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318 lines
10 KiB
318 lines
10 KiB
roaring [](https://travis-ci.org/RoaringBitmap/roaring) [](https://godoc.org/github.com/RoaringBitmap/roaring) [](https://godoc.org/github.com/RoaringBitmap/roaring/roaring64) [](https://goreportcard.com/report/github.com/RoaringBitmap/roaring)
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[](https://cloud.drone.io/RoaringBitmap/roaring)
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=============
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This is a go version of the Roaring bitmap data structure.
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Roaring bitmaps are used by several major systems such as [Apache Lucene][lucene] and derivative systems such as [Solr][solr] and
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[Elasticsearch][elasticsearch], [Apache Druid (Incubating)][druid], [LinkedIn Pinot][pinot], [Netflix Atlas][atlas], [Apache Spark][spark], [OpenSearchServer][opensearchserver], [Cloud Torrent][cloudtorrent], [Whoosh][whoosh], [Pilosa][pilosa], [Microsoft Visual Studio Team Services (VSTS)][vsts], and eBay's [Apache Kylin][kylin]. The YouTube SQL Engine, [Google Procella](https://research.google/pubs/pub48388/), uses Roaring bitmaps for indexing.
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[lucene]: https://lucene.apache.org/
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[solr]: https://lucene.apache.org/solr/
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[elasticsearch]: https://www.elastic.co/products/elasticsearch
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[druid]: https://druid.apache.org/
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[spark]: https://spark.apache.org/
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[opensearchserver]: http://www.opensearchserver.com
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[cloudtorrent]: https://github.com/jpillora/cloud-torrent
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[whoosh]: https://bitbucket.org/mchaput/whoosh/wiki/Home
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[pilosa]: https://www.pilosa.com/
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[kylin]: http://kylin.apache.org/
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[pinot]: http://github.com/linkedin/pinot/wiki
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[vsts]: https://www.visualstudio.com/team-services/
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[atlas]: https://github.com/Netflix/atlas
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Roaring bitmaps are found to work well in many important applications:
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> Use Roaring for bitmap compression whenever possible. Do not use other bitmap compression methods ([Wang et al., SIGMOD 2017](http://db.ucsd.edu/wp-content/uploads/2017/03/sidm338-wangA.pdf))
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The ``roaring`` Go library is used by
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* [Cloud Torrent](https://github.com/jpillora/cloud-torrent)
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* [runv](https://github.com/hyperhq/runv)
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* [InfluxDB](https://www.influxdata.com)
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* [Pilosa](https://www.pilosa.com/)
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* [Bleve](http://www.blevesearch.com)
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* [lindb](https://github.com/lindb/lindb)
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* [Elasticell](https://github.com/deepfabric/elasticell)
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* [SourceGraph](https://github.com/sourcegraph/sourcegraph)
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* [M3](https://github.com/m3db/m3)
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* [trident](https://github.com/NetApp/trident)
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This library is used in production in several systems, it is part of the [Awesome Go collection](https://awesome-go.com).
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There are also [Java](https://github.com/RoaringBitmap/RoaringBitmap) and [C/C++](https://github.com/RoaringBitmap/CRoaring) versions. The Java, C, C++ and Go version are binary compatible: e.g, you can save bitmaps
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from a Java program and load them back in Go, and vice versa. We have a [format specification](https://github.com/RoaringBitmap/RoaringFormatSpec).
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This code is licensed under Apache License, Version 2.0 (ASL2.0).
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Copyright 2016-... by the authors.
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### References
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- Daniel Lemire, Owen Kaser, Nathan Kurz, Luca Deri, Chris O'Hara, François Saint-Jacques, Gregory Ssi-Yan-Kai, Roaring Bitmaps: Implementation of an Optimized Software Library, Software: Practice and Experience 48 (4), 2018 [arXiv:1709.07821](https://arxiv.org/abs/1709.07821)
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- Samy Chambi, Daniel Lemire, Owen Kaser, Robert Godin,
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Better bitmap performance with Roaring bitmaps,
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Software: Practice and Experience 46 (5), 2016.
