("author")
t.column("title")
t.column("body")
}
FTS5 supports options:
// CREATE VIRTUAL TABLE book USING fts5(
// content,
// uuid UNINDEXED,
// content='table',
// content_rowid='id',
// prefix='2 4',
// columnsize=0,
// detail=column
// )
try db.create(virtualTable: "document", using: FTS5()) { t in
t.column("content")
t.column("uuid").notIndexed()
t.content = "table"
t.contentRowID = "id"
t.prefixes = [2, 4]
t.columnSize = 0
t.detail = "column"
}
The content
and contentRowID
options are involved in "contentless" and "external content" full-text tables. GRDB can help you defining full-text tables that automatically synchronize with their content table. See External Content Full-Text Tables.
See SQLite documentation for more information.
A tokenizer defines what "matching" means. Depending on the tokenizer you choose, full-text searches won't return the same results.
SQLite ships with three built-in FTS5 tokenizers: ascii
, porter
and unicode61
that use different algorithms to match queries with indexed content.
try db.create(virtualTable: "book", using: FTS5()) { t in
// Pick one:
t.tokenizer = .unicode61() // default
t.tokenizer = .unicode61(...)
t.tokenizer = .ascii
t.tokenizer = .porter(...)
}
See below some examples of matches:
content | query | ascii | unicode61 | porter on ascii | porter on unicode61 |
---|---|---|---|---|---|
Foo | Foo | X | X | X | X |
Foo | FOO | X | X | X | X |
Jérôme | Jérôme | X ¹ | X ¹ | X ¹ | X ¹ |
Jérôme | JÉRÔME | X ¹ | X ¹ | ||
Jérôme | Jerome | X ¹ | X ¹ | ||
Database | Databases | X | X | ||
Frustration | Frustrated | X | X |
¹ Don't miss Unicode Full-Text Gotchas
-
unicode61
try db.create(virtualTable: "book", using: FTS5()) { t in t.tokenizer = .unicode61() t.tokenizer = .unicode61(diacritics: .keep) }
The default "unicode61" tokenizer is case-insensitive for unicode characters. It matches "Jérôme" with "JÉRÔME".
It strips diacritics from latin script characters by default, and matches "jérôme" with "jerome". This behavior can be disabled, as in the example above.
It does not provide stemming, and won't match "databases" with "database".
-
ascii
try db.create(virtualTable: "book", using: FTS5()) { t in t.tokenizer = .ascii }
The "ascii" tokenizer is case-insensitive for ASCII characters. It matches "foo" with "FOO", but not "Jérôme" with "JÉRÔME".
It does not provide stemming, and won't match "databases" with "database".
It does not strip diacritics from latin script characters, and won't match "jérôme" with "jerome".
-
porter
try db.create(virtualTable: "book", using: FTS5()) { t in t.tokenizer = .porter() // porter wrapping unicode61 (the default) t.tokenizer = .porter(.ascii) // porter wrapping ascii t.tokenizer = .porter(.unicode61(diacritics: .keep)) // porter wrapping unicode61 without diacritics stripping }
The porter tokenizer is a wrapper tokenizer which compares English words according to their roots: it matches "database" with "databases", and "frustration" with "frustrated".
It strips diacritics from latin script characters if it wraps unicode61, and does not if it wraps ascii (see the example above).
See SQLite tokenizers for more information, and custom FTS5 tokenizers in order to add your own tokenizers.
Full-text search in FTS5 tables is performed with search patterns:
database
matches all documents that contain "database"data*
matches all documents that contain a word starting with "data"SQLite database
matches all documents that contain both "SQLite" and "database"SQLite OR database
matches all documents that contain "SQLite" or "database""SQLite database"
matches all documents that contain the "SQLite database" phrase
Not all search patterns are valid: they must follow the Full-Text Query Syntax.
The FTS5Pattern type helps you validating patterns, and building valid patterns from untrusted strings (such as strings typed by users):
extension Database {
func makeFTS5Pattern(rawPattern: String, forTable table: String) throws -> FTS5Pattern
}
struct FTS5Pattern {
init?(matchingAnyTokenIn string: String)
init?(matchingAllTokensIn string: String)
init?(matchingPhrase string: String)
}
The Database.makeFTS5Pattern(rawPattern:forTable:)
method validates your raw patterns against the query grammar and the columns of the targeted table, and may throw a DatabaseError:
// OK: FTS5Pattern
try db.makeFTS5Pattern(rawPattern: "sqlite", forTable: "book")
// DatabaseError: syntax error near \"AND\"
try db.makeFTS5Pattern(rawPattern: "AND", forTable: "book")
// DatabaseError: no such column: missing
try db.makeFTS5Pattern(rawPattern: "missing: sqlite", forTable: "book")
The FTS5Pattern initializers don't throw. They build a valid pattern from any string, including strings provided by users of your application. They let you find documents that match all given words, any given word, or a full phrase, depending on the needs of your application:
let query = "SQLite database"
// Matches documents that contain "SQLite" or "database"
let pattern = FTS5Pattern(matchingAnyTokenIn: query)
// Matches documents that contain both "SQLite" and "database"
let pattern = FTS5Pattern(matchingAllTokensIn: query)
// Matches documents that contain "SQLite database"
let pattern = FTS5Pattern(matchingPhrase: query)
// Matches documents that start with "SQLite database"
let pattern = FTS5Pattern(matchingPrefixPhrase: query)
They return nil when no pattern could be built from the input string:
let pattern = FTS5Pattern(matchingAnyTokenIn: "") // nil
let pattern = FTS5Pattern(matchingAnyTokenIn: "*") // nil
FTS5Pattern are regular values. You can use them as query arguments:
let documents = try Document.fetchAll(db,
sql: "SELECT * FROM document WHERE document MATCH ?",
arguments: [pattern])
Use them in the query interface:
let documents = try Document.matching(pattern).fetchAll(db)
FTS5 can sort results by relevance (most to least relevant):
// SQL
let documents = try Document.fetchAll(db,
sql: "SELECT * FROM document WHERE document MATCH ? ORDER BY rank",
arguments: [pattern])
// Query Interface
let documents = try Document.matching(pattern).order(Column.rank).fetchAll(db)
For more information about the ranking algorithm, as well as extra options, read Sorting by Auxiliary Function Results
GRDB does not provide any ranking for FTS3 and FTS4. See SQLite's Search Application Tips if you really need it.
An external content table does not store the indexed text. Instead, it indexes the text stored in another table.
This is very handy when you want to index a table that can not be declared as a full-text table (because it contains non-textual values, for example). You just have to define an external content full-text table that refers to the regular table.
The two tables must be kept up-to-date, so that the full-text index matches the content of the regular table. This synchronization happens automatically if you use the synchronize(withTable:)
method in your full-text table definition:
// A regular table
try db.create(table: "book") { t in
t.column("author", .text)
t.column("title", .text)
t.column("content", .text)
...
}
// A full-text table synchronized with the regular table
try db.create(virtualTable: "book_ft", using: FTS4()) { t in // or FTS5()
t.synchronize(withTable: "book")
t.column("author")
t.column("title")
t.column("content")
}
The eventual content already present in the regular table is indexed, and every insert, update or delete that happens in the regular table is automatically applied to the full-text index.
For more information, see the SQLite documentation about external content tables: FTS4, FTS5.
See also WWDC Companion, a sample app that uses external content tables to store, display, and let the user search the WWDC sessions.
Synchronization of full-text tables with their content table happens by the mean of SQL triggers.
SQLite automatically deletes those triggers when the content (not full-text) table is dropped.
However, those triggers remain after the full-text table has been dropped. Unless they are dropped too, they will prevent future insertion, updates, and deletions in the content table, and the creation of a new full-text table.
To drop those triggers, use the dropFTS4SynchronizationTriggers
or dropFTS5SynchronizationTriggers
methods:
// Create tables
try db.create(table: "book") { t in
...
}
try db.create(virtualTable: "book_ft", using: FTS4()) { t in
t.synchronize(withTable: "book")
...
}
// Drop full-text table
try db.drop(table: "book_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "book_ft")
⚠️ Warning: there was a bug in GRDB up to version 2.3.1 included, which created triggers with a wrong name. If it is possible that the full-text table was created by an old version of GRDB, then delete the synchronization triggers twice: once with the name of the deleted full-text table, and once with the name of the content table:// Drop full-text table try db.drop(table: "book_ft") try db.dropFTS4SynchronizationTriggers(forTable: "book_ft") try db.dropFTS4SynchronizationTriggers(forTable: "book") // Support for GRDB <= 2.3.1
When you need to perform a full-text search, and the external content table contains all the data you need, you can simply query the full-text table.
But if you need to load columns from the regular table, and in the same time perform a full-text search, then you will need to query both tables at the same time.
That is because SQLite will throw an error when you try to perform a full-text search on a regular table:
// SQLite error 1: unable to use function MATCH in the requested context
// SELECT * FROM book WHERE book MATCH '...'
let books = Book.matching(pattern).fetchAll(db)
The solution is to perform a joined request, using raw SQL:
let sql = """
SELECT book.*
FROM book
JOIN book_ft
ON book_ft.rowid = book.rowid
AND book_ft MATCH ?
"""
let books = Book.fetchAll(db, sql: sql, arguments: [pattern])
You can define record types around the full-text virtual tables.
However these tables don't have any explicit primary key. Instead, they use the implicit rowid primary key: a special hidden column named rowid
.
You will have to expose this hidden column in order to fetch, delete, and update full-text records by primary key.
The SQLite built-in tokenizers for FTS3, FTS4 and FTS5 are generally unicode-aware, with a few caveats, and limitations.
Generally speaking, matches may fail when content and query don't use the same unicode normalization. SQLite actually exhibits inconsistent behavior in this regard.
For example, for "aimé" to match "aimé", they better have the same normalization: the NFC "aim\u{00E9}" form may not match its NFD "aime\u{0301}" equivalent. Most strings that you get from Swift, UIKit and Cocoa use NFC, so be careful with NFD inputs (such as strings from the HFS+ file system, or strings that you can't trust like network inputs). Use String.precomposedStringWithCanonicalMapping to turn a string into NFC.
Besides, if you want "fi" to match the ligature "fi" (U+FB01), then you need to normalize your indexed contents and inputs to NFKC or NFKD. Use String.precomposedStringWithCompatibilityMapping to turn a string into NFKC.
Unicode normalization is not the end of the story, because it won't help "Encyclopaedia" match "Encyclopædia", "Mueller", "Müller", "Grossmann", "Großmann", or "Diyarbakır", "DIYARBAKIR". The String.applyingTransform method can help.
GRDB lets you write custom FTS5 tokenizers that can transparently deal with all these issues. For FTS3 and FTS4, you'll need to pre-process your strings before injecting them in the full-text engine.
Happy indexing!
GRDB helps consuming joined queries with complex selection.
In this chapter, we will focus on the extraction of information from complex rows, such as the ones fetched by the query below:
-- How to consume the left, middle, and right parts of those rows?
SELECT player.*, team.*, MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...
We will not talk about the generation of joined queries, which is covered in Associations.
So what are we talking about?
It is difficult to consume rows fetched from complex joined queries, because they often contain several columns with the same name: id
from table player
, id
from table team
, etc.
When such ambiguity happens, GRDB row accessors always favor the leftmost matching column. This means that row["id"]
would give a player id, whithout any obvious way to access the team id.
A classical technique to avoid this ambiguity is to give each column a unique name. For example:
-- A classical technique
SELECT player.id AS player_id, player.name AS player_name, team.id AS team_id, team.name AS team_name, team.color AS team_color, MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...
This technique works pretty well, but it has three drawbacks:
- The selection becomes hard to read and understand.
- Such queries are difficult to write by hand.
- The mangled names are a very bad fit for FetchableRecord types that expect specific column names. After all, if the
Team
record type can readSELECT * FROM team ...
, it should be able to readSELECT ..., team.*, ...
as well.
We thus need another technique. Below we'll see how to split rows into slices, and preserve column names.
SELECT player.*, team.*, MAX(round.score) AS maxScore FROM ...
will be splitted into three slices: one that contains player's columns, one that contains team's columns, and a remaining slice that contains remaining column(s). The Player record type will be able to read the first slice, which contains the colums expected by the Player.init(row:)
initializer. In the same way, the Team record type could read the second slice.
