trie: try out ristretto cache

This commit is contained in:
Martin Holst Swende 2019-09-25 14:37:48 +02:00
parent df89233b57
commit fa166501ad
No known key found for this signature in database
GPG key ID: 683B438C05A5DDF0
18 changed files with 2106 additions and 30 deletions

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@ -17,7 +17,6 @@
package trie
import (
"encoding/binary"
"errors"
"fmt"
"io"
@ -25,7 +24,6 @@ import (
"sync"
"time"
"github.com/allegro/bigcache"
"github.com/ethereum/go-ethereum/common"
"github.com/ethereum/go-ethereum/ethdb"
"github.com/ethereum/go-ethereum/log"
@ -69,7 +67,7 @@ const secureKeyLength = 11 + 32
type Database struct {
diskdb ethdb.KeyValueStore // Persistent storage for matured trie nodes
cleans *bigcache.BigCache // GC friendly memory cache of clean node RLPs
cleans *RistrettoCache // GC friendly memory cache of clean node RLPs
dirties map[common.Hash]*cachedNode // Data and references relationships of dirty nodes
oldest common.Hash // Oldest tracked node, flush-list head
newest common.Hash // Newest tracked node, flush-list tail
@ -275,19 +273,6 @@ func expandNode(hash hashNode, n node) node {
}
}
// trienodeHasher is a struct to be used with BigCache, which uses a Hasher to
// determine which shard to place an entry into. It's not a cryptographic hash,
// just to provide a bit of anti-collision (default is FNV64a).
//
// Since trie keys are already hashes, we can just use the key directly to
// map shard id.
type trienodeHasher struct{}
// Sum64 implements the bigcache.Hasher interface.
func (t trienodeHasher) Sum64(key string) uint64 {
return binary.BigEndian.Uint64([]byte(key))
}
// NewDatabase creates a new trie database to store ephemeral trie content before
// its written out to disk or garbage collected. No read cache is created, so all
// data retrievals will hit the underlying disk database.
@ -299,16 +284,9 @@ func NewDatabase(diskdb ethdb.KeyValueStore) *Database {
// before its written out to disk or garbage collected. It also acts as a read cache
// for nodes loaded from disk.
func NewDatabaseWithCache(diskdb ethdb.KeyValueStore, cache int) *Database {
var cleans *bigcache.BigCache
var cleans *RistrettoCache
if cache > 0 {
cleans, _ = bigcache.NewBigCache(bigcache.Config{
Shards: 1024,
LifeWindow: time.Hour,
MaxEntriesInWindow: cache * 1024,
MaxEntrySize: 512,
HardMaxCacheSize: cache,
Hasher: trienodeHasher{},
})
cleans, _ = NewRistrettoCache(cache)
}
return &Database{
diskdb: diskdb,
@ -384,7 +362,7 @@ func (db *Database) insertPreimage(hash common.Hash, preimage []byte) {
func (db *Database) node(hash common.Hash) node {
// Retrieve the node from the clean cache if available
if db.cleans != nil {
if enc, err := db.cleans.Get(string(hash[:])); err == nil && enc != nil {
if enc, err := db.cleans.Get(hash); err == nil && enc != nil {
memcacheCleanHitMeter.Mark(1)
memcacheCleanReadMeter.Mark(int64(len(enc)))
return mustDecodeNode(hash[:], enc)
@ -404,7 +382,7 @@ func (db *Database) node(hash common.Hash) node {
return nil
}
if db.cleans != nil {
db.cleans.Set(string(hash[:]), enc)
db.cleans.Set(hash, enc)
memcacheCleanMissMeter.Mark(1)
memcacheCleanWriteMeter.Mark(int64(len(enc)))
}
@ -420,7 +398,7 @@ func (db *Database) Node(hash common.Hash) ([]byte, error) {
}
// Retrieve the node from the clean cache if available
if db.cleans != nil {
if enc, err := db.cleans.Get(string(hash[:])); err == nil && enc != nil {
if enc, err := db.cleans.Get(hash); err == nil && enc != nil {
memcacheCleanHitMeter.Mark(1)
memcacheCleanReadMeter.Mark(int64(len(enc)))
return enc, nil
@ -438,7 +416,7 @@ func (db *Database) Node(hash common.Hash) ([]byte, error) {
enc, err := db.diskdb.Get(hash[:])
if err == nil && enc != nil {
if db.cleans != nil {
db.cleans.Set(string(hash[:]), enc)
db.cleans.Set(hash, enc)
memcacheCleanMissMeter.Mark(1)
memcacheCleanWriteMeter.Mark(int64(len(enc)))
}
@ -835,7 +813,7 @@ func (c *cleaner) Put(key []byte, rlp []byte) error {
}
// Move the flushed node into the clean cache to prevent insta-reloads
if c.db.cleans != nil {
c.db.cleans.Set(string(hash[:]), rlp)
c.db.cleans.Set(hash, rlp)
}
return nil
}

64
trie/ristretto.go Normal file
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@ -0,0 +1,64 @@
package trie
// Copyright 2019 The go-ethereum Authors
// This file is part of the go-ethereum library.
