| .. | ||
| arena_test.go | ||
| arena.go | ||
| flush_iterator.go | ||
| iterator.go | ||
| LICENSE | ||
| node.go | ||
| race_test.go | ||
| README.md | ||
| skl_test.go | ||
| skl.go | ||
arenaskl
Fast, lock-free, arena-based Skiplist implementation in Go that supports iteration in both directions.
Advantages
Arenaskl offers several advantages over other skiplist implementations:
- High performance that linearly scales with the number of cores. This is achieved by allocating from a fixed-size arena and by avoiding locks.
- Iterators that can be allocated on the stack and easily cloned by value.
- Simple-to-use and low overhead model for detecting and handling race conditions with other threads.
- Support for iterating in reverse (i.e. previous links).
Limitations
The advantages come at a cost that prevents arenaskl from being a general-purpose skiplist implementation:
- The size of the arena sets a hard upper bound on the combined size of skiplist nodes, keys, and values. This limit includes even the size of deleted nodes, keys, and values.
- Deletion is not supported. Instead, higher-level code is expected to add deletion tombstones and needs to process those tombstones appropriately.
Pedigree
This code is based on Andy Kimball's arenaskl code:
https://github.com/andy-kimball/arenaskl
The arenaskl code is based on the skiplist found in Badger, a Go-based KV store:
https://github.com/dgraph-io/badger/tree/master/skl
The skiplist in Badger is itself based on a C++ skiplist built for Facebook's RocksDB:
https://github.com/facebook/rocksdb/tree/master/memtable
Benchmarks
The benchmarks consist of a mix of reads and writes executed in parallel. The fraction of reads is indicated in the run name: "frac_X" indicates a run where X percent of the operations are reads.
The results are much better than skiplist and slist.
name                  time/op
ReadWrite/frac_0-8     470ns ±11%
ReadWrite/frac_10-8    462ns ± 3%
ReadWrite/frac_20-8    436ns ± 2%
ReadWrite/frac_30-8    410ns ± 2%
ReadWrite/frac_40-8    385ns ± 2%
ReadWrite/frac_50-8    360ns ± 4%
ReadWrite/frac_60-8    386ns ± 1%
ReadWrite/frac_70-8    352ns ± 2%
ReadWrite/frac_80-8    306ns ± 3%
ReadWrite/frac_90-8    253ns ± 4%
ReadWrite/frac_100-8  28.1ns ± 2%
Note that the above numbers are for concurrent operations using 8x parallelism. The same benchmarks without concurrency (use these numbers when comparing vs batchskl):
name                time/op
ReadWrite/frac_0    1.53µs ± 1%
ReadWrite/frac_10   1.46µs ± 2%
ReadWrite/frac_20   1.39µs ± 3%
ReadWrite/frac_30   1.28µs ± 3%
ReadWrite/frac_40   1.21µs ± 2%
ReadWrite/frac_50   1.11µs ± 3%
ReadWrite/frac_60   1.23µs ±17%
ReadWrite/frac_70   1.16µs ± 4%
ReadWrite/frac_80    959ns ± 3%
ReadWrite/frac_90    738ns ± 5%
ReadWrite/frac_100  81.9ns ± 2%
Forward and backward iteration are also fast:
name                time/op
IterNext            3.97ns ± 5%
IterPrev            3.88ns ± 3%