Unlike the name-mangling technique, splitting rows keeps SQL legible, accepts your hand-crafted SQL queries, and plays as nicely as possible with your existing record types.
- Splitting Rows, an Introduction
- Splitting Rows, the Record Way
- Splitting Rows, the Request Way
- Splitting Rows, the Codable Way
Let's first write some introductory code, hoping that this chapter will make you understand how pieces fall together. We'll see later how records will help us streamline the initial approach, how to track changes in joined requests, and how we can use the standard Decodable protocol.
To split rows, we will use row adapters. Row adapters adapt rows so that row consumers see exactly the columns they want. Among other things, row adapters can define several row scopes that give access to as many row slices. Sounds like a perfect match.
At the very beginning, there is an SQL query:
try dbQueue.read { db in
let sql = """
SELECT player.*, team.*, MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...
"""
We need an adapter that extracts player columns, in a slice that has as many columns as there are columns in the player table. That's RangeRowAdapter:
// SELECT player.*, team.*, ...
// <------>
let playerWidth = try db.columns(in: "player").count
let playerAdapter = RangeRowAdapter(0 ..< playerWidth)
We also need an adapter that extracts team columns:
// SELECT player.*, team.*, ...
// <---->
let teamWidth = try db.columns(in: "team").count
let teamAdapter = RangeRowAdapter(playerWidth ..< (playerWidth + teamWidth))
We merge those two adapters in a single ScopeAdapter that will allow us to access both sliced rows:
let playerScope = "player"
let teamScope = "team"
let adapter = ScopeAdapter([
playerScope: playerAdapter,
teamScope: teamAdapter])
And now we can fetch, and start consuming our rows. You already know row cursors:
let rows = try Row.fetchCursor(db, sql: sql, adapter: adapter)
while let row = try rows.next() {
From a fetched row, we can build a player:
let player: Player = row[playerScope]
In the SQL query, the team is joined with the LEFT JOIN
operator. This means that the team may be missing: its slice may contain team values, or it may only contain NULLs. When this happens, we don't want to build a Team record, and we thus load an optional Team:
let team: Team? = row[teamScope]
And finally, we can load the maximum score, assuming that the "maxScore" column is not ambiguous:
let maxScore: Int = row["maxScore"]
print("player: \(player)")
print("team: \(team)")
print("maxScore: \(maxScore)")
}
}
💡 In this chapter, we have learned:
- how to use
RangeRowAdapter
to extract a specific table's columns into a row slice.- how to use
ScopeAdapter
to gives access to several row slices through named scopes.- how to use Row subscripting to extract records from rows, or optional records in order to deal with left joins.
Our introduction above has introduced important techniques. It uses row adapters in order to split rows. It uses Row subscripting in order to extract records from row slices.
But we may want to make it more usable and robust:
- It's generally easier to consume records than raw rows.
- Joined records not always need all columns from a table (see
TableRecord.databaseSelection
in Columns Selected by a Request). - Building row adapters is long and error prone.
To address the first bullet, let's define a record that holds our player, optional team, and maximum score. Since it can decode database rows, it adopts the FetchableRecord protocol:
struct PlayerInfo {
var player: Player
var team: Team?
var maxScore: Int
}
/// PlayerInfo can decode rows:
extension PlayerInfo: FetchableRecord {
private enum Scopes {
static let player = "player"
static let team = "team"
}
init(row: Row) {
player = row[Scopes.player]
team = row[Scopes.team]
maxScore = row["maxScore"]
}
}
Let's now write the method that fetches PlayerInfo records:
extension PlayerInfo {
static func fetchAll(_ db: Database) throws -> [PlayerInfo] {
To acknowledge that both Player and Team records may customize their selection of the "player" and "team" columns, we'll write our SQL in a slightly different way:
// Let Player and Team customize their selection:
let sql = """
SELECT
\(Player.selectionSQL()), -- instead of player.*
\(Team.selectionSQL()), -- instead of team.*
MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...
"""
Player.selectionSQL()
will output player.*
, unless Player defines a customized selection.
☝️ Note: you may also use SQL table aliases:
let sql = """ SELECT \(Player.selectionSQL(alias: "p")), \(Team.selectionSQL(alias: "t")), MAX(r.score) AS maxScore FROM player p LEFT JOIN team t ON ... LEFT JOIN round r ON ... GROUP BY ... """
Now is the time to build adapters (taking in account the customized selection of both player and team). We use the splittingRowAdapters
global function, which builds row adapters of desired widths:
let adapters = try splittingRowAdapters(columnCounts: [
Player.numberOfSelectedColumns(db),
Team.numberOfSelectedColumns(db)])
let adapter = ScopeAdapter([
Scopes.player: adapters[0],
Scopes.team: adapters[1]])
☝️ Note:
splittingRowAdapters
returns as many adapters as necessary to fully split a row. In the example above, it returns three adapters: one for player, one for team, and one for the remaining columns.
And finally, we can fetch player infos:
return try PlayerInfo.fetchAll(db, sql: sql, adapter: adapter)
}
}
And when your app needs to fetch player infos, it now reads:
// Fetch player infos
let playerInfos = try dbQueue.read { db in
try PlayerInfo.fetchAll(db)
}
💡 In this chapter, we have learned:
- how to define a
FetchableRecord
record that consumes rows fetched from a joined query.- how to use
selectionSQL
andnumberOfSelectedColumns
in order to deal with nested record types that define custom selection.- how to use
splittingRowAdapters
in order to streamline the definition of row slices.- how to gather all relevant methods and constants in a record type, fully responsible of its relationship with the database.
The PlayerInfo.fetchAll
method above directly fetches records. It's all good, but in order to profit from database observation, you'll need a custom request that defines a database query.
It is recommended that you read the previous paragraphs before you dive in this sample code. We start with the same PlayerInfo record as above:
struct PlayerInfo {
var player: Player
var team: Team?
var maxScore: Int
}
/// PlayerInfo can decode rows:
extension PlayerInfo: FetchableRecord {
private enum Scopes {
static let player = "player"
static let team = "team"
}
init(row: Row) {
player = row[Scopes.player]
team = row[Scopes.team]
maxScore = row["maxScore"]
}
}
Now we write a method that returns a request, and build the fetching method on top of that request:
extension PlayerInfo {
/// The request for all player infos
static func all() -> AdaptedFetchRequest<SQLRequest<PlayerInfo>> {
let sql = """
SELECT
\(Player.selectionSQL()),
\(Team.selectionSQL()),
MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...
"""
return SQLRequest<PlayerInfo>(sql: sql).adapted { db in
let adapters = try splittingRowAdapters(columnCounts: [
Player.numberOfSelectedColumns(db),
Team.numberOfSelectedColumns(db)])
return ScopeAdapter([
Scopes.player: adapters[0],
Scopes.team: adapters[1]])
}
}
/// Fetches all player infos
static func fetchAll(_ db: Database) throws -> [PlayerInfo] {
return try all().fetchAll(db)
}
}
It is now time to use our request:
// Fetch player infos
let playerInfos = try dbQueue.read { db in
try PlayerInfo.fetchAll(db)
}
// Track player infos with RxRGDB:
PlayerInfo.all()
.rx.fetchAll(in: dbQueue)
.subscribe(onNext: { (playerInfos: [PlayerInfo]) in
print("Player infos have changed")
})
💡 In this chapter, we have learned how to define a custom request that can both fetch records from joined queries, and feed database observation tools.
Codable Records build on top of the standard Decodable protocol in order to decode database rows.
You can consume complex joined queries with Codable records as well. As a demonstration, we'll rewrite the above sample code:
struct Player: Decodable, FetchableRecord, TableRecord {
var id: Int64
var name: String
}
struct Team: Decodable, FetchableRecord, TableRecord {
var id: Int64
var name: String
var color: Color
}
struct PlayerInfo: Decodable, FetchableRecord {
var player: Player
var team: Team?
var maxScore: Int
}
extension PlayerInfo {
/// The request for all player infos
static func all() -> AdaptedFetchRequest<SQLRequest<PlayerInfo>> {
let sql = """
SELECT
\(Player.selectionSQL()),
\(Team.selectionSQL()),
MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...
"""
return SQLRequest<PlayerInfo>(sql: sql).adapted { db in
let adapters = try splittingRowAdapters(columnCounts: [
Player.numberOfSelectedColumns(db),
Team.numberOfSelectedColumns(db)])
return ScopeAdapter([
CodingKeys.player.stringValue: adapters[0],
CodingKeys.team.stringValue: adapters[1]])
}
}
/// Fetches all player infos
static func fetchAll(_ db: Database) throws -> [PlayerInfo] {
return try all().fetchAll(db)
}
}
// Fetch player infos
let playerInfos = try dbQueue.read { db in
try PlayerInfo.fetchAll(db)
}
// Track player infos with RxRGDB:
PlayerInfo.all()
.rx.fetchAll(in: dbQueue)
.subscribe(onNext: { (playerInfos: [PlayerInfo]) in
print("Player infos have changed")
})
💡 In this chapter, we have learned how to use the
Decodable
protocol and its associatedCodingKeys
enum in order to dry up our code.
SQLite notifies its host application of changes performed to the database, as well of transaction commits and rollbacks.
GRDB puts this SQLite feature to some good use, and lets you observe the database in various ways:
- After Commit Hook: Handle successful transactions one by one.
- ValueObservation and DatabaseRegionObservation: Automated tracking of database requests.
- TransactionObserver Protocol: Low-level database observation.
- GRDBCombine: Automated tracking of database changes, with Combine.
- RxGRDB: Automated tracking of database changes, with RxSwift.
Database observation requires that a single database queue or pool is kept open for all the duration of the database usage.
When your application needs to make sure a specific database transaction has been successfully committed before it executes some work, use the Database.afterNextTransactionCommit(_:)
method.
Its closure argument is called right after database changes have been successfully written to disk:
try dbQueue.write { db in
db.afterNextTransactionCommit { db in
print("success")
}
...
} // prints "success"
The closure runs in a protected dispatch queue, serialized with all database updates.
This "after commit hook" helps synchronizing the database with other resources, such as files, or system sensors.
In the example below, a location manager starts monitoring a CLRegion if and only if it has successfully been stored in the database:
/// Inserts a region in the database, and start monitoring upon
/// successful insertion.
func startMonitoring(_ db: Database, region: CLRegion) throws {
// Make sure database is inside a transaction
try db.inSavepoint {
// Save the region in the database
try insert(...)
// Start monitoring if and only if the insertion is
// eventually committed
db.afterNextTransactionCommit { _ in
// locationManager prefers the main queue:
DispatchQueue.main.async {
locationManager.startMonitoring(for: region)
}
}
return .commit
}
}
The method above won't trigger the location manager if the transaction is eventually rollbacked (explicitly, or because of an error), as in the sample code below:
try dbQueue.write { db in
// success
try startMonitoring(db, region)
// On error, the transaction is rollbacked, the region is not inserted, and
// the location manager is not invoked.
try failableMethod(db)
}
ValueObservation and DatabaseRegionObservation are two database observations tools that track changes in database requests.
// Let's observe all players!
let request = Player.all()
ValueObservation notifies your application with fresh values (this is what most applications need 👍):
let observation = ValueObservation.tracking { db in
try request.fetchAll(db)
}
let observer = observation.start(
in: dbQueue,
onError: { error in
print("fresh players could not be fetched")
},
onChange: { (players: [Player]) in
let names = players.map { $0.name }.joined(separator: ", ")
print("Fresh players: \(names)")
})
try dbQueue.write { db in
try Player(name: "Arthur").insert(db)
}
// Prints "Fresh players: Arthur, ..."
DatabaseRegionObservation notifies your application with database connections, right after an impactful database transaction has been committed (reserved for more advanced use cases 🤓):
let observation = DatabaseRegionObservation(tracking: request)
let observer = try observation.start(in: dbQueue) { (db: Database) in
print("Players have changed.")
}
try dbQueue.write { db in
try Player(name: "Barbara").insert(db)
}
// Prints "Players have changed."
ValueObservation tracks changes in the results of database requests, and notifies fresh values whenever the database changes.