//
// The go-ethereum library is free software: you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// The go-ethereum library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with the go-ethereum library. If not, see <http://www.gnu.org/licenses/>.
import (
"errors"
"github.com/dgraph-io/ristretto"
"github.com/ethereum/go-ethereum/common"
)
var ErrMissingItem = errors.New("missing item")
type RistrettoCache struct {
cache *ristretto.Cache
}
func NewRistrettoCache(capacity int) (*RistrettoCache, error) {
cache, err := ristretto.NewCache(&ristretto.Config{
NumCounters: int64(capacity * 10),
MaxCost: int64(capacity),
BufferItems: 64,
Metrics: false,
KeyToHash: func(key interface{}) uint64 {
h := key.(common.Hash)
return uint64(h[7]) | uint64(h[6])<<8 | uint64(h[5])<<16 | uint64(h[4])<<24 |
uint64(h[3])<<32 | uint64(h[2])<<40 | uint64(h[1])<<48 | uint64(h[0])<<56
},
})
if err != nil {
return nil, err
}
return &RistrettoCache{
cache: cache,
}, nil
}
func (c *RistrettoCache) Get(key common.Hash) ([]byte, error) {
v, exist := c.cache.Get(key)
if exist {
return []byte(v.(string)), nil
}
return nil, ErrMissingItem
}
func (c *RistrettoCache) Set(key common.Hash, value []byte) error {
c.cache.Set(key, string(value), int64(len(value)))
return nil
}

176
vendor/github.com/dgraph-io/ristretto/LICENSE generated vendored Normal file
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@ -0,0 +1,176 @@
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104
vendor/github.com/dgraph-io/ristretto/README.md generated vendored Normal file
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@ -0,0 +1,104 @@
# Ristretto
[![GoDoc](https://img.shields.io/badge/api-reference-blue.svg)](https://godoc.org/github.com/dgraph-io/ristretto)
[![Go Report Card](https://img.shields.io/badge/go%20report-A%2B-green.svg)](https://goreportcard.com/report/github.com/dgraph-io/ristretto)
Ristretto is a fast, concurrent cache library using a [TinyLFU](https://arxiv.org/abs/1512.00727)
admission policy and Sampled LFU eviction policy.
The motivation to build Ristretto comes from the need for a contention-free
cache in [Dgraph][].
[Dgraph]: https://github.com/dgraph-io/dgraph
## Example
```go
package main
import (
"fmt"
"time"
"github.com/dgraph-io/ristretto"
)
func main() {
// create a cache instance
cache, err := ristretto.NewCache(&ristretto.Config{
NumCounters: 1000000 * 10,
MaxCost: 1000000,
BufferItems: 64,
})
if err != nil {
panic(err)
}
// set a value
cache.Set("key", "value", 1)
// wait for value to pass through buffers
time.Sleep(time.Second / 100)
// get a value, given a key
value, found := cache.Get("key")
if !found {
panic("missing value")
}
fmt.Println(value)
// delete a value, given a key
cache.Del("key")
}
```
### Benchmarks
The benchmarks can be found in https://github.com/dgraph-io/benchmarks/tree/master/cachebench/ristretto
### Hit Ratios
#### Search
This trace is described as "disk read accesses initiated by a large commercial
search engine in response to various web search requests."