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http://arxiv.org/abs/1402.6407 This paper used data from http://lemire.me/data/realroaring2014.html
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- Daniel Lemire, Gregory Ssi-Yan-Kai, Owen Kaser, Consistently faster and smaller compressed bitmaps with Roaring, Software: Practice and Experience 46 (11), 2016. http://arxiv.org/abs/1603.06549
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### Dependencies
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Dependencies are fetched automatically by giving the `-t` flag to `go get`.
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they include
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- github.com/willf/bitset
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- github.com/mschoch/smat
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- github.com/glycerine/go-unsnap-stream
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- github.com/philhofer/fwd
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- github.com/jtolds/gls
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Note that the smat library requires Go 1.6 or better.
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#### Installation
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- go get -t github.com/RoaringBitmap/roaring
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### Example
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Here is a simplified but complete example:
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```go
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package main
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import (
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"fmt"
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"github.com/RoaringBitmap/roaring"
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"bytes"
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)
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func main() {
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// example inspired by https://github.com/fzandona/goroar
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fmt.Println("==roaring==")
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rb1 := roaring.BitmapOf(1, 2, 3, 4, 5, 100, 1000)
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fmt.Println(rb1.String())
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rb2 := roaring.BitmapOf(3, 4, 1000)
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fmt.Println(rb2.String())
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rb3 := roaring.New()
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fmt.Println(rb3.String())
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fmt.Println("Cardinality: ", rb1.GetCardinality())
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fmt.Println("Contains 3? ", rb1.Contains(3))
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rb1.And(rb2)
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rb3.Add(1)
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rb3.Add(5)
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rb3.Or(rb1)
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// computes union of the three bitmaps in parallel using 4 workers
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roaring.ParOr(4, rb1, rb2, rb3)
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// computes intersection of the three bitmaps in parallel using 4 workers
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roaring.ParAnd(4, rb1, rb2, rb3)
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// prints 1, 3, 4, 5, 1000
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i := rb3.Iterator()
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for i.HasNext() {
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fmt.Println(i.Next())
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}
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fmt.Println()
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// next we include an example of serialization
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buf := new(bytes.Buffer)
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rb1.WriteTo(buf) // we omit error handling
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newrb:= roaring.New()
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newrb.ReadFrom(buf)
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if rb1.Equals(newrb) {
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fmt.Println("I wrote the content to a byte stream and read it back.")
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}
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// you can iterate over bitmaps using ReverseIterator(), Iterator, ManyIterator()
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}
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```
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If you wish to use serialization and handle errors, you might want to
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consider the following sample of code:
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```go
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rb := BitmapOf(1, 2, 3, 4, 5, 100, 1000)
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buf := new(bytes.Buffer)
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size,err:=rb.WriteTo(buf)
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if err != nil {
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t.Errorf("Failed writing")
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}
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newrb:= New()
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size,err=newrb.ReadFrom(buf)
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if err != nil {
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t.Errorf("Failed reading")
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}
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if ! rb.Equals(newrb) {
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t.Errorf("Cannot retrieve serialized version")
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}
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```
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Given N integers in [0,x), then the serialized size in bytes of
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a Roaring bitmap should never exceed this bound:
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`` 8 + 9 * ((long)x+65535)/65536 + 2 * N ``
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That is, given a fixed overhead for the universe size (x), Roaring
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bitmaps never use more than 2 bytes per integer. You can call
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``BoundSerializedSizeInBytes`` for a more precise estimate.