Changes are only notified after they have been committed in the database. No insertion, update, or deletion in tracked tables is missed. This includes indirect changes triggered by foreign keys or SQL triggers.
- ValueObservation Usage
- ValueObservation.tracking(value:)
- ValueObservation.tracking(_:fetch:)
- observationForCount, observationForAll, observationForFirst
- ValueObservation Transformations: map, compactMap, ...
- ValueObservation Error Handling
- ValueObservation Options
- Advanced: ValueObservation.tracking(_:reducer:)
Here is a typical UIViewController which observes the database in order to keep its view up-to-date:
class PlayerViewController: UIViewController {
@IBOutlet weak var nameLabel: UILabel!
private var observer: TransactionObserver?
override func viewWillAppear(_ animated: Bool) {
super.viewWillAppear(animated)
// Define a ValueObservation which tracks a player
let observation = ValueObservation.tracking { db in
try Player.fetchOne(db, key: 42)
}
// Start observing the database
observer = observation.start(
in: dbQueue,
onError: { error in
print("player could not be fetched")
},
onChange: { [weak self] (player: Player?) in
// Player has been refreshed: update view
guard let self = self else { return }
self.nameLabel.text = player?.name
})
}
override func viewWillDisappear(_ animated: Bool) {
super.viewWillDisappear(animated)
// Stop observing the database
observer = nil
}
}
By default, all values and errors are notified on the main queue. Views can be updated right from the onChange
callback.
By default, an initial fetch is performed as soon as the observation starts: the view is set up and ready when the viewWillAppear
method returns.
The observer returned by the start
method is stored in a property of the view controller. This allows the view controller to control the duration of the observation. When the observer is deallocated, the observation stops. Meanwhile, all transactions that modify the observed player are notified, and the nameLabel
is kept up-to-date.
💡 Tip: see the Demo Application for a sample app that uses ValueObservation.
💡 Tip: When fetching values is slow, and should never ever block the main queue, opt in for async notifications:
override func viewWillAppear(_ animated: Bool) { super.viewWillAppear(animated) // Define a ValueObservation which tracks a player let observation = ValueObservation.tracking { db in try Player.fetchOne(db, key: 42) } // Observation is asynchronous observation.scheduling = .async(onQueue: .main, startImmediately: true) // Start observing the database observer = observation.start( in: dbQueue, onError: { error in print("player could not be fetched") }, onChange: { [weak self] (player: Player?) in // Player has been refreshed: update view guard let self = self else { return } self.activityIndicator.stopAnimating() self.nameLabel.text = player?.name }) // Wait for player activityIndicator.startAnimating() nameLabel.text = nil }See ValueObservation.scheduling for more information.
In order to observe database values, you will generally define a ValueObservation which tracks the value you are interested in, and then start the observation.
For example:
// Track changes in a single player
let observation = ValueObservation.tracking { db in
try Player.fetchOne(db, key: 42)
}
observer = observation.start(
in: dbQueue,
onError: { error in ... },
onChange: { (player: Player?) in
print("Fresh player: \(player)")
})
You can observe several requests and several tables if you need: all writes that have an impact on the fetched values will trigger the observation, and call the onChange
function.
It may happen that such an observation notifies identical consecutive values. This is because it will fetch a fresh value whenever a change could happen. For example, the observation for the maximum player score will notify a fresh value everytime a score is changed, inserted, or deleted, even if the maximum score is unchanged:
// Track changes in the maximum player score
// This observation may notify duplicate values
let observation = ValueObservation.tracking { db in
try Player.select(max(Column("score")), as: Int.self).fetchOne(db)
}
You can filter out those duplicates with the ValueObservation.removeDuplicates method. It requires the observed value to adopt the Equatable protocol:
let observation = ValueObservation
.tracking { db in
try Player.select(max(Column("score")), as: Int.self).fetchOne(db)
}
.removeDuplicates()
We will see below other ways to define observations. They all add a little convenience, or optimization.
The ValueObservation.tracking(_:fetch:)
method is an optimized version of the ValueObservation.tracking(value:)
method seen above.
The returned observation ouputs exactly the same results, but it can perform better when you use a database pool, and the fetch is slow. It reduces write contention by fetching fresh values without blocking write accesses. When you use a database queue, no optimization is applied.
It accepts two arguments:
- A list of observed requests.
- A closure that fetches a fresh value whenever one of the observed requests are modified.
Changes that happen outside of the observed requests are ignored, so make sure you fully cover the database region you want to observe. This is the price you pay for the optimization.
Let's give a practical example, and observe the "Hall of Fame":
struct HallOfFame {
var totalPlayerCount: Int
var bestPlayers: [Player]
}
extension HallOfFame {
/// Fetch the HallOfFame
static fetch(_ db: Database) throws -> HallOfFame {
let totalPlayerCount = try Player.fetchCount(db)
let bestPlayers = try Player
.order(Column("score").desc)
.limit(10)
.fetchAll(db)
return HallOfFame(
totalPlayerCount: totalPlayerCount,
bestPlayers: bestPlayers)
}
}
In order to track changes in the Hall of Fame in an optimized way, we see that any change to the player
table can impact the Hall of Fame. We thus track the request for all players, Player.all()
, and fetch a new Hall of Fame whenever players change:
let observation = ValueObservation.tracking(Player.all(), fetch: { db in
try HallOfFame.fetch(db)
})
☝️ Note: the initial parameter of
ValueObservation.tracking(_:fetch:)
can be fed with requests, and generally speaking, values that adopt the DatabaseRegionConvertible protocol.
Given a request, even a custom request, you can observe its number of results, all results, or the first one:
request.observationForCount()
request.observationForAll()
request.observationForFirst()
Those observations are equivalent to the following ones, defined with ValueObservation.tracking(value:)
:
ValueObservation.tracking { db in try request.fetchCount(db) }
ValueObservation.tracking { db in try request.fetchAll(db) }
ValueObservation.tracking { db in try request.fetchOne(db) }
Yet they are optimized:
- They perform a filtering of consecutive identical values, based on raw database values, so that you are not notified of database changes that do not impact the result of the request.
- They can perform better when you use a database pool, and the fetch is slow.
- ValueObservation.map
- ValueObservation.compactMap
- ValueObservation.removeDuplicates
- ValueObservation.combine(...)
The map
method lets you transform the values notified by a ValueObservation.
For example:
// Observe a player's profile image
let observation = ValueObservation
.tracking { db in try Player.fetchOne(db, key: 42) }
.map { player in player?.image }
let observer = observation.start(
in: dbQueue,
onError: { error in ... },
onChange: { (image: UIImage?) in
print("Player picture has changed")
})
The transformation closure does not run on the main queue, and is suitable for heavy computations.
The compactMap
method lets you transform and filter the values notified by a ValueObservation. Only non-nil transformed values are notified.
For example:
// Observe a player
let observation = ValueObservation
.tracking { db in try Player.fetchOne(db, key: 42) }
.compactMap { $0 }
let observer = observation.start(
in: dbQueue,
onError: { error in ... },
onChange: { (player: Player) in
print("Player name: \(player.name)")
})
The transformation closure does not run on the main queue, and is suitable for heavy computations.
The removeDuplicates
method filters out the consecutive equal values notified by a ValueObservation. The observed values must adopt the standard Equatable protocol.
For example:
let observation = ValueObservation
.tracking { db in try Player.fetchOne(db, key: 42) }
.removeDuplicates()
let observer = observation.start(
in: dbQueue,
onError: { error in ... },
onChange: { (player: Player) in
print("Player: \(player)")
})
☝️ Note: the observations returned by the observationForCount, observationForAll, observationForFirst methods already perform a similar filtering, based on raw database values.
The ValueObservation.combine(...)
method builds a single observation from several:
// Two base observations
let playerCountObservation = ValueObservation.tracking { db in
try Player.fetchCount(db)
}
let bestPlayersObservation = ValueObservation.tracking { db in
try Player
.limit(10)
.order(Column("score").desc)
.fetchAll(db)
}
// The combined observation
let observation = ValueObservation.combine(
playerCountObservation,
bestPlayersObservation)
// Start tracking the hall of fame
let observer = observation.start(
in: dbQueue,
onError: { error in ... },
onChange: { (totalPlayerCount, bestPlayers) in
print("""
Best players out of \(totalPlayerCount):
\(bestPlayers)
""")
})
combine
also exists as an instance method:
struct HallOfFame {
var totalPlayerCount: Int
var bestPlayers: [Player]
}
let observation = playerCountObservation.combine(bestPlayersObservation) {
HallOfFame(totalPlayerCount: $0, bestPlayers: $1)
}
You can combine up to eight observations together. They can feed from as many database tables as needed.
Combining observations provides the guarantee that notified values are consistent.
☝️ Note: readers who are familiar with Reactive Programming will recognize the CombineLatest operator in the ValueObservation
combine
method. The reactive operator does not care about data consistency, though: if you use a Reactive layer such as GRDBCombine or RxGRDB, make sure you compose observations withValueObservation.combine
, not with the CombineLatest operator.
When you start an observation, the onError
callback is called whenever fresh values could not be fetched. It is scheduled just like values (see ValueObservation.scheduling):
let observer = observation.start(
in: dbQueue,
onError: { error in
print("fresh value could not be fetched")
},
onChange: { value in
print("fresh value: \(value)")
})
An error does not stop the observation. After an error has been received, subsequent transactions may succeed in notifying fresh values. You may witness such temporary errors when the database becomes temporarily unreachable, for example due to data protection.
Depending on the way your application wants to deal with such errors, you may want to tighten your control on the scheduling of database accesses with DatabaseRegionObservation. See also the reactive companion libraries GRDBCombine and RxGRDB, which stop observation whenever a ValueObservation error happens.
The onError
callback can be omitted, but this is not recommended:
// Not recommended: omitting the onError callback
let observer = try observation.start(in: dbQueue) { value in
print("fresh value: \(value)")
}
Some behaviors of value observations can be configured:
- ValueObservation.scheduling: Control the dispatching of notified values.
- ValueObservation.requiresWriteAccess: Allow observations to write in the database.
The scheduling
property lets you control how fresh values are notified:
-
.mainQueue
(the default): all values are notified on the main queue.If the observation starts on the main queue, an initial value is notified right upon subscription, synchronously:
// On main queue let observer = observation.start( in: dbQueue, onError: { error in ... }, onChange: { value in // On main queue print("fresh value: \(value)") }) // <- Here "fresh value" is already printed.
If the observation does not start on the main queue, an initial value is also notified on the main queue, but asynchronously:
// Not on the main queue let observer = observation.start( in: dbQueue, onError: { error in ... }, onChange: { value in // On main queue print("fresh value: \(value)") })
After the initial value has been notified, all subsequent values are notified asynchronously:
try dbQueue.write { db in ... } // <- Eventually prints "fresh value" on the main queue
-
.async(onQueue:startImmediately:)
: all values are asychronously notified on the specified queue.An initial value is fetched and notified if
startImmediately
is true.For example:
// On main queue var observation = ... observation.scheduling = .async(onQueue: .main, startImmediately: true) let observer = observation.start( in: dbQueue, onError: { error in ... }, onChange: { value in // On main queue print("fresh value: \(value)") }) // <- Eventually prints "fresh value"
-
unsafe(startImmediately:)
: values are not all notified on the same dispatch queue.If
startImmediately
is true, an initial value is notified right upon subscription, synchronously, on the dispatch queue which starts the observation.// On any queue var observation = ... observation.scheduling = .unsafe(startImmediately: true) let observer = observation.start( in: dbQueue, onError: { error in ... }, onChange: { value in print("fresh value: \(value)") }) // <- Here "fresh value" is already printed.
After the initial value has been notified, all subsequent values are notified on unspecified queues.
☝️ Note: this unsafe mode is intended for third-party libraries that provide their own scheduling engine.
The requiresWriteAccess
property is false by default. When true, a ValueObservation has a write access to the database, and its fetches are automatically wrapped in a savepoint:
var observation = ValueObservation.tracking { db in
// write access allowed
...
}
observation.requiresWriteAccess = true
When you use a database pool, don't use this flag unless you really need it. Observations with write access are less efficient because they block all writes for the whole duration of a fetch.