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20Search%20(ARC-S3).svg?sanitize=true)
#### Database
This trace is described as "a database server running at a commercial site
running an ERP application on top of a commercial database."
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20Database%20(ARC-DS1).svg?sanitize=true)
#### Looping
This trace demonstrates a looping access pattern.
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20Glimpse%20(LIRS-GLI).svg?sanitize=true)
#### CODASYL
This trace is described as "references to a CODASYL database for a one hour
period."
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20CODASYL%20(ARC-OLTP).svg?sanitize=true)
### Throughput
All throughput benchmarks were ran on an Intel Core i7-8700K (3.7GHz) with 16gb
of RAM.
#### Mixed
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Throughput%20-%20Mixed.svg?sanitize=true)
#### Read
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Throughput%20-%20Read%20(Zipfian).svg?sanitize=true)
#### Write
![](https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Throughput%20-%20Write%20(Zipfian).svg?sanitize=true)

358
vendor/github.com/dgraph-io/ristretto/cache.go generated vendored Normal file
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@ -0,0 +1,358 @@
/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// Ristretto is a fast, fixed size, in-memory cache with a dual focus on
// throughput and hit ratio performance. You can easily add Ristretto to an
// existing system and keep the most valuable data where you need it.
package ristretto
import (
"bytes"
"errors"
"fmt"
"sync/atomic"
"github.com/dgraph-io/ristretto/z"
)
// Cache is a thread-safe implementation of a hashmap with a TinyLFU admission
// policy and a Sampled LFU eviction policy. You can use the same Cache instance
// from as many goroutines as you want.
type Cache struct {
// store is the central concurrent hashmap where key-value items are stored
store store
// policy determines what gets let in to the cache and what gets kicked out
policy policy
// getBuf is a custom ring buffer implementation that gets pushed to when
// keys are read
getBuf *ringBuffer
// setBuf is a buffer allowing us to batch/drop Sets during times of high
// contention
setBuf chan *item
// stats contains a running log of important statistics like hits, misses,
// and dropped items
stats *metrics
// onEvict is called for item evictions
onEvict func(uint64, interface{}, int64)
// KeyToHash function is used to customize the key hashing algorithm.
// Each key will be hashed using the provided function. If keyToHash value
// is not set, the default keyToHash function is used.
keyToHash func(interface{}) uint64
}
// Config is passed to NewCache for creating new Cache instances.
type Config struct {
// NumCounters determines the number of counters (keys) to keep that hold
// access frequency information. It's generally a good idea to have more
// counters than the max cache capacity, as this will improve eviction
// accuracy and subsequent hit ratios.
//
// For example, if you expect your cache to hold 1,000,000 items when full,
// NumCounters should be 10,000,000 (10x). Each counter takes up 4 bits, so
// keeping 10,000,000 counters would require 5MB of memory.
NumCounters int64
// MaxCost can be considered as the cache capacity, in whatever units you
// choose to use.
//
// For example, if you want the cache to have a max capacity of 100MB, you
// would set MaxCost to 100,000,000 and pass an item's number of bytes as
// the `cost` parameter for calls to Set. If new items are accepted, the
// eviction process will take care of making room for the new item and not
// overflowing the MaxCost value.
MaxCost int64
// BufferItems determines the size of Get buffers.
//
// Unless you have a rare use case, using `64` as the BufferItems value
// results in good performance.
BufferItems int64
// Metrics determines whether cache statistics are kept during the cache's
// lifetime. There *is* some overhead to keeping statistics, so you should
// only set this flag to true when testing or throughput performance isn't a
// major factor.
Metrics bool
// OnEvict is called for every eviction and passes the hashed key, value,
// and cost to the function.
