fastcache - fast thread-safe inmemory cache for big number of entries in Go
- Fast. Performance scales on multi-core CPUs. See benchmark results below.
- Thread-safe. Concurrent goroutines may read and write into a single cache instance.
- The fastcache is designed for storing big number of entries without GC overhead.
- Fastcache automatically evicts old entries when reaching the maximum cache size set on its creation.
- Simple API.
- Simple source code.
- Cache may be saved to file and loaded from file.
- Works on Google AppEngine.
Fastcache performance is compared with BigCache, standard Go map and sync.Map.
GOMAXPROCS=4 go test github.com/VictoriaMetrics/fastcache -bench='Set|Get' -benchtime=10s goos: linux goarch: amd64 pkg: github.com/VictoriaMetrics/fastcache BenchmarkBigCacheSet-4 2000 10566656 ns/op 6.20 MB/s 4660369 B/op 6 allocs/op BenchmarkBigCacheGet-4 2000 6902694 ns/op 9.49 MB/s 684169 B/op 131076 allocs/op BenchmarkBigCacheSetGet-4 1000 17579118 ns/op 7.46 MB/s 5046744 B/op 131083 allocs/op BenchmarkCacheSet-4 5000 3808874 ns/op 17.21 MB/s 1142 B/op 2 allocs/op BenchmarkCacheGet-4 5000 3293849 ns/op 19.90 MB/s 1140 B/op 2 allocs/op BenchmarkCacheSetGet-4 2000 8456061 ns/op 15.50 MB/s 2857 B/op 5 allocs/op BenchmarkStdMapSet-4 2000 10559382 ns/op 6.21 MB/s 268413 B/op 65537 allocs/op BenchmarkStdMapGet-4 5000 2687404 ns/op 24.39 MB/s 2558 B/op 13 allocs/op BenchmarkStdMapSetGet-4 100 154641257 ns/op 0.85 MB/s 387405 B/op 65558 allocs/op BenchmarkSyncMapSet-4 500 24703219 ns/op 2.65 MB/s 3426543 B/op 262411 allocs/op BenchmarkSyncMapGet-4 5000 2265892 ns/op 28.92 MB/s 2545 B/op 79 allocs/op BenchmarkSyncMapSetGet-4 1000 14595535 ns/op 8.98 MB/s 3417190 B/op 262277 allocs/op
MB/s column here actually means
millions of operations per second. As you can see,
fastcache is faster than the
BigCache in all the cases.
fastcache is faster than the standard Go map and
sync.Map on workloads with inserts.
- Keys and values must be byte slices. Other types must be marshaled before storing them in the cache.
- Big entries with sizes exceeding 64KB must be stored via distinct API.
- There is no cache expiration. Entries are evicted from the cache only on cache size overflow. Entry deadline may be stored inside the value in order to implement cache expiration.
The cache uses ideas from BigCache:
- The cache consists of many buckets, each with its own lock. This helps scaling the performance on multi-core CPUs, since multiple CPUs may concurrently access distinct buckets.
- Each bucket consists of a
hash(key) -> (key, value) positionmap and 64KB-sized byte slices (chunks) holding encoded
(key, value)entries. Each bucket contains only
O(chunksCount)pointers. For instance, 64GB cache would contain ~1M pointers, while similarly-sized
map[string]bytewould contain ~1B pointers for short keys and values. This would lead to huge GC overhead.
64KB-sized chunks reduce memory fragmentation and the total memory usage comparing to a single big chunk per bucket. Chunks are allocated off-heap if possible. This reduces total memory usage because GC collects unused memory more frequently without the need in
Fastcachehas been extracted from VictoriaMetrics sources. See this article for more info about
What is the difference between
fastcache and other similar caches like BigCache or FreeCache?
Fastcacheis faster. See benchmark results above.
Fastcacheuses less memory due to lower heap fragmentation. This allows saving many GBs of memory on multi-GB caches.
FastcacheAPI is simpler. The API is designed to be used in zero-allocation mode.
fastcache doesn't support cache expiration?
Because we don't need cache expiration in VictoriaMetrics. Cached entries inside
VictoriaMetrics never expire. They are automatically evicted on cache size overflow.
It is easy to implement cache expiration on top of
fastcache by caching values with marshaled deadlines and verifying deadlines after reading these values from the cache.
fastcache doesn't support advanced features such as thundering herd protection or callbacks on entries' eviction?
Because these features would complicate the code and would make it slower.
Fastcache source code is simple - just copy-paste it and implement the feature you want on top of it.