The most low-level way to define a ValueObservation is to create one from an observed database region (see above), and a reducer that adopts the ValueReducer protocol (🔥 EXPERIMENTAL):
protocol ValueReducer {
associatedtype Fetched
associatedtype Value
/// Fetches a database value
func fetch(_ db: Database) throws -> Fetched
/// Returns a notified value
mutating func value(_ fetched: Fetched) -> Value?
}
The fetch
method is called upon changes in the observed database region. It runs inside a protected dispatch queue and is guaranteed an immutable view of the last committed state of the database.
The value
method transforms a fetched value into a notified value. It returns nil if the observer should not be notified. It runs inside a dispatch queue called the "reduce queue", which is not the main queue, and not a database queue.
The sample code below counts the number of times the player table is modified:
var count = 0
let reducer = AnyValueReducer(
fetch: { _ in /* don't fetch anything */ },
value: { _ -> Int? in
defer { count += 1 }
return count })
let observation = ValueObservation.tracking(Player.all(), reducer: { _ in reducer })
let observer = observation.start(
in: dbQueue,
onError: { error in ... },
onChange: { (count: Int) in
print("Number of transactions that have modified players: \(count)")
})
// Prints "Number of transactions that have modified players: 0"
try dbQueue.write { db in
try Player(...).insert(db)
}
// Prints "Number of transactions that have modified players: 1"
DatabaseRegionObservation tracks changes in database requests, and notifies each impactful transaction.
No insertion, update, or deletion in the tracked tables is missed. This includes indirect changes triggered by foreign keys or SQL triggers.
DatabaseRegionObservation calls your application right after changes have been committed in the database, and before any other thread had any opportunity to perform further changes. This is a pretty strong guarantee, that most applications do not really need. Instead, most applications prefer to be notified with fresh values: make sure you check ValueObservation before using DatabaseRegionObservation.
Define an observation by providing one or several requests to track:
// Track all players
let observation = DatabaseRegionObservation(tracking: Player.all())
Then start the observation from a database queue or pool:
let observer = try observation.start(in: dbQueue) { (db: Database) in
print("Players were changed")
}
And enjoy the changes notifications:
try dbQueue.write { db in
try Player(name: "Arthur").insert(db)
}
// Prints "Players were changed"
By default, the observation lasts until the observer returned by the start
method is deallocated. See DatabaseRegionObservation.extent for more details.
You can also feed DatabaseRegionObservation with DatabaseRegion, or any type which conforms to the DatabaseRegionConvertible protocol. For example:
// Observe the full database
let observation = DatabaseRegionObservation(tracking: DatabaseRegion.fullDatabase)
let observer = try observation.start(in: dbQueue) { (db: Database) in
print("Database was changed")
}
There are very few use cases for DatabaseRegionObservation.
For example:
-
One needs to write in the database after an impactful transaction.
-
One needs to synchronize the content of the database file with some external resources, like other files, or system sensors like CLRegion monitoring.
-
On iOS, one needs to process a database transaction before the operating system had any opportunity to put the application in the suspended state.
-
One want to build a database snapshot with a guaranteed snapshot content.
Outside of those use cases, it is much likely wrong to use a DatabaseRegionObservation. Please check other Database Observation options.
The extent
property lets you specify the duration of the observation. See Observation Extent for more details:
// This observation lasts until the database connection is closed
var observation = DatabaseRegionObservation...
observation.extent = .databaseLifetime
_ = try observation.start(in: dbQueue) { db in ... }
The default extent is .observerLifetime
: the observation stops when the observer returned by start
is deallocated.
Regardless of the extent of an observation, you can always stop observation with the remove(transactionObserver:)
method:
// Start
let observer = try observation.start(in: dbQueue) { db in ... }
// Stop
dbQueue.remove(transactionObserver: observer)
The TransactionObserver
protocol lets you observe individual database changes and transactions:
protocol TransactionObserver : class {
/// Notifies a database change:
/// - event.kind (insert, update, or delete)
/// - event.tableName
/// - event.rowID
///
/// For performance reasons, the event is only valid for the duration of
/// this method call. If you need to keep it longer, store a copy:
/// event.copy().
func databaseDidChange(with event: DatabaseEvent)
/// Filters the database changes that should be notified to the
/// `databaseDidChange(with:)` method.
func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool
/// An opportunity to rollback pending changes by throwing an error.
func databaseWillCommit() throws
/// Database changes have been committed.
func databaseDidCommit(_ db: Database)
/// Database changes have been rollbacked.
func databaseDidRollback(_ db: Database)
}
- Activate a Transaction Observer
- Database Changes And Transactions
- Filtering Database Events
- Observation Extent
- DatabaseRegion
- Support for SQLite Pre-Update Hooks
To activate a transaction observer, add it to the database queue or pool:
let observer = MyObserver()
dbQueue.add(transactionObserver: observer)
By default, database holds weak references to its transaction observers: they are not retained, and stop getting notifications after they are deallocated. See Observation Extent for more options.
A transaction observer is notified of all database changes: inserts, updates and deletes. This includes indirect changes triggered by ON DELETE and ON UPDATE actions associated to foreign keys, and SQL triggers.
☝️ Note: the changes that are not notified are changes to internal system tables (such as
sqlite_master
), changes toWITHOUT ROWID
tables, and the deletion of duplicate rows triggered byON CONFLICT REPLACE
clauses (this last exception might change in a future release of SQLite).
Notified changes are not actually written to disk until the transaction commits, and the databaseDidCommit
callback is called. On the other side, databaseDidRollback
confirms their invalidation:
try dbQueue.write { db in
try db.execute(sql: "INSERT ...") // 1. didChange
try db.execute(sql: "UPDATE ...") // 2. didChange
} // 3. willCommit, 4. didCommit
try dbQueue.inTransaction { db in
try db.execute(sql: "INSERT ...") // 1. didChange
try db.execute(sql: "UPDATE ...") // 2. didChange
return .rollback // 3. didRollback
}
try dbQueue.write { db in
try db.execute(sql: "INSERT ...") // 1. didChange
throw SomeError()
} // 2. didRollback
Database statements that are executed outside of any transaction do not drop off the radar:
try dbQueue.inDatabase { db in
try db.execute(sql: "INSERT ...") // 1. didChange, 2. willCommit, 3. didCommit
try db.execute(sql: "UPDATE ...") // 4. didChange, 5. willCommit, 6. didCommit
}
Changes that are on hold because of a savepoint are only notified after the savepoint has been released. This makes sure that notified events are only events that have an opportunity to be committed:
try dbQueue.inTransaction { db in
try db.execute(sql: "INSERT ...") // 1. didChange
try db.execute(sql: "SAVEPOINT foo")
try db.execute(sql: "UPDATE ...") // delayed
try db.execute(sql: "UPDATE ...") // delayed
try db.execute(sql: "RELEASE SAVEPOINT foo") // 2. didChange, 3. didChange
try db.execute(sql: "SAVEPOINT foo")
try db.execute(sql: "UPDATE ...") // not notified
try db.execute(sql: "ROLLBACK TO SAVEPOINT foo")
return .commit // 4. willCommit, 5. didCommit
}
Eventual errors thrown from databaseWillCommit
are exposed to the application code:
do {
try dbQueue.inTransaction { db in
...
return .commit // 1. willCommit (throws), 2. didRollback
}
} catch {
// 3. The error thrown by the transaction observer.
}
☝️ Note: all callbacks are called in a protected dispatch queue, and serialized with all database updates.
☝️ Note: the databaseDidChange(with:) and databaseWillCommit() callbacks must not touch the SQLite database. This limitation does not apply to databaseDidCommit and databaseDidRollback which can use their database argument.
DatabaseRegionObservation, ValueObservation, GRDBCombine, and RxGRDB are all based on the TransactionObserver protocol.
See also TableChangeObserver.swift, which shows a transaction observer that notifies of modified database tables with NSNotificationCenter.
Transaction observers can avoid being notified of database changes they are not interested in.
The filtering happens in the observes(eventsOfKind:)
method, which tells whether the observer wants notification of specific kinds of changes, or not. For example, here is how an observer can focus on the changes that happen on the "player" database table:
class PlayerObserver: TransactionObserver {
func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
// Only observe changes to the "player" table.
return eventKind.tableName == "player"
}
func databaseDidChange(with event: DatabaseEvent) {
// This method is only called for changes that happen to
// the "player" table.
}
}
Generally speaking, the observes(eventsOfKind:)
method can distinguish insertions from deletions and updates, and is also able to inspect the columns that are about to be changed:
class PlayerScoreObserver: TransactionObserver {
func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
// Only observe changes to the "score" column of the "player" table.
switch eventKind {
case .insert(let tableName):
return tableName == "player"
case .delete(let tableName):
return tableName == "player"
case .update(let tableName, let columnNames):
return tableName == "player" && columnNames.contains("score")
}
}
}
When the observes(eventsOfKind:)
method returns false for all event kinds, the observer is still notified of commits and rollbacks:
class PureTransactionObserver: TransactionObserver {
func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
// Ignore all individual changes
return false
}
func databaseDidChange(with event: DatabaseEvent) { /* Never called */ }
func databaseWillCommit() throws { /* Called before commit */ }
func databaseDidRollback(_ db: Database) { /* Called on rollback */ }
func databaseDidCommit(_ db: Database) { /* Called on commit */ }
}
For more information about event filtering, see DatabaseRegion.
You can specify how long an observer is notified of database changes and transactions.
The remove(transactionObserver:)
method explicitly stops notifications, at any time:
// From a database queue or pool:
dbQueue.remove(transactionObserver: observer)
// From a database connection:
dbQueue.inDatabase { db in
db.remove(transactionObserver: observer)
}
Alternatively, use the extent
parameter of the add(transactionObserver:extent:)
method:
let observer = MyObserver()
// On a database queue or pool:
dbQueue.add(transactionObserver: observer) // default extent
dbQueue.add(transactionObserver: observer, extent: .observerLifetime)
dbQueue.add(transactionObserver: observer, extent: .nextTransaction)
dbQueue.add(transactionObserver: observer, extent: .databaseLifetime)
// On a database connection:
dbQueue.inDatabase { db in
db.add(transactionObserver: ...)
}
-
The default extent is
.observerLifetime
: the database holds a weak reference to the observer, and the observation automatically ends when the observer is deallocated. Meanwhile, observer is notified of all changes and transactions. -
.nextTransaction
activates the observer until the current or next transaction completes. The database keeps a strong reference to the observer until itsdatabaseDidCommit
ordatabaseDidRollback
method is eventually called. Hereafter the observer won't get any further notification. -
.databaseLifetime
has the database retain and notify the observer until the database connection is closed.
Finally, an observer may ignore all database changes until the end of the current transaction:
class PlayerObserver: TransactionObserver {
var playerTableWasModified = false
func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
return eventKind.tableName == "player"
}
func databaseDidChange(with event: DatabaseEvent) {
playerTableWasModified = true
// It is pointless to keep on tracking further changes:
stopObservingDatabaseChangesUntilNextTransaction()
}
}
After stopObservingDatabaseChangesUntilNextTransaction()
, the databaseDidChange(with:)
method will not be notified of any change for the remaining duration of the current transaction. This helps GRDB optimize database observation.
DatabaseRegion is a type that helps observing changes in the results of a database request.
A request knows which database modifications can impact its results. It can communicate this information to transaction observers by the way of a DatabaseRegion.
DatabaseRegion fuels, for example, ValueObservation and DatabaseRegionObservation.
A region notifies potential changes, not actual changes in the results of a request. A change is notified if and only if a statement has actually modified the tracked tables and columns by inserting, updating, or deleting a row.
For example, if you observe the region of Player.select(max(Column("score")))
, then you'll get be notified of all changes performed on the score
column of the player
table (updates, insertions and deletions), even if they do not modify the value of the maximum score. However, you will not get any notification for changes performed on other database tables, or updates to other columns of the player table.
For more details, see the reference.
DatabaseRegionConvertible is a protocol for all types that can turn into a DatabaseRegion:
protocol DatabaseRegionConvertible {
func databaseRegion(_ db: Database) throws -> DatabaseRegion
}
All requests adopt this protocol, and this allows them to be observed with DatabaseRegionObservation and ValueObservation.