OnEvict func(key uint64, value interface{}, cost int64)
// KeyToHash function is used to customize the key hashing algorithm.
// Each key will be hashed using the provided function. If keyToHash value
// is not set, the default keyToHash function is used.
KeyToHash func(key interface{}) uint64
}
// item is passed to setBuf so items can eventually be added to the cache
type item struct {
key uint64
val interface{}
cost int64
}
// NewCache returns a new Cache instance and any configuration errors, if any.
func NewCache(config *Config) (*Cache, error) {
switch {
case config.NumCounters == 0:
return nil, errors.New("NumCounters can't be zero.")
case config.MaxCost == 0:
return nil, errors.New("MaxCost can't be zero.")
case config.BufferItems == 0:
return nil, errors.New("BufferItems can't be zero.")
}
policy := newPolicy(config.NumCounters, config.MaxCost)
cache := &Cache{
store: newStore(),
policy: policy,
getBuf: newRingBuffer(ringLossy, &ringConfig{
Consumer: policy,
Capacity: config.BufferItems,
}),
// TODO: size configuration for this? like BufferItems but for setBuf?
setBuf: make(chan *item, 32*1024),
onEvict: config.OnEvict,
keyToHash: config.KeyToHash,
}
if config.Metrics {
cache.collectMetrics()
}
// We can possibly make this configurable. But having 2 goroutines
// processing this seems sufficient for now.
//
// TODO: Allow a way to stop these goroutines.
for i := 0; i < 2; i++ {
go cache.processItems()
}
return cache, nil
}
// Get returns the value (if any) and a boolean representing whether the
// value was found or not. The value can be nil and the boolean can be true at
// the same time.
func (c *Cache) Get(key interface{}) (interface{}, bool) {
if c == nil {
return nil, false
}
hash := c.keyHash(key)
c.getBuf.Push(hash)
val, ok := c.store.Get(hash)
if ok {
c.stats.Add(hit, hash, 1)
} else {
c.stats.Add(miss, hash, 1)
}
return val, ok
}
// keyHash generates the hash for a given key using the cutom keyToHash function, if provided.
// Otherwise it generates the hash using the z.KeyToHash funcion.
func (c *Cache) keyHash(key interface{}) uint64 {
if c.keyToHash != nil {
return c.keyToHash(key)
}
return z.KeyToHash(key)
}
// Set attempts to add the key-value item to the cache. If it returns false,
// then the Set was dropped and the key-value item isn't added to the cache. If
// it returns true, there's still a chance it could be dropped by the policy if
// its determined that the key-value item isn't worth keeping, but otherwise the
// item will be added and other items will be evicted in order to make room.
func (c *Cache) Set(key interface{}, val interface{}, cost int64) bool {
if c == nil {
return false
}
hash := c.keyHash(key)
// TODO: Add a c.store.UpdateIfPresent here. This would catch any value updates and avoid having
// to push the key in setBuf.
// attempt to add the (possibly) new item to the setBuf where it will later
// be processed by the policy and evaluated
select {
case c.setBuf <- &item{key: hash, val: val, cost: cost}:
return true
default:
// drop the set and avoid blocking
c.stats.Add(dropSets, hash, 1)
return false
}
}
// TODO: Add a public Update function, which would update a key only if present.
// Del deletes the key-value item from the cache if it exists.
func (c *Cache) Del(key interface{}) {
if c == nil {
return
}
hash := c.keyHash(key)
c.policy.Del(hash)
c.store.Del(hash)
}
// Close stops all goroutines and closes all channels.
func (c *Cache) Close() {}
// processItems is ran by goroutines processing the Set buffer.
func (c *Cache) processItems() {
for item := range c.setBuf {
victims, added := c.policy.Add(item.key, item.cost)
if added {
// item was accepted by the policy, so add to the hashmap
c.store.Set(item.key, item.val)
}
// delete victims that are no longer worthy of being in the cache
for _, victim := range victims {
// eviction callback
if c.onEvict != nil {
victim.val, _ = c.store.Get(victim.key)
c.onEvict(victim.key, victim.val, victim.cost)
}
// delete from hashmap
c.store.Del(victim.key)
}
}
}
func (c *Cache) collectMetrics() {
c.stats = newMetrics()
c.policy.CollectMetrics(c.stats)
}
// Metrics returns statistics about cache performance.
