BigCsvReader
Package bigcscvreader offers a multi-threaded approach for reading a large CSV file in order to improve the time of reading and processing it.
It spawns multiple goroutines, each reading a piece of the file.
Read rows are put into channels equal in number to the spawned goroutines, in this way also the processing of those rows can be parallelized.
Benchmarks
go test -timeout=20m -benchmem -benchtime=2x -bench=.
goos: darwin
goarch: amd64
pkg: github.com/actforgood/bigcsvreader
cpu: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
Benchmark50000Rows_50Mb_withBigCsvReader-8 2 8030321166 ns/op 61739968 B/op 100219 allocs/op
Benchmark50000Rows_50Mb_withGoCsvReaderReadAll-8 2 65555449418 ns/op 67438460 B/op 100040 allocs/op
Benchmark50000Rows_50Mb_withGoCsvReaderReadOneByOneAndReuseRecord-8 2 66464272707 ns/op 57605856 B/op 50014 allocs/op
Benchmarks are made with a file of ~50Mb in size, also a fake processing of any given row of 1ms was taken into consideration.
bigcsvreader was launched with 8 goroutines.
Other benchmarks are made using directly the encoding/csv go package.
As you can see, bigcsvreader reads and processes all rows in ~8s.
Go standard csv package reads and processes all rows in ~65s.
ReadAll API has the disadvantage of keeping all rows into memory.
Read rows one by one API with ReuseRecord flag set has the advantage of fewer allocations, but has the cost of sequentially reading rows.
Bellow are some process stats captured with unix TOP command while running each benchmark.
| Bench | %CPU | MEM |
|---|---|---|
| Benchmark50000Rows_50Mb_withBigCsvReader | 21.6 | 8156K |
| Benchmark50000Rows_50Mb_withGoCsvReaderReadAll | 5.3 | 67M |
| Benchmark50000Rows_50Mb_withGoCsvReaderReadOneByOneAndReuseRecord | 10.1 | 5704K |
License
This package is released under a MIT license. See LICENSE.