Use this protocol when you want to encapsulate your complex requests in a dedicated type, and still profit from optimized observation APIs. See ValueObservation.tracking(_:fetch:)
for more information.
When SQLite is built with the SQLITE_ENABLE_PREUPDATE_HOOK option, TransactionObserverType gets an extra callback which lets you observe individual column values in the rows modified by a transaction:
protocol TransactionObserverType : class {
#if SQLITE_ENABLE_PREUPDATE_HOOK
/// Notifies before a database change (insert, update, or delete)
/// with change information (initial / final values for the row's
/// columns).
///
/// The event is only valid for the duration of this method call. If you
/// need to keep it longer, store a copy: event.copy().
func databaseWillChange(with event: DatabasePreUpdateEvent)
#endif
}
This extra API can be activated in two ways:
-
Use the GRDB.swift CocoaPod with a custom compilation option, as below. It uses the system SQLite, which is compiled with SQLITE_ENABLE_PREUPDATE_HOOK support, but only on iOS 11.0+ (we don't know the minimum version of macOS, tvOS, watchOS):
pod 'GRDB.swift' platform :ios, '11.0' # or above post_install do |installer| installer.pods_project.targets.select { |target| target.name == "GRDB.swift" }.each do |target| target.build_configurations.each do |config| # Enable extra GRDB APIs config.build_settings['OTHER_SWIFT_FLAGS'] = "$(inherited) -D SQLITE_ENABLE_PREUPDATE_HOOK" # Enable extra SQLite APIs config.build_settings['GCC_PREPROCESSOR_DEFINITIONS'] = "$(inherited) GRDB_SQLITE_ENABLE_PREUPDATE_HOOK=1" end end end
⚠️ Warning: make sure you use the right platform version! You will get runtime errors on devices with a lower version.☝️ Note: the
GRDB_SQLITE_ENABLE_PREUPDATE_HOOK=1
option inGCC_PREPROCESSOR_DEFINITIONS
defines some C function prototypes that are lacking from the system<sqlite3.h>
header. When Xcode eventually ships with an SDK that includes a complete header, you may get a compiler error about duplicate function definitions. When this happens, just remove thisGRDB_SQLITE_ENABLE_PREUPDATE_HOOK=1
option. -
Use a custom SQLite build and activate the
SQLITE_ENABLE_PREUPDATE_HOOK
compilation option.
GRDB can encrypt your database with SQLCipher v3.4+.
Use CocoaPods, and specify in your Podfile
:
# GRDB with SQLCipher 4
pod 'GRDB.swift/SQLCipher'
pod 'SQLCipher', '~> 4.0'
# GRDB with SQLCipher 3
pod 'GRDB.swift/SQLCipher'
pod 'SQLCipher', '~> 3.4'
- Creating or Opening an Encrypted Database
- Changing the Passphrase of an Encrypted Database
- Exporting a Database to an Encrypted Database
- Security Considerations
You create and open an encrypted database by providing a passphrase to your database connection:
var config = Configuration()
config.prepareDatabase = { db in
try db.usePassphrase("secret")
}
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
It is also in prepareDatabase
that you perform other SQLCipher configuration steps that must happen early in the lifetime of a SQLCipher connection. For example:
var config = Configuration()
config.prepareDatabase = { db in
try db.usePassphrase("secret")
try db.execute(sql: "PRAGMA cipher_page_size = ...")
try db.execute(sql: "PRAGMA kdf_iter = ...")
}
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
When you want to open an existing SQLCipher 3 database with SQLCipher 4, you may want to run the cipher_compatibility
pragma:
// Open an SQLCipher 3 database with SQLCipher 4
var config = Configuration()
config.prepareDatabase = { db in
try db.usePassphrase("secret")
try db.execute(sql: "PRAGMA cipher_compatibility = 3")
}
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
See SQLCipher 4.0.0 Release and Upgrading to SQLCipher 4 for more information.
You can change the passphrase of an already encrypted database.
When you use a database queue, open the database with the old passphrase, and then apply the new passphrase:
try dbQueue.write { db in
try db.changePassphrase("newSecret")
}
When you use a database pool, make sure that no concurrent read can happen by changing the passphrase within the barrierWriteWithoutTransaction
block. You must also ensure all future reads open a new database connection by calling the invalidateReadOnlyConnections
method:
try dbPool.barrierWriteWithoutTransaction { db in
try db.changePassphrase("newSecret")
dbPool.invalidateReadOnlyConnections()
}
☝️ Note: When an application wants to keep on using a database queue or pool after the passphrase has changed, it is responsible for providing the correct passphrase to the
usePassphrase
method called in the database preparation function. Consider:// WRONG: this won't work across a passphrase change let passphrase = try getPassphrase() var config = Configuration() config.prepareDatabase = { db in try db.usePassphrase(passphrase) } // CORRECT: get the latest passphrase when it is needed var config = Configuration() config.prepareDatabase = { db in let passphrase = try getPassphrase() try db.usePassphrase(passphrase) }
☝️ Note: The
DatabasePool.barrierWriteWithoutTransaction
method does not prevent database snapshots from accessing the database during the passphrase change, or after the new passphrase has been applied to the database. Those database accesses may throw errors. Applications should provide their own mechanism for invalidating open snapshots before the passphrase is changed.
☝️ Note: Instead of changing the passphrase "in place" as described here, you can also export the database in a new encrypted database that uses the new passphrase. See Exporting a Database to an Encrypted Database.
Providing a passphrase won't encrypt a clear-text database that already exists, though. SQLCipher can't do that, and you will get an error instead: SQLite error 26: file is encrypted or is not a database
.
Instead, create a new encrypted database, at a distinct location, and export the content of the existing database. This can both encrypt a clear-text database, or change the passphrase of an encrypted databaase.
The technique to do that is documented by SQLCipher.
With GRDB, it gives:
// The existing database
let existingDBQueue = try DatabaseQueue(path: "/path/to/existing.db")
// The new encrypted database, at some distinct location:
var config = Configuration()
config.prepareDatabase = { db in
try db.usePassphrase("secret")
}
let newDBQueue = try DatabaseQueue(path: "/path/to/new.db", configuration: config)
try existingDBQueue.inDatabase { db in
try db.execute(
sql: """
ATTACH DATABASE ? AS encrypted KEY ?;
SELECT sqlcipher_export('encrypted');
DETACH DATABASE encrypted;
""",
arguments: [newDBQueue.path, "secret"])
}
// Now the export is completed, and the existing database can be deleted.
It is recommended to avoid keeping the passphrase in memory longer than necessary. To do this, make sure you load the passphrase from inside the prepareDatabase
function:
// NOT RECOMMENDED: this keeps the passphrase in memory longer than necessary
let passphrase = try getPassphrase()
var config = Configuration()
config.prepareDatabase = { db in
try db.usePassphrase(passphrase)
}
// RECOMMENDED: only load the passphrase when it is needed
var config = Configuration()
config.prepareDatabase = { db in
let passphrase = try getPassphrase()
try db.usePassphrase(passphrase)
}
This technique manages the lifetime of the passphrase string. Some demanding users will want to go further, and manage the lifetime of the raw passphrase bytes. See below.
GRDB offers convenience methods for providing the database passphrases as Swift strings: usePassphrase(_:)
and changePassphrase(_:)
. Those methods don't keep the passphrase String in memory longer than necessary. But they are as secure as the standard String type: the lifetime of actual passphrase bytes in memory is not under control.
When you want to precisely manage the passphrase bytes, talk directly to SQLCipher, using its raw C functions.
For example:
import GRDB
import SQLCipher
var config = Configuration()
config.prepareDatabase = { db in
... // Carefully load passphrase bytes
let code = sqlite3_key(db.sqliteConnection, /* passphrase bytes */)
... // Carefully dispose passphrase bytes
guard code == SQLITE_OK else {
throw DatabaseError(
resultCode: ResultCode(rawValue: code),
message: db.lastErrorMessage)
}
}
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
When the passphrase is securely stored in the system keychain, your application can protect it using the kSecAttrAccessible
attribute.
Such protection prevents GRDB from creating SQLite connections when the passphrase is not available:
var config = Configuration()
config.prepareDatabase = { db in
let passphrase = try loadPassphraseFromSystemKeychain()
try db.usePassphrase(passphrase)
}
// Success if and only if the passphrase is available
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
For the same reason, database pools, which open SQLite connections on demand, may fail at any time as soon as the passphrase becomes unavailable:
// Success if and only if the passphrase is available
let dbPool = try DatabasePool(path: dbPath, configuration: config)
// May fail if passphrase has turned unavailable
try dbPool.read { ... }
// May trigger value observation failure if passphrase has turned unavailable
try dbPool.write { ... }
Because DatabasePool maintains a pool of long-lived SQLite connections, some database accesses will use an existing connection, and succeed. And some other database accesses will fail, as soon as the pool wants to open a new connection. It is impossible to predict which accesses will succeed or fail.
For the same reason, a database queue, which also maintains a long-lived SQLite connection, will remain available even after the passphrase has turned unavailable.
Applications are thus responsible for protecting database accesses when the passphrase is unavailable. To this end, they can use Data Protection. They can also destroy their instances of database queue or pool when the passphrase becomes unavailable.
You can backup (copy) a database into another.
Backups can for example help you copying an in-memory database to and from a database file when you implement NSDocument subclasses.
let source: DatabaseQueue = ... // or DatabasePool
let destination: DatabaseQueue = ... // or DatabasePool
try source.backup(to: destination)
The backup
method blocks the current thread until the destination database contains the same contents as the source database.
When the source is a database pool, concurrent writes can happen during the backup. Those writes may, or may not, be reflected in the backup, but they won't trigger any error.
SQL injection is a technique that lets an attacker nuke your database.
Here is an example of code that is vulnerable to SQL injection:
// BAD BAD BAD
let id = 1
let name = textField.text
try dbQueue.write { db in
try db.execute(sql: "UPDATE students SET name = '\(name)' WHERE id = \(id)")
}
If the user enters a funny string like Robert'; DROP TABLE students; --
, SQLite will see the following SQL, and drop your database table instead of updating a name as intended:
UPDATE students SET name = 'Robert';
DROP TABLE students;
--' WHERE id = 1
To avoid those problems, never embed raw values in your SQL queries. The only correct technique is to provide arguments to your raw SQL queries:
let name = textField.text
try dbQueue.write { db in
// Good
try db.execute(
sql: "UPDATE students SET name = ? WHERE id = ?",
arguments: [name, id])
// Just as good
try db.execute(
sql: "UPDATE students SET name = :name WHERE id = :id",
arguments: ["name": name, "id": id])
}
When you use records and the query interface, GRDB always prevents SQL injection for you:
let id = 1
let name = textField.text
try dbQueue.write { db in
if var student = try Student.fetchOne(db, key: id) {
student.name = name
try student.update(db)
}
}
GRDB can throw DatabaseError, PersistenceError, or crash your program with a fatal error.
Considering that a local database is not some JSON loaded from a remote server, GRDB focuses on trusted databases. Dealing with untrusted databases requires extra care.
DatabaseError are thrown on SQLite errors:
do {
try db.execute(
sql: "INSERT INTO pet (masterId, name) VALUES (?, ?)",
arguments: [1, "Bobby"])
} catch let error as DatabaseError {
// The SQLite error code: 19 (SQLITE_CONSTRAINT)
error.resultCode
// The extended error code: 787 (SQLITE_CONSTRAINT_FOREIGNKEY)
error.extendedResultCode
// The eventual SQLite message: FOREIGN KEY constraint failed
error.message
// The eventual erroneous SQL query
// "INSERT INTO pet (masterId, name) VALUES (?, ?)"
error.sql
// Full error description:
// "SQLite error 19 with statement `INSERT INTO pet (masterId, name)
// VALUES (?, ?)` arguments [1, "Bobby"]: FOREIGN KEY constraint failed""
error.description
}
SQLite uses codes to distinguish between various errors:
do {
try ...