func (c *Cache) Metrics() *metrics {
return c.stats
}
type metricType int
const (
// The following 2 keep track of hits and misses.
hit = iota
miss
// The following 3 keep track of number of keys added, updated and evicted.
keyAdd
keyUpdate
keyEvict
// The following 2 keep track of cost of keys added and evicted.
costAdd
costEvict
// The following keep track of how many sets were dropped or rejected later.
dropSets
rejectSets
// The following 2 keep track of how many gets were kept and dropped on the floor.
dropGets
keepGets
// This should be the final enum. Other enums should be set before this.
doNotUse
)
func stringFor(t metricType) string {
switch t {
case hit:
return "hit"
case miss:
return "miss"
case keyAdd:
return "keys-added"
case keyUpdate:
return "keys-updated"
case keyEvict:
return "keys-evicted"
case costAdd:
return "cost-added"
case costEvict:
return "cost-evicted"
case dropSets:
return "sets-dropped"
case rejectSets:
return "sets-rejected" // by policy.
case dropGets:
return "gets-dropped"
case keepGets:
return "gets-kept"
default:
return "unidentified"
}
}
// metrics is the struct for hit ratio statistics. Note that there is some
// cost to maintaining the counters, so it's best to wrap Policies via the
// Recorder type when hit ratio analysis is needed.
type metrics struct {
all [doNotUse][]*uint64
}
func newMetrics() *metrics {
s := &metrics{}
for i := 0; i < doNotUse; i++ {
s.all[i] = make([]*uint64, 256)
slice := s.all[i]
for j := range slice {
slice[j] = new(uint64)
}
}
return s
}
func (p *metrics) Add(t metricType, hash, delta uint64) {
if p == nil {
return
}
valp := p.all[t]
// Avoid false sharing by padding at least 64 bytes of space between two
// atomic counters which would be incremented.
idx := (hash % 25) * 10
atomic.AddUint64(valp[idx], delta)
}
func (p *metrics) Get(t metricType) uint64 {
if p == nil {
return 0
}
valp := p.all[t]
var total uint64
for i := range valp {
total += atomic.LoadUint64(valp[i])
}
return total
}
func (p *metrics) Ratio() float64 {
if p == nil {
return 0.0
}
hits, misses := p.Get(hit), p.Get(miss)
if hits == 0 && misses == 0 {
return 0.0
}
return float64(hits) / float64(hits+misses)
}
func (p *metrics) String() string {
if p == nil {
return ""
}
var buf bytes.Buffer
for i := 0; i < doNotUse; i++ {
t := metricType(i)
fmt.Fprintf(&buf, "%s: %d ", stringFor(t), p.Get(t))
}
fmt.Fprintf(&buf, "gets-total: %d ", p.Get(hit)+p.Get(miss))
fmt.Fprintf(&buf, "hit-ratio: %.2f", p.Ratio())
return buf.String()
}

9
vendor/github.com/dgraph-io/ristretto/go.mod generated vendored Normal file
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@ -0,0 +1,9 @@
module github.com/dgraph-io/ristretto
go 1.12
require (
github.com/davecgh/go-spew v1.1.1 // indirect
github.com/dgryski/go-farm v0.0.0-20190423205320-6a90982ecee2
github.com/stretchr/testify v1.3.0
)

10
vendor/github.com/dgraph-io/ristretto/go.sum generated vendored Normal file
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@ -0,0 +1,10 @@
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dgryski/go-farm v0.0.0-20190423205320-6a90982ecee2 h1:tdlZCpZ/P9DhczCTSixgIKmwPv6+wP5DGjqLYw5SUiA=
github.com/dgryski/go-farm v0.0.0-20190423205320-6a90982ecee2/go.mod h1:SqUrOPUnsFjfmXRMNPybcSiG0BgUW2AuFH8PAnS2iTw=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
github.com/stretchr/testify v1.3.0 h1:TivCn/peBQ7UY8ooIcPgZFpTNSz0Q2U6UrFlUfqbe0Q=
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=

411
vendor/github.com/dgraph-io/ristretto/policy.go generated vendored Normal file
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/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package ristretto
import (
"container/list"
"math"
"sync"
"github.com/dgraph-io/ristretto/z"
)
const (
// lfuSample is the number of items to sample when looking at eviction
// candidates. 5 seems to be the most optimal number [citation needed].
