Golangs built in map sharded!

For better concurrency.

The whole point of this project was to assist me in a scenario where map access I/O became a bottleneck.

( godoc: https://godoc.org/github.com/zutto/shardedmap )

1. Installation

go get github.com/zutto/shardedmap

2. Usage

Intialization is easy as:

shardmap := shardedmap.NewShardMap(24)

Wondering what that 24 is? It's the amount of 'shards' shardedmap should initialize. General rule of thumb: Lower your I/O is, the less shards you need. Each shard holds their own mutex lock for rwd access.

Adding item to shardmap

type demo struct {
   str1 string
   str2 string
}

var data interface{} = demo{"Hello", "World"}

shardmap.Set("I am a string key", &data)

Input data type is interface{}, key datatype is always a string.

Reading items from shardmap

retrievedData := shardmap.Get("I am a string key")

Deleting items from shardmap

shardmap.Delete("I am a string key")

for more documentation, please look at godoc or the source code!

3. Performance

There are benchmarks comparing normal map vs shardedmap included in the shardmap_test.go file. Generally, shardedmap only becomes faster the more I/O you require, and amount of shards you are willing to create. Also, don't forget that slices exist! use slices if you can!!

Heres the benchmarks, i ran them on t460p laptop w/i7-6700HQ CPU @ 2.60GHz. Your mileage may vary, and the performance difference is best seen

$ go test -bench=.
goos: linux
goarch: amd64
pkg: github.com/zutto/shardedmap
BenchmarkShardedMapWrite-8               1000000              2047 ns/op
BenchmarkShardedMapRead-8                1000000              1218 ns/op
BenchmarkShardedMapWR-8                   500000              3197 ns/op
BenchmarkShardedMapWRForceGet-8           300000              4242 ns/op
BenchmarkShardedMapDel-8                 1000000              1420 ns/op
BenchmarkPlainMapWrite-8                  500000              5481 ns/op
BenchmarkPlainMapRead-8                  1000000              2363 ns/op
BenchmarkPlainMapDel-8                    500000              4518 ns/op

Shards are stored in a slice. The slice where your data is added to is computed by djbhash - djbhash is dubbed as:

"It is one of the most efficient hash functions ever published."

Djbhash is very simple and insecure hash, its sole purpose is to split the I/O access across the shards, thus why fast hashing function was deemed necessary.

4. Limitations

Limitations mainly come from golangs std rwmutex & slices & maps. If you find more limitations in this project, do please let me know!

----------------

TODO:

license
documentation & readme
clean the code
more tests?
better error handling graceful error handling to be done.
look for more entrypoints for fuzzing
documentation & readme of the sub-libraries (shardreduce & shardquest)

This project is licensed under MIT license.

Also if you use shardedmap somewhere, I would be delighted to hear about it!

Support available via issues, enterprise support available upon request.