} catch let error as DatabaseError where error.extendedResultCode == .SQLITE_CONSTRAINT_FOREIGNKEY {
// foreign key constraint error
} catch let error as DatabaseError where error.resultCode == .SQLITE_CONSTRAINT {
// any other constraint error
} catch let error as DatabaseError {
// any other database error
}
In the example above, error.extendedResultCode
is a precise extended result code, and error.resultCode
is a less precise primary result code. Extended result codes are refinements of primary result codes, as SQLITE_CONSTRAINT_FOREIGNKEY
is to SQLITE_CONSTRAINT
, for example. See SQLite result codes for more information.
As a convenience, extended result codes match their primary result code in a switch statement:
do {
try ...
} catch let error as DatabaseError {
switch error.extendedResultCode {
case ResultCode.SQLITE_CONSTRAINT_FOREIGNKEY:
// foreign key constraint error
case ResultCode.SQLITE_CONSTRAINT:
// any other constraint error
default:
// any other database error
}
}
⚠️ Warning: SQLite has progressively introduced extended result codes accross its versions. The SQLite release notes are unfortunately not quite clear about that: write your handling of extended result codes with care.
PersistenceError is thrown by the PersistableRecord protocol, in a single case: when the update
method could not find any row to update:
do {
try player.update(db)
} catch let PersistenceError.recordNotFound(databaseTableName: table, key: key) {
print("Key \(key) was not found in table \(table).")
}
Fatal errors notify that the program, or the database, has to be changed.
They uncover programmer errors, false assumptions, and prevent misuses. Here are a few examples:
-
The code asks for a non-optional value, when the database contains NULL:
// fatal error: could not convert NULL to String. let name: String = row["name"]
Solution: fix the contents of the database, use NOT NULL constraints, or load an optional:
let name: String? = row["name"]
-
Conversion from database value to Swift type fails:
// fatal error: could not convert "Mom’s birthday" to Date. let date: Date = row["date"] // fatal error: could not convert "" to URL. let url: URL = row["url"]
Solution: fix the contents of the database, or use DatabaseValue to handle all possible cases:
let dbValue: DatabaseValue = row["date"] if dbValue.isNull { // Handle NULL } else if let date = Date.fromDatabaseValue(dbValue) { // Handle valid date } else { // Handle invalid date }
-
The database can't guarantee that the code does what it says:
// fatal error: table player has no unique index on column email try Player.deleteOne(db, key: ["email": "arthur@example.com"])
Solution: add a unique index to the player.email column, or use the
deleteAll
method to make it clear that you may delete more than one row:try Player.filter(Column("email") == "arthur@example.com").deleteAll(db)
-
Database connections are not reentrant:
// fatal error: Database methods are not reentrant. dbQueue.write { db in dbQueue.write { db in ... } }
Solution: avoid reentrancy, and instead pass a database connection along.
Let's consider the code below:
let sql = "SELECT ..."
// Some untrusted arguments for the query
let arguments: [String: Any] = ...
let rows = try Row.fetchCursor(db, sql: sql, arguments: StatementArguments(arguments))
while let row = try rows.next() {
// Some untrusted database value:
let date: Date? = row[0]
}
It has two opportunities to throw fatal errors:
- Untrusted arguments: The dictionary may contain values that do not conform to the DatabaseValueConvertible protocol, or may miss keys required by the statement.
- Untrusted database content: The row may contain a non-null value that can't be turned into a date.
In such a situation, you can still avoid fatal errors by exposing and handling each failure point, one level down in the GRDB API:
// Untrusted arguments
if let arguments = StatementArguments(arguments) {
let statement = try db.makeSelectStatement(sql: sql)
try statement.validate(arguments: arguments)
statement.unsafeSetArguments(arguments)
var cursor = try Row.fetchCursor(statement)
while let row = try iterator.next() {
// Untrusted database content
let dbValue: DatabaseValue = row[0]
if dbValue.isNull {
// Handle NULL
if let date = Date.fromDatabaseValue(dbValue) {
// Handle valid date
} else {
// Handle invalid date
}
}
}
See prepared statements and DatabaseValue for more information.
SQLite can be configured to invoke a callback function containing an error code and a terse error message whenever anomalies occur.
This global error callback must be configured early in the lifetime of your application:
Database.logError = { (resultCode, message) in
NSLog("%@", "SQLite error \(resultCode): \(message)")
}
⚠️ Warning: Database.logError must be set before any database connection is opened. This includes the connections that your application opens with GRDB, but also connections opened by other tools, such as third-party libraries. Setting it after a connection has been opened is an SQLite misuse, and has no effect.
See The Error And Warning Log for more information.
SQLite lets you store unicode strings in the database.
However, SQLite does not provide any unicode-aware string transformations or comparisons.
The UPPER
and LOWER
built-in SQLite functions are not unicode-aware:
// "JéRôME"
try String.fetchOne(db, sql: "SELECT UPPER('Jérôme')")
GRDB extends SQLite with SQL functions that call the Swift built-in string functions capitalized
, lowercased
, uppercased
, localizedCapitalized
, localizedLowercased
and localizedUppercased
:
// "JÉRÔME"
let uppercased = DatabaseFunction.uppercase
try String.fetchOne(db, sql: "SELECT \(uppercased.name)('Jérôme')")
Those unicode-aware string functions are also readily available in the query interface:
Player.select(nameColumn.uppercased)
SQLite compares strings in many occasions: when you sort rows according to a string column, or when you use a comparison operator such as =
and <=
.
The comparison result comes from a collating function, or collation. SQLite comes with three built-in collations that do not support Unicode: binary, nocase, and rtrim.
GRDB comes with five extra collations that leverage unicode-aware comparisons based on the standard Swift String comparison functions and operators:
unicodeCompare
(uses the built-in<=
and==
Swift operators)caseInsensitiveCompare
localizedCaseInsensitiveCompare
localizedCompare
localizedStandardCompare
A collation can be applied to a table column. All comparisons involving this column will then automatically trigger the comparison function:
try db.create(table: "player") { t in
// Guarantees case-insensitive email unicity
t.column("email", .text).unique().collate(.nocase)
// Sort names in a localized case insensitive way
t.column("name", .text).collate(.localizedCaseInsensitiveCompare)
}
// Players are sorted in a localized case insensitive way:
let players = try Player.order(nameColumn).fetchAll(db)
⚠️ Warning: SQLite requires host applications to provide the definition of any collation other than binary, nocase and rtrim. When a database file has to be shared or migrated to another SQLite library of platform (such as the Android version of your application), make sure you provide a compatible collation.
If you can't or don't want to define the comparison behavior of a column (see warning above), you can still use an explicit collation in SQL requests and in the query interface:
let collation = DatabaseCollation.localizedCaseInsensitiveCompare
let players = try Player.fetchAll(db,
sql: "SELECT * FROM player ORDER BY name COLLATE \(collation.name))")
let players = try Player.order(nameColumn.collating(collation)).fetchAll(db)
You can also define your own collations:
let collation = DatabaseCollation("customCollation") { (lhs, rhs) -> NSComparisonResult in
// return the comparison of lhs and rhs strings.
}
dbQueue.add(collation: collation) // Or dbPool.add(collation: ...)
Both SQLite and GRDB use non-essential memory that help them perform better.
You can reclaim this memory with the releaseMemory
method:
// Release as much memory as possible.
dbQueue.releaseMemory()
dbPool.releaseMemory()
This method blocks the current thread until all current database accesses are completed, and the memory collected.
The iOS operating system likes applications that do not consume much memory.
Database queues and pools can call the releaseMemory
method for you, when application receives memory warnings, and when application enters background: call the setupMemoryManagement
method after creating the queue or pool instance:
let dbQueue = try DatabaseQueue(...)
dbQueue.setupMemoryManagement(in: UIApplication.shared)
Data Protection lets you protect files so that they are encrypted and unavailable until the device is unlocked.
Data protection can be enabled globally for all files created by an application.
You can also explicitly protect a database, by configuring its enclosing directory. This will not only protect the database file, but also all temporary files created by SQLite (including the persistent .shm
and .wal
files created by database pools).
For example, to explicitly use complete protection:
// Paths
let fileManager = FileManager.default
let directoryURL = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("database", isDirectory: true)
let databaseURL = directoryURL.appendingPathComponent("db.sqlite")
// Create directory if needed
var isDirectory: ObjCBool = false
if !fileManager.fileExists(atPath: directoryURL.path, isDirectory: &isDirectory) {
try fileManager.createDirectory(atPath: directoryURL.path, withIntermediateDirectories: false)
} else if !isDirectory.boolValue {
throw NSError(domain: NSCocoaErrorDomain, code: NSFileWriteFileExistsError, userInfo: nil)
}
// Enable data protection
try fileManager.setAttributes([.protectionKey : FileProtectionType.complete], ofItemAtPath: directoryURL.path)
// Open database
let dbQueue = try DatabaseQueue(path: databaseURL.path)
When a database is protected, an application that runs in the background on a locked device won't be able to read or write from it. Instead, it will get DatabaseError with code SQLITE_IOERR
(10) "disk I/O error", or SQLITE_AUTH
(23) "not authorized".
You can catch those errors and wait for UIApplicationDelegate.applicationProtectedDataDidBecomeAvailable(_:) or UIApplicationProtectedDataDidBecomeAvailable notification in order to retry the failed database operation.
- Guarantees and Rules
- Differences between Database Queues and Pools
- Advanced DatabasePool
- Database Snapshots
- DatabaseWriter and DatabaseReader Protocols
- Asynchronous APIs
- Unsafe Concurrency APIs
- Dealing with External Connections
GRDB ships with three concurrency modes:
- DatabaseQueue opens a single database connection, and serializes all database accesses.
- DatabasePool manages a pool of several database connections, and allows concurrent reads and writes.
- DatabaseSnapshot opens a single read-only database connection on an unchanging database content, and (currently) serializes all database accesses
All foster application safety: regardless of the concurrency mode you choose, GRDB provides you with the same guarantees, as long as you follow three rules.
-
Guarantee 1: writes are always serialized. At every moment, there is no more than a single thread that is writing into the database.
Database writes always happen in a unique serial dispatch queue, named the writer protected dispatch queue.
-
Guarantee 2: reads are always isolated. This means that they are guaranteed an immutable view of the database, and that you can perform subsequent fetches without fearing eventual concurrent writes to mess with your application logic:
try dbPool.read { db in // or dbQueue.read // Guaranteed to be equal let count1 = try Player.fetchCount(db) let count2 = try Player.fetchCount(db) }
In database queues, reads happen in the same protected dispatch queue as writes: isolation is just a consequence of the serialization of database accesses
Database pools and snapshots both use the "snapshot isolation" made possible by SQLite's WAL mode (see Isolation In SQLite).
-
Guarantee 3: requests don't fail, unless a database constraint violation, a programmer mistake, or a very low-level issue such as a disk error or an unreadable database file. GRDB grants correct use of SQLite, and particularly avoids locking errors and other SQLite misuses.
Those guarantees hold as long as you follow three rules:
-
☝️ Rule 1: Have a unique instance of DatabaseQueue or DatabasePool connected to any database file.
This means that opening a new connection each time you access the database is a bad idea. Do share a single connection instead.
See the Demo Application for a sample app that sets up a single database queue that is available throughout the application.
If there are several instances of database queues or pools that write in the same database, a multi-threaded application will eventually face "database is locked" errors. See Dealing with External Connections.
// SAFE CONCURRENCY func fetchCurrentUser(_ db: Database) throws -> User? { return try User.fetchOne(db) } // dbQueue is a singleton defined somewhere in your app let user = try dbQueue.read { db in // or dbPool.read try fetchCurrentUser(db) } // UNSAFE CONCURRENCY // This method fails when some other thread is currently writing into // the database. func currentUser() throws -> User? { let dbQueue = try DatabaseQueue(...) return try dbQueue.read { db in try User.fetchOne(db) } } let user = try currentUser()
-
☝️ Rule 2: Group related statements within a single call to a DatabaseQueue or DatabasePool database access method (or use snapshots).