lfuSample = 5
)
// policy is the interface encapsulating eviction/admission behavior.
type policy interface {
ringConsumer
// Add attempts to Add the key-cost pair to the Policy. It returns a slice
// of evicted keys and a bool denoting whether or not the key-cost pair
// was added. If it returns true, the key should be stored in cache.
Add(uint64, int64) ([]*item, bool)
// Has returns true if the key exists in the Policy.
Has(uint64) bool
// Del deletes the key from the Policy.
Del(uint64)
// Cap returns the available capacity.
Cap() int64
// Optionally, set stats object to track how policy is performing.
CollectMetrics(stats *metrics)
}
func newPolicy(numCounters, maxCost int64) policy {
p := &defaultPolicy{
admit: newTinyLFU(numCounters),
evict: newSampledLFU(maxCost),
itemsCh: make(chan []uint64, 3),
}
// TODO: Add a way to stop the goroutine.
go p.processItems()
return p
}
// defaultPolicy is the default defaultPolicy, which is currently TinyLFU
// admission with sampledLFU eviction.
type defaultPolicy struct {
sync.Mutex
admit *tinyLFU
evict *sampledLFU
itemsCh chan []uint64
stats *metrics
}
func (p *defaultPolicy) CollectMetrics(stats *metrics) {
p.stats = stats
p.evict.stats = stats
}
type policyPair struct {
key uint64
cost int64
}
func (p *defaultPolicy) processItems() {
for items := range p.itemsCh {
p.Lock()
p.admit.Push(items)
p.Unlock()
}
}
func (p *defaultPolicy) Push(keys []uint64) bool {
if len(keys) == 0 {
return true
}
select {
case p.itemsCh <- keys:
p.stats.Add(keepGets, keys[0], uint64(len(keys)))
return true
default:
p.stats.Add(dropGets, keys[0], uint64(len(keys)))
return false
}
}
func (p *defaultPolicy) Add(key uint64, cost int64) ([]*item, bool) {
p.Lock()
defer p.Unlock()
// can't add an item bigger than entire cache
if cost > p.evict.maxCost {
return nil, false
}
// we don't need to go any further if the item is already in the cache
if has := p.evict.updateIfHas(key, cost); has {
return nil, true
}
// if we got this far, this key doesn't exist in the cache
//
// calculate the remaining room in the cache (usually bytes)
room := p.evict.roomLeft(cost)
if room >= 0 {
// there's enough room in the cache to store the new item without
// overflowing, so we can do that now and stop here
p.evict.add(key, cost)
return nil, true
}
// incHits is the hit count for the incoming item
incHits := p.admit.Estimate(key)
// sample is the eviction candidate pool to be filled via random sampling
//
// TODO: perhaps we should use a min heap here. Right now our time
// complexity is N for finding the min. Min heap should bring it down to
// O(lg N).
sample := make([]*policyPair, 0, lfuSample)
// as items are evicted they will be appended to victims
victims := make([]*item, 0)
// Delete victims until there's enough space or a minKey is found that has
// more hits than incoming item.
for ; room < 0; room = p.evict.roomLeft(cost) {
// fill up empty slots in sample
sample = p.evict.fillSample(sample)
// find minimally used item in sample
minKey, minHits, minId, minCost := uint64(0), int64(math.MaxInt64), 0, int64(0)
for i, pair := range sample {
// look up hit count for sample key
if hits := p.admit.Estimate(pair.key); hits < minHits {
minKey, minHits, minId, minCost = pair.key, hits, i, pair.cost
}
}
// If the incoming item isn't worth keeping in the policy, reject.
