xiaodin1 / mlsql

The Programming Language Designed For Big Data and AI

• Kolo-Lang
  • Kolo Code Example
• Official WebSite
• VSCode Extension（MacOS、Linux）
• Docker Sandbox
  • Pulling Sandbox Docker Image
  • Start Container
• Download Kolo
• Building a Distribution
  • Prerequisites
  • Downloading Source Code
  • Building Spark 2.4.3 Bundle
  • Building Spark 3.1.1 Bundle
  • Building without Chinese Analyzer
  • Building with Aliyun OSS Support
• Deploying
• How to contribute to Kolo-Lang
• Contributors
• WeChat Group

Kolo-Lang

Kolo (former MLSQL) is a low-code open-source programming language for data pipeline, analytics and AI in cloud native way.

Deisgn protocol: Everything is a table. Kolo is a SQL-like language, to simplify data pipeline, analytics and AI, combined with built-in algorithms and plugins.

We believe that everything is a table, a simple and powerful SQL-like language can significantly reduce human efforts of data development without switching different tools.

Kolo Code Example

load hive.`raw.stripe_discounts` as discounts;
load hive.`raw.stripe_invoice_items` as invoice_items;

select
        invoice_items.*,
        case
            when discounts.discount_type = 'percent'
                then amount * (1.0 - discounts.discount_value::float / 100)
            else amount - discounts.discount_value
        end as discounted_amount

    from invoice_items

    left outer join discounts
        on invoice_items.customer_id = discounts.customer_id
        and invoice_items.invoice_date > discounts.discount_start
        and (invoice_items.invoice_date < discounts.discount_end
             or discounts.discount_end is null)
as joined;



select

        id,
        invoice_id,
        customer_id,
        coalesce(discounted_amount, amount) as discounted_amount,
        currency,
        description,
        created_at,
        deleted_at

    from joined
as final;



set allColumns = "all,wow";

!if ''' split(:allColumns,",")[0] == "all" ''';
   select * from final as final2;
!else;
   select id,invoice from final as final2;
!fi;

select * from final2 as output;

Official WebSite

https://mlsql.tech [New official website is coming soon]

VSCode Extension（MacOS、Linux）

kolo-lang-vscode-extension

More document about kolo-lang vscode extension（Chinese version）

Docker Sandbox

Pulling Sandbox Docker Image

For Spark 2.4.3 bundle:

docker pull techmlsql/mlsql-sandbox:2.4.3-2.1.0

For Spark 3.1.1 bundle：

docker pull techmlsql/mlsql-sandbox:3.1.1-2.1.0

Start Container

docker run -d \
-p 3306:3306 \
-p 9002:9002 \
-e MYSQL_ROOT_PASSWORD=mlsql \
--name mlsql-sandbox-2.4.3-2.1.0 \
techmlsql/mlsql-sandbox:2.4.3-2.1.0

1. Launch a browser, enter http://localhost:9002, and "Setup MLSQL Console in 2 Steps" page shows.
2. Enter admin username and password, click "Go" button.
3. Enter spark for "Engine Name", http://localhost:9003 for "Engine Url", leave "Access Token" blank, click "Go" button.
4. Click "Go to Console Page", and you're all set to play with mlsql.

Download Kolo

• The latest stable version is release-2.1.0
• You can download from Kolo Website
• Spark 2.4.3/3.1.1 have been tested

Naming Convention

mlsql-engine_${spark_major_version}-${mlsql_version}.tgz

## Pre-built for Spark 2.4.3
mlsql-engine_2.4-2.1.0.tar.gz

## Pre-built for Spark 3.1.1
mlsql-engine_3.0-2.1.0.tar.gz

Building a Distribution

Prerequisites

• JDK 8+
• Maven
• Linux or MacOS

Downloading Source Code

## Clone the code base
git clone https://github.com/byzer-org/kolo-lang.git.
cd mlsql

Building Spark 2.4.3 Bundle

export MLSQL_SPARK_VERSION=2.4
./dev/make-distribution.sh

Building Spark 3.1.1 Bundle

export MLSQL_SPARK_VERSION=3.0
./dev/make-distribution.sh

Building without Chinese Analyzer

## Chinese analyzer is enabled by default.
export ENABLE_CHINESE_ANALYZER=false
./dev/make-distribution.sh <spark_version>

Building with Aliyun OSS Support

## Aliyun OSS support is disabled by default
export OSS_ENABLE=true
./dev/make-distribution.sh <spark_version>

Deploying

1. Download or build a distribution
2. Install Spark and set environment variable SPARK_HOME, make sure Spark version matches that of MLSQL
3. Deploy tgz

• Set environment variable MLSQL_HOME
• Copy distribution tar ball over and untar it

4.Start Kolo in local mode

cd $MLSQL_HOME
## Run process in background
nohup ./bin/start-local.sh 2>&1 > ./local_mlsql.log &

5. Open a browser and type in http://localhost:9003, have fun.

Directory structure

|-- mlsql
    |-- bin        
    |-- conf       
    |-- data       
    |-- examples   
    |-- libs       
    |-- README.md  
    |-- LICENSE
    |-- RELEASE

How to contribute to Kolo-Lang

If you are planning to contribute to this repository, please create an issue at our Issue page even if the topic is not related to source code itself (e.g., documentation, new idea and proposal).

This is an active open source project for everyone, and we are always open to people who want to use this system or contribute to it.

Contributors

• Zhu William/allwefantasy#gmail.com
• Chen Fu/cfmcgrady#gmail.com
• Geng Yifei/pigeongeng#gmail.com
• wanp1989/wanp1989#126.com
• chenliang613
• RebieKong
• CoderOverflow
• ghsuzzy
• xubo245
• zhuohuwu0603
• liyubin117
• 9bbword
• Slash-Wong/523935329#qq.com
• anan0120/158989903#qq.com

WeChat Group

扫码添加K小助微信号，添加成功后，发送 mlsql 这5个英文字母进群。