Database access methods isolate your groups of related statements against eventual database updates performed by other threads, and guarantee a consistent view of the database. This isolation is only guaranteed inside the closure argument of those methods. Two consecutive calls do not guarantee isolation:
// SAFE CONCURRENCY try dbPool.read { db in // or dbQueue.read // Guaranteed to be equal: let count1 = try Place.fetchCount(db) let count2 = try Place.fetchCount(db) } // UNSAFE CONCURRENCY // Those two values may be different because some other thread may have // modified the database between the two blocks: let count1 = try dbPool.read { db in try Place.fetchCount(db) } let count2 = try dbPool.read { db in try Place.fetchCount(db) }
In the same vein, when you fetch values that depends on some database updates, group them:
// SAFE CONCURRENCY try dbPool.write { db in // The count is guaranteed to be non-zero try Place(...).insert(db) let count = try Place.fetchCount(db) } // UNSAFE CONCURRENCY // The count may be zero because some other thread may have performed // a deletion between the two blocks: try dbPool.write { db in try Place(...).insert(db) } let count = try dbPool.read { db in try Place.fetchCount(db) }
On that last example, see Advanced DatabasePool if you look after extra performance.
-
☝️ Rule 3: When you perform several modifications of the database that temporarily put the database in an inconsistent state, make sure those modifications are grouped within a transaction.
// SAFE CONCURRENCY try dbPool.write { db in // or dbQueue.write try Credit(destinationAccount, amount).insert(db) try Debit(sourceAccount, amount).insert(db) } // SAFE CONCURRENCY try dbPool.writeInTransaction { db in // or dbQueue.inTransaction try Credit(destinationAccount, amount).insert(db) try Debit(sourceAccount, amount).insert(db) return .commit } // UNSAFE CONCURRENCY try dbPool.writeWithoutTransaction { db in try Credit(destinationAccount, amount).insert(db) // <- Concurrent dbPool.read sees a partial db update here try Debit(sourceAccount, amount).insert(db) }
Without transaction,
DatabasePool.read { ... }
may see the first statement, but not the second, and access a database where the balance of accounts is not zero. A highly bug-prone situation.So do use transactions in order to guarantee database consistency accross your application threads: that's what they are made for.
Despite the common guarantees and rules shared by database queues and pools, those two database accessors don't have the same behavior.
Database queues serialize all database accesses, reads, and writes. There is never more than one thread that uses the database. In the image below, we see how three threads can see the database as time passes:
Database pools also serialize all writes. But they allow concurrent reads and writes, and isolate reads so that they don't see changes performed by other threads. This gives a very different picture:
See how, with database pools, two reads can see different database states at the same time.
For more information about database pools, grab information about SQLite WAL mode and snapshot isolation. See Database Observation when you look after automatic notifications of database changes.
Database pools are very concurrent, since all reads can run in parallel, and can even run during write operations. But writes are still serialized: at any given point in time, there is no more than a single thread that is writing into the database.
When your application modifies the database, and then reads some value that depends on those modifications, you may want to avoid locking the writer queue longer than necessary:
try dbPool.write { db in
// Increment the number of players
try Player(...).insert(db)
// Read the number of players. The writer queue is still locked :-(
let count = try Player.fetchCount(db)
}
A wrong solution is to chain a write then a read, as below. Don't do that, because another thread may modify the database in between, and make the read unreliable:
// WRONG
try dbPool.write { db in
// Increment the number of players
try Player(...).insert(db)
}
// <- other threads can write in the database here
try dbPool.read { db in
// Read some random value :-(
let count = try Player.fetchCount(db)
}
The correct solution is the concurrentRead
method, which must be called from within a write block, outside of any transaction.
concurrentRead
returns a future value which you consume on any dispatch queue, with the wait()
method:
// CORRECT
let futureCount: DatabaseFuture<Int> = try dbPool.writeWithoutTransaction { db in
// increment the number of players
try Player(...).insert(db)
// <- not in a transaction here
let futureCount = dbPool.concurrentRead { db
return try Player.fetchCount(db)
}
return futureCount
}
// <- The writer queue has been unlocked :-)
// Wait for the player count
let count: Int = try futureCount.wait()
concurrentRead
blocks until it can guarantee its closure argument an isolated access to the last committed state of the database. It then asynchronously executes the closure.
The closure can run concurrently with eventual updates performed after concurrentRead
: those updates won't be visible from within the closure. In the example below, the number of players is guaranteed to be non-zero, even though it is fetched concurrently with the player deletion:
try dbPool.writeWithoutTransaction { db in
// Increment the number of players
try Player(...).insert(db)
let futureCount = dbPool.concurrentRead { db
// Guaranteed to be non-zero
return try Player.fetchCount(db)
}
try Player.deleteAll(db)
}
Transaction Observers can also use concurrentRead
in their databaseDidCommit
method in order to process database changes without blocking other threads that want to write into the database.
try dbPool.barrierWriteWithoutTransaction { db in
// Exclusive database access
}
The barrier write guarantees exclusive access to the database: the method blocks until all concurrent database accesses are completed, reads and writes, and postpones all other accesses until it completes.
There is a known limitation: reads performed by database snapshots are out of scope, and may run concurrently with the barrier.
Database pool can take snapshots. A database snapshot sees an unchanging database content, as it existed at the moment it was created.
"Unchanging" means that a snapshot never sees any database modifications during all its lifetime. And yet it doesn't prevent database updates. This "magic" is made possible by SQLite's WAL mode (see Isolation In SQLite).
You create snapshots from a database pool:
let snapshot = try dbPool.makeSnapshot()
You can create as many snapshots as you need, regardless of the maximum number of readers in the pool. A snapshot database connection is closed when the snapshot gets deallocated.
A snapshot can be used from any thread. Its read
methods is synchronous, and blocks the current thread until your database statements are executed:
// Read values:
try snapshot.read { db in
let players = try Player.fetchAll(db)
let playerCount = try Player.fetchCount(db)
}
// Extract a value from the database:
let playerCount = try snapshot.read { db in
try Player.fetchCount(db)
}
When you want to control the latest committed changes seen by a snapshot, create the snapshot from the pool's writer protected dispatch queue, outside of any transaction:
let snapshot1 = try dbPool.writeWithoutTransaction { db -> DatabaseSnapshot in
try db.inTransaction {
// delete all players
try Player.deleteAll()
return .commit
}
// <- not in a transaction here
return dbPool.makeSnapshot()
}
// <- Other threads may modify the database here
let snapshot2 = try dbPool.makeSnapshot()
try snapshot1.read { db in
// Guaranteed to be zero
try Player.fetchCount(db)
}
try snapshot2.read { db in
// Could be anything
try Player.fetchCount(db)
}
☝️ Note: snapshots currently serialize all database accesses. In the future, snapshots may allow concurrent reads.
Both DatabaseQueue and DatabasePool adopt the DatabaseReader and DatabaseWriter protocols. DatabaseSnapshot adopts DatabaseReader only.
These protocols provide a unified API that let you write generic code that targets all concurrency modes. They fuel, for example:
Only five types adopt those protocols: DatabaseQueue, DatabasePool, DatabaseSnapshot, AnyDatabaseReader, and AnyDatabaseWriter. Expanding this set is not supported: any future GRDB release may break your custom writers and readers, without notice.
DatabaseReader and DatabaseWriter provide the smallest common guarantees: they don't erase the differences between queues, pools, and snapshots. See for example Differences between Database Queues and Pools.
However, you can prevent some parts of your application from writing in the database by giving them a DatabaseReader:
// This class can read in the database, but can't write into it.
class MyReadOnlyComponent {
let reader: DatabaseReader
init(reader: DatabaseReader) {
self.reader = reader
}
}
let dbQueue: DatabaseQueue = ...
let component = MyReadOnlyComponent(reader: dbQueue)
☝️ Note: DatabaseReader is not a secure way to prevent an application component from writing in the database, because write access is just a cast away:
if let dbQueue = reader as? DatabaseQueue { try dbQueue.write { ... } }
Database queues, pools, snapshots, as well as their common protocols DatabaseReader
and DatabaseWriter
provide asynchronous database access methods.
The asyncRead
method can be used from any thread. It submits your database statements for asynchronous execution on a protected dispatch queue:
reader.asyncRead { (result: Result<Database>) in
try {
let db = try result.get()
let players = try Player.fetchAll(db)
} catch {
// handle error
}
}
The argument function accepts a standard Result<Database, Error>
which may contain a failure if it was impossible to start a reading access to the database.
Any attempt at modifying the database throws an error.
When you use a database queue or a database snapshot, the read has to wait for any eventual concurrent database access performed by this queue or snapshot to complete.
When you use a database pool, reads are generally non-blocking, unless the maximum number of concurrent reads has been reached. In this case, a read has to wait for another read to complete. That maximum number can be configured.
☝️ Note: because it uses the standard
Result
type,asyncRead
is only available with a Swift 5+ compiler, starting Xcode 10.2.
The asyncWrite
method can be used from any thread. It submits your database statements for asynchronous execution on a protected dispatch queue, wrapped inside a database transaction:
writer.asyncWrite({ (db: Database) in
try Player(...).insert(db)
}, completion: { (db: Database, result: Result<Void, Error>) in
switch result {
case let .success:
// handle transaction success
case let .failure(error):
// handle transaction error
}
})
asyncWrite
accepts two function arguments. The first one executes your database updates. The second one is a completion function which accepts a database connection and the result of the asynchronous transaction.
On the first unhandled error during database updates, all changes are reverted, the whole transaction is rollbacked, and the error is passed to the completion function.
When the transaction completes successfully, the result of the first function is contained in the standard Result
passed to the completion function:
writer.asyncWrite({ (db: Database) -> Int in
try Player(...).insert(db)
return try Player.fetchCount(db)
}, completion: { (db: Database, result: Result<Int, Error>) in
switch result {
case let .success(newPlayerCount):
print("new player count: \(newPlayerCount)")
case let .failure(error):
// handle transaction error
}
})
The scheduled asynchronous transaction has to wait for any eventual concurrent database write to complete before it can start.
☝️ Note: because it uses the standard
Result
type,asyncWrite
is only available with a Swift 5+ compiler, starting Xcode 10.2.
The asyncWriteWithoutTransaction
method can be used from any thread. It submits your database statements for asynchronous execution on a protected dispatch queue, outside of any transaction:
writer.asyncWriteWithoutTransaction { (db: Database) in
try {
try Player(...).insert(db)
} catch {
// handle error
}
}
Writing outside of any transaction is dangerous. You should almost always prefer the asyncWrite
method described above. Please see Transactions and Savepoints for more information.
The scheduled asynchronous updates have to wait for any eventual concurrent database write to complete before they can start.
The asyncConcurrentRead
method is available on database pools only. It is the asynchronous equivalent of the concurrentRead
described in the Advanced DatabasePool chapter.
It must be called from a writing dispatch queue, outside of any transaction. You'll get a fatal error otherwise.
The closure argument is guaranteed to see the database in the last committed state at the moment this method is called. Eventual concurrent database updates are not visible inside the block.
asyncConcurrentRead
blocks until it can guarantee its closure argument an isolated access to the last committed state of the database. It then asynchronously executes the closure.
In the example below, the number of players is fetched concurrently with the player insertion. Yet the future is guaranteed to return zero:
try writer.asyncWriteWithoutTransaction { db in
do {
// Delete all players
try Player.deleteAll()
// <- not in a transaction here
// Count players concurrently
writer.asyncConcurrentRead { (result: Result<Database>) in
try {
let db = try result.get()
// Guaranteed to be zero
let count = try Player.fetchCount()
} catch {
// handle error
}
}
// Insert a player
try Player(...).insert(db)
} catch {
// handle error
}
}
☝️ Note: because it uses the standard
Result
type,asyncWriteWithoutTransaction
is only available with a Swift 5+ compiler, starting Xcode 10.2.
Database queues, pools, snapshots, as well as their common protocols DatabaseReader
and DatabaseWriter
provide unsafe database access methods. Unsafe APIs lift concurrency guarantees, and allow advanced yet unsafe patterns.
-
unsafeRead
The
unsafeRead
method is synchronous, and blocks the current thread until your database statements are executed in a protected dispatch queue. GRDB does just the bare minimum to provide a database connection that can read.When used on a database pool, reads are no longer isolated:
dbPool.unsafeRead { db in // Those two values may be different because some other thread // may have inserted or deleted a player between the two requests: let count1 = try Player.fetchCount(db) let count2 = try Player.fetchCount(db) }
When used on a database queue, the closure argument is allowed to write in the database.