if incHits < minHits {
p.stats.Add(rejectSets, key, 1)
return victims, false
}
// delete the victim from metadata
p.evict.del(minKey)
// delete the victim from sample
sample[minId] = sample[len(sample)-1]
sample = sample[:len(sample)-1]
// store victim in evicted victims slice
victims = append(victims, &item{minKey, nil, minCost})
}
p.evict.add(key, cost)
return victims, true
}
func (p *defaultPolicy) Has(key uint64) bool {
p.Lock()
defer p.Unlock()
_, exists := p.evict.keyCosts[key]
return exists
}
func (p *defaultPolicy) Del(key uint64) {
p.Lock()
defer p.Unlock()
p.evict.del(key)
}
func (p *defaultPolicy) Cap() int64 {
p.Lock()
defer p.Unlock()
return int64(p.evict.maxCost - p.evict.used)
}
// sampledLFU is an eviction helper storing key-cost pairs.
type sampledLFU struct {
keyCosts map[uint64]int64
maxCost int64
used int64
stats *metrics
}
func newSampledLFU(maxCost int64) *sampledLFU {
return &sampledLFU{
keyCosts: make(map[uint64]int64),
maxCost: maxCost,
}
}
func (p *sampledLFU) roomLeft(cost int64) int64 {
return p.maxCost - (p.used + cost)
}
func (p *sampledLFU) fillSample(in []*policyPair) []*policyPair {
if len(in) >= lfuSample {
return in
}
for key, cost := range p.keyCosts {
in = append(in, &policyPair{key, cost})
if len(in) >= lfuSample {
return in
}
}
return in
}
func (p *sampledLFU) del(key uint64) {
cost, ok := p.keyCosts[key]
if !ok {
return
}
p.stats.Add(keyEvict, key, 1)
p.stats.Add(costEvict, key, uint64(cost))
p.used -= cost
delete(p.keyCosts, key)
}
func (p *sampledLFU) add(key uint64, cost int64) {
p.stats.Add(keyAdd, key, 1)
p.stats.Add(costAdd, key, uint64(cost))
p.keyCosts[key] = cost
p.used += cost
}
// TODO: Move this to the store itself. So, it can be used by public Set.
func (p *sampledLFU) updateIfHas(key uint64, cost int64) (updated bool) {
if prev, exists := p.keyCosts[key]; exists {
// Update the cost of the existing key. For simplicity, don't worry about evicting anything
// if the updated cost causes the size to grow beyond maxCost.
p.stats.Add(keyUpdate, key, 1)
p.used += cost - prev
p.keyCosts[key] = cost
return true
}
return false
}
// tinyLFU is an admission helper that keeps track of access frequency using
// tiny (4-bit) counters in the form of a count-min sketch.
// tinyLFU is NOT thread safe.
type tinyLFU struct {
freq *cmSketch
door *z.Bloom
incrs int64
resetAt int64
}
func newTinyLFU(numCounters int64) *tinyLFU {
return &tinyLFU{
freq: newCmSketch(numCounters),
door: z.NewBloomFilter(float64(numCounters), 0.01),
resetAt: numCounters,
}
}
func (p *tinyLFU) Push(keys []uint64) {
for _, key := range keys {
p.Increment(key)
}
}
func (p *tinyLFU) Estimate(key uint64) int64 {
hits := p.freq.Estimate(key)
if p.door.Has(key) {
hits += 1
}
return hits
}
func (p *tinyLFU) Increment(key uint64) {
// flip doorkeeper bit if not already
if added := p.door.AddIfNotHas(key); !added {
// increment count-min counter if doorkeeper bit is already set.
p.freq.Increment(key)
}
p.incrs++
if p.incrs >= p.resetAt {
p.reset()
}
}
func (p *tinyLFU) reset() {
// Zero out incrs.
p.incrs = 0
// clears doorkeeper bits
p.door.Clear()
// halves count-min counters
p.freq.Reset()
}
// lruPolicy is different than the default policy in that it uses exact LRU
// eviction rather than Sampled LFU eviction, which may be useful for certain
// workloads (ARC-OLTP for example; LRU heavy workloads).