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### 64-bit Roaring
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By default, roaring is used to stored unsigned 32-bit integers. However, we also offer
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an extension dedicated to 64-bit integers. It supports roughly the same functions:
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```go
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package main
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import (
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"fmt"
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"github.com/RoaringBitmap/roaring/roaring64"
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"bytes"
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)
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func main() {
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// example inspired by https://github.com/fzandona/goroar
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fmt.Println("==roaring64==")
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rb1 := roaring64.BitmapOf(1, 2, 3, 4, 5, 100, 1000)
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fmt.Println(rb1.String())
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rb2 := roaring64.BitmapOf(3, 4, 1000)
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fmt.Println(rb2.String())
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rb3 := roaring64.New()
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fmt.Println(rb3.String())
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fmt.Println("Cardinality: ", rb1.GetCardinality())
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fmt.Println("Contains 3? ", rb1.Contains(3))
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rb1.And(rb2)
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rb3.Add(1)
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rb3.Add(5)
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rb3.Or(rb1)
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// prints 1, 3, 4, 5, 1000
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i := rb3.Iterator()
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for i.HasNext() {
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fmt.Println(i.Next())
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}
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fmt.Println()
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// next we include an example of serialization
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buf := new(bytes.Buffer)
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rb1.WriteTo(buf) // we omit error handling
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newrb:= roaring64.New()
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newrb.ReadFrom(buf)
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if rb1.Equals(newrb) {
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fmt.Println("I wrote the content to a byte stream and read it back.")
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}
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// you can iterate over bitmaps using ReverseIterator(), Iterator, ManyIterator()
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}
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```
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Only the 32-bit roaring format is standard and cross-operable between Java, C++, C and Go. There is no guarantee that the 64-bit versions are compatible.
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### Documentation
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Current documentation is available at http://godoc.org/github.com/RoaringBitmap/roaring and http://godoc.org/github.com/RoaringBitmap/roaring64
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### Goroutine safety
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In general, it should not generally be considered safe to access
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the same bitmaps using different goroutines--they are left
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unsynchronized for performance. Should you want to access
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a Bitmap from more than one goroutine, you should
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provide synchronization. Typically this is done by using channels to pass
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the *Bitmap around (in Go style; so there is only ever one owner),
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or by using `sync.Mutex` to serialize operations on Bitmaps.
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### Coverage
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We test our software. For a report on our test coverage, see
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https://coveralls.io/github/RoaringBitmap/roaring?branch=master
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### Benchmark
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Type
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go test -bench Benchmark -run -
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To run benchmarks on [Real Roaring Datasets](https://github.com/RoaringBitmap/real-roaring-datasets)
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run the following:
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```sh
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go get github.com/RoaringBitmap/real-roaring-datasets
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BENCH_REAL_DATA=1 go test -bench BenchmarkRealData -run -
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```
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### Iterative use
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You can use roaring with gore:
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- go get -u github.com/motemen/gore
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- Make sure that ``$GOPATH/bin`` is in your ``$PATH``.
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- go get github.com/RoaringBitmap/roaring
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```go
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$ gore
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gore version 0.2.6 :help for help
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gore> :import github.com/RoaringBitmap/roaring
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gore> x:=roaring.New()
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gore> x.Add(1)
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gore> x.String()
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"{1}"
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```
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### Fuzzy testing
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You can help us test further the library with fuzzy testing:
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go get github.com/dvyukov/go-fuzz/go-fuzz
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go get github.com/dvyukov/go-fuzz/go-fuzz-build
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go test -tags=gofuzz -run=TestGenerateSmatCorpus
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go-fuzz-build github.com/RoaringBitmap/roaring
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go-fuzz -bin=./roaring-fuzz.zip -workdir=workdir/ -timeout=200
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Let it run, and if the # of crashers is > 0, check out the reports in
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the workdir where you should be able to find the panic goroutine stack
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traces.
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### Alternative in Go
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There is a Go version wrapping the C/C++ implementation https://github.com/RoaringBitmap/gocroaring
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For an alternative implementation in Go, see https://github.com/fzandona/goroar
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The two versions were written independently.
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### Mailing list/discussion group
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https://groups.google.com/forum/#!forum/roaring-bitmaps
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