-
unsafeReentrantRead
The
unsafeReentrantRead
behaves just asunsafeRead
(see above), and allows reentrant calls:dbPool.read { db1 in // No "Database methods are not reentrant" fatal error: dbPool.unsafeReentrantRead { db2 in dbPool.unsafeReentrantRead { db3 in ... } } }
Reentrant database accesses make it very easy to break the second safety rule, which says: "group related statements within a single call to a DatabaseQueue or DatabasePool database access method.". Using a reentrant method is pretty much likely the sign of a wrong application architecture that needs refactoring.
There is a single valid use case for reentrant methods, which is when you are unable to control database access scheduling.
-
unsafeReentrantWrite
The
unsafeReentrantWrite
method is synchronous, and blocks the current thread until your database statements are executed in a protected dispatch queue. Writes are serialized: eventual concurrent database updates are postponed until the block has executed.Reentrant calls are allowed:
dbQueue.write { db1 in // No "Database methods are not reentrant" fatal error: dbQueue.unsafeReentrantWrite { db2 in dbQueue.unsafeReentrantWrite { db3 in ... } } }
Reentrant database accesses make it very easy to break the second safety rule, which says: "group related statements within a single call to a DatabaseQueue or DatabasePool database access method.". Using a reentrant method is pretty much likely the sign of a wrong application architecture that needs refactoring.
There is a single valid use case for reentrant methods, which is when you are unable to control database access scheduling.
The first rule of GRDB is:
- Rule 1: Have a unique instance of DatabaseQueue or DatabasePool connected to any database file.
This means that dealing with external connections is not a focus of GRDB. Guarantees of GRDB may or may not hold as soon as some external connection modifies a database.
If you absolutely need multiple connections, then:
- Reconsider your position
- Read about isolation in SQLite
- Learn about locks and transactions
- Become a master of the WAL mode
- Prepare to setup a busy handler with Configuration.busyMode
- Ask questions
GRDB is a reasonably fast library, and can deliver quite efficient SQLite access. See Comparing the Performances of Swift SQLite libraries for an overview.
You'll find below general advice when you do look after performance:
- Focus
- Know your platform
- Use transactions
- Don't do useless work
- Learn about SQL strengths and weaknesses
- Avoid strings & dictionaries
You don't know which part of your program needs improvement until you have run a benchmarking tool.
Don't make any assumption, avoid optimizing code too early, and use Instruments.
If your application processes a huge JSON file and inserts thousands of rows in the database right from the main thread, it will quite likely become unresponsive, and provide a sub-quality user experience.
If not done yet, read the Concurrency Programming Guide and learn how to perform heavy computations without blocking your application.
Most GRBD APIs are synchronous. Spawning them into parallel queues is as easy as:
DispatchQueue.global().async {
dbQueue.write { db in
// Perform database work
}
DispatchQueue.main.async {
// update your user interface
}
}
Performing multiple updates to the database is much faster when executed inside a transaction. This is because a transaction allows SQLite to postpone writing changes to disk until the final commit:
// Inefficient
try dbQueue.inDatabase { db in // or dbPool.writeWithoutTransaction
for player in players {
try player.insert(db)
}
}
// Efficient
try dbQueue.write { db in // or dbPool.write
for player in players {
try player.insert(db)
}
}
// Efficient
try dbQueue.inTransaction { db in // or dbPool.writeInTransaction
for player in players {
try player.insert(db)
}
return .commit
}
Obviously, no code is faster than any code.
Don't fetch columns you don't use
// SELECT * FROM player
try Player.fetchAll(db)
// SELECT id, name FROM player
try Player.select(idColumn, nameColumn).fetchAll(db)
If your Player type can't be built without other columns (it has non-optional properties for other columns), do define and use a different type.
See Columns Selected by a Request for more information.
Don't fetch rows you don't use
Use fetchOne when you need a single value, and otherwise limit your queries at the database level:
// Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)
// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)
Don't copy values unless necessary
Particularly: the Array returned by the fetchAll
method, and the cursor returned by fetchCursor
aren't the same:
fetchAll
copies all values from the database into memory, when fetchCursor
iterates database results as they are generated by SQLite, taking profit from SQLite efficiency.
You should only load arrays if you need to keep them for later use (such as iterating their contents in the main thread). Otherwise, use fetchCursor
.
See fetching methods for more information about fetchAll
and fetchCursor
. See also the Row.dataNoCopy method.
Don't update rows unless necessary
An UPDATE statement is costly: SQLite has to look for the updated row, update values, and write changes to disk.
When the overwritten values are the same as the existing ones, it's thus better to avoid performing the UPDATE statement:.
if player.hasDatabaseChanges {
try player.update(db)
}
See Record Comparison for more information.
Consider a simple use case: your store application has to display a list of authors with the number of available books:
- J. M. Coetzee (6)
- Herman Melville (1)
- Alice Munro (3)
- Kim Stanley Robinson (7)
- Oliver Sacks (4)
The following code is inefficient. It is an example of the N+1 problem, because it performs one query to load the authors, and then N queries, as many as there are authors. This turns very inefficient as the number of authors grows:
// SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
// SELECT COUNT(*) FROM book WHERE authorId = ...
author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}
Instead, perform a single query:
let sql = """
SELECT author.*, COUNT(book.id) AS bookCount
FROM author
LEFT JOIN book ON book.authorId = author.id
GROUP BY author.id
"""
let authors = try Author.fetchAll(db, sql: sql)
In the example above, consider extending your Author with an extra bookCount property, or define and use a different type.
Generally, define indexes on your database tables, and use SQLite's efficient query planning:
The String and Dictionary Swift types are better avoided when you look for the best performance.
Now GRDB records, for your convenience, do use strings and dictionaries:
class Player : Record {
var id: Int64?
var name: String
var email: String
required init(_ row: Row) {
id = row["id"] // String
name = row["name"] // String
email = row["email"] // String
super.init()
}
override func encode(to container: inout PersistenceContainer) {
container["id"] = id // String
container["name"] = name // String
container["email"] = email // String
}
}
When convenience hurts performance, you can still use records, but you have better avoiding their string and dictionary-based methods.
For example, when fetching values, prefer loading columns by index:
// Strings & dictionaries
let players = try Player.fetchAll(db)
// Column indexes
// SELECT id, name, email FROM player
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
let id: Int64 = row[0]
let name: String = row[1]
let email: String = row[2]
let player = Player(id: id, name: name, email: email)
...
}
When inserting values, use reusable prepared statements, and set statements values with an array:
// Strings & dictionaries
for player in players {
try player.insert(db)
}
// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
// Only use the unsafe arguments setter if you are sure that you provide
// all statement arguments. A mistake can store unexpected values in
// the database.
insertStatement.unsafeSetArguments([player.name, player.email])
try insertStatement.execute()
}
- How do I create a database in my application?
- How do I open a database stored as a resource of my application?
- How do I close a database connection?
- How do I print a request as SQL?
- Generic parameter 'T' could not be inferred
- SQLite error 10 "disk I/O error", SQLite error 23 "not authorized"
- SQLite error 21 "wrong number of statement arguments" with LIKE queries
- What Are Experimental Features?
This question assumes that your application has to create a new database from scratch. If your app has to open an existing database that is embedded inside your application as a resource, see How do I open a database stored as a resource of my application? instead.
The database has to be stored in a valid place where it can be created and modified. For example, in the Application Support directory:
let databaseURL = try FileManager.default
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)
If your application does not need to modify the database, open a read-only connection to your resource:
var config = Configuration()
config.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
If the application should modify the database, you need to copy it to a place where it can be modified. For example, in the Application Support directory. Only then, open a connection:
let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)
Database connections are managed by database queues and pools. A connection is closed when its database queue or pool is deallocated, and all usages of this connection are completed.
Database accesses that run in background threads postpone the closing of connections.
When you want to debug a request that does not deliver the expected results, you may want to print the SQL that is actually executed.
You can turn your request into a SQLRequest
instance:
try dbQueue.read { db in
let request = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")
let sqlRequest = try SQLRequest(db, request: request)
print(sqlRequest.sql)
// Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
print(sqlRequest.arguments)
// Prints ["Burgundy"]
}
Another option is to setup a tracing function that will print out all SQL requests executed by your application. You provide the trace function when you connect to the database:
var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)
try dbQueue.read { db in
let wines = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")
.fetchAll(db)
// Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}
☝️ Note: the generated SQL may change between GRDB releases, without notice: don't have your application rely on any specific SQL output.
You may get this error when using the read
and write
methods of database queues and pools:
// Generic parameter 'T' could not be inferred
let string = try dbQueue.read { db in
let result = try String.fetchOne(db, ...)
return result
}
This is a limitation of the Swift compiler.
The general workaround is to explicitly declare the type of the closure result:
// General Workaround
let string = try dbQueue.read { db -> String? in
let result = try String.fetchOne(db, ...)
return result
}
You can also, when possible, write a single-line closure:
// Single-line closure workaround:
let string = try dbQueue.read { db in
try String.fetchOne(db, ...)
}
Those errors may be the sign that SQLite can't access the database due to data protection.
When your application should be able to run in the background on a locked device, it has to catch this error, and, for example, wait for UIApplicationDelegate.applicationProtectedDataDidBecomeAvailable(_:) or UIApplicationProtectedDataDidBecomeAvailable notification and retry the failed database operation.
do {
try ...
} catch let error as DatabaseError where
error.resultCode == .SQLITE_IOERR ||
error.resultCode == .SQLITE_AUTH
{
// Handle possible data protection error
}
This error can also be prevented altogether by using a more relaxed file protection.
You may get the error "wrong number of statement arguments" when executing a LIKE query similar to:
let name = textField.text
let players = try dbQueue.read { db in
try Player.fetchAll(db, sql: "SELECT * FROM player WHERE name LIKE '%?%'", arguments: [name])
}
The problem lies in the '%?%'
pattern.
SQLite only interprets ?
as a parameter when it is a placeholder for a whole value (int, double, string, blob, null). In this incorrect query, ?
is just a character in the '%?%'
string: it is not a query parameter, and is not processed in any way. See https://www.sqlite.org/lang_expr.html#varparam for more information about SQLite parameters.
To fix the error, you can feed the request with the pattern itself, instead of the name:
let name = textField.text
let players: [Player] = try dbQueue.read { db in
let pattern = "%\(name)%"
return try Player.fetchAll(db, sql: "SELECT * FROM player WHERE name LIKE ?", arguments: [pattern])
}
Since GRDB 1.0, all backwards compatibility guarantees of semantic versioning apply: no breaking change will happen until the next major version of the library.
There is an exception, though: experimental features, marked with the "🔥 EXPERIMENTAL" badge. Those are advanced features that are too young, or lack user feedback. They are not stabilized yet.
Those experimental features are not protected by semantic versioning, and may break between two minor releases of the library. To help them becoming stable, your feedback is greatly appreciated.
- The Documentation is full of GRDB snippets.
- Demo Application: A sample iOS application.
- WWDC Companion: A sample iOS application.
- Check
GRDB.xcworkspace
: it contains GRDB-enabled playgrounds to play with. - How to synchronize a database table with a JSON payload: JSONSynchronization.playground
Thanks
- Pierlis, where we write great software.
- @alextrob, @bellebethcooper, @bfad, @cfilipov, @charlesmchen-signal, @Chiliec, @chrisballinger, @darrenclark, @davidkraus, @fpillet, @gusrota, @hartbit, @kdubb, @kluufger, @KyleLeneau, @Marus, @michaelkirk-signal, @pakko972, @peter-ss, @pierlo, @pocketpixels, @robcas3, @runhum, @schveiguy, @SD10, @sobri909, @sroddy, @swiftlyfalling, @Timac, @valexa, and @zmeyc for their contributions, help, and feedback on GRDB.
- @aymerick and @kali because SQL.
- ccgus/fmdb for its excellency.
This chapter has been renamed Record Comparison.
This chapter has moved.
This protocol has been renamed PersistableRecord in GRDB 3.0.
This protocol has been renamed FetchableRecord in GRDB 3.0.
This protocol has been renamed TableRecord in GRDB 3.0.
This chapter has been renamed Beyond FetchableRecord.