//
// TODO: - cost based eviction (multiple evictions for one new item, etc.)
// - sampled LRU
type lruPolicy struct {
sync.Mutex
admit *tinyLFU
ptrs map[uint64]*lruItem
vals *list.List
maxCost int64
room int64
}
type lruItem struct {
ptr *list.Element
key uint64
cost int64
}
func newLRUPolicy(numCounters, maxCost int64) policy {
return &lruPolicy{
admit: newTinyLFU(numCounters),
ptrs: make(map[uint64]*lruItem, maxCost),
vals: list.New(),
room: maxCost,
maxCost: maxCost,
}
}
func (p *lruPolicy) Push(keys []uint64) bool {
if len(keys) == 0 {
return true
}
p.Lock()
defer p.Unlock()
for _, key := range keys {
// increment tinylfu counter
p.admit.Increment(key)
// move list item to front
if val, ok := p.ptrs[key]; ok {
// move accessed val to MRU position
p.vals.MoveToFront(val.ptr)
}
}
return true
}
func (p *lruPolicy) Add(key uint64, cost int64) ([]*item, bool) {
p.Lock()
defer p.Unlock()
if cost > p.maxCost {
return nil, false
}
if val, has := p.ptrs[key]; has {
p.vals.MoveToFront(val.ptr)
return nil, true
}
victims := make([]*item, 0)
incHits := p.admit.Estimate(key)
if p.room >= 0 {
goto add
}
for p.room < 0 {
lru := p.vals.Back()
victim := lru.Value.(*lruItem)
if incHits < p.admit.Estimate(victim.key) {
return victims, false
}
// delete victim from metadata
p.vals.Remove(victim.ptr)
delete(p.ptrs, victim.key)
victims = append(victims, &item{victim.key, nil, victim.cost})
// adjust room
p.room += victim.cost
}
add:
item := &lruItem{key: key, cost: cost}
item.ptr = p.vals.PushFront(item)
p.ptrs[key] = item
p.room -= cost
return victims, true
}
func (p *lruPolicy) Has(key uint64) bool {
p.Lock()
defer p.Unlock()
_, has := p.ptrs[key]
return has
}
func (p *lruPolicy) Del(key uint64) {
p.Lock()
defer p.Unlock()
if val, ok := p.ptrs[key]; ok {
p.vals.Remove(val.ptr)
delete(p.ptrs, key)
}
}
func (p *lruPolicy) Cap() int64 {
p.Lock()
defer p.Unlock()
return int64(p.vals.Len())
}
// TODO
func (p *lruPolicy) CollectMetrics(stats *metrics) {
}

145
vendor/github.com/dgraph-io/ristretto/ring.go generated vendored Normal file
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/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package ristretto
import (
"sync"
"sync/atomic"
"time"
)
const (
ringLossy byte = iota
ringLossless
)
// ringConsumer is the user-defined object responsible for receiving and
// processing items in batches when buffers are drained.
type ringConsumer interface {
Push([]uint64) bool
}
// ringStripe is a singular ring buffer that is not concurrent safe.
type ringStripe struct {
consumer ringConsumer
data []uint64
capacity int
busy int32
}
func newRingStripe(config *ringConfig) *ringStripe {
return &ringStripe{
consumer: config.Consumer,
data: make([]uint64, 0, config.Capacity),
capacity: int(config.Capacity),
}
}
// Push appends an item in the ring buffer and drains (copies items and
// sends to Consumer) if full.
func (s *ringStripe) Push(item uint64) {
s.data = append(s.data, item)
// if we should drain
if len(s.data) >= s.capacity {
// Send elements to consumer. Create a new one.
if s.consumer.Push(s.data) {
s.data = make([]uint64, 0, s.capacity)
} else {
s.data = s.data[:0]
}
}
}
// ringConfig is passed to newRingBuffer with parameters.
type ringