treap alternatives and similar packages
Based on the "Data Structures" category.
Alternatively, view treap alternatives based on common mentions on social networks and blogs.
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golang-set
A simple, battle-tested and generic set type for the Go language. Trusted by Docker, 1Password, Ethereum and Hashicorp. -
hyperloglog
HyperLogLog with lots of sugar (Sparse, LogLog-Beta bias correction and TailCut space reduction) brought to you by Axiom -
ttlcache
An in-memory cache with item expiration and generics [Moved to: https://github.com/jellydator/ttlcache] -
Bloomfilter
Face-meltingly fast, thread-safe, marshalable, unionable, probability- and optimal-size-calculating Bloom filter in go -
hilbert
Go package for mapping values to and from space-filling curves, such as Hilbert and Peano curves. -
cuckoo-filter
Cuckoo Filter go implement, better than Bloom Filter, configurable and space optimized 布谷鸟过滤器的Go实现,优于布隆过滤器,可以定制化过滤器参数,并进行了空间优化 -
go-rquad
:pushpin: State of the art point location and neighbour finding algorithms for region quadtrees, in Go -
nan
Zero allocation Nullable structures in one library with handy conversion functions, marshallers and unmarshallers
InfluxDB - Power Real-Time Data Analytics at Scale
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README
treap
Package treap implements an immutabe sorted set datastructure using a combination tree/heap or treap.
The algorithms are mostly based on Fast Set Operations Using Treaps
Although the package is oriented towards ordered sets, it is simple to convert it to work as a persistent map. There is a working example showing how to do this.
Benchmark stats
The most interesting benchmark is the performance of insert where a single random key is inserted into a 5k sized map. As the example shows, the treap structure does well here as opposed to a regular immutable map (using full copying). This benchmark does not take into account the fact that the regular maps are not sorted unlike treaps.
The intersection benchmark compares the case where two 10k sets with 5k in common being interesected. The regular map is about 30% faster but this is still respectable showing for treaps.
$ go test --bench=. -benchmem
goos: darwin
goarch: amd64
pkg: github.com/perdata/treap
BenchmarkInsert-4 1000000 2347 ns/op 1719 B/op 36 allocs/op
BenchmarkInsertRegularMap-4 2000 890745 ns/op 336311 B/op 8 allocs/op
BenchmarkIntersection-4 500 3125772 ns/op 1719838 B/op 35836 allocs/op
BenchmarkIntersectionRegularMap-4 500 2436519 ns/op 718142 B/op 123 allocs/op
BenchmarkUnion-4 1000 1451047 ns/op 939846 B/op 19580 allocs/op
BenchmarkDiff-4 500 3280823 ns/op 1742080 B/op 36298 allocs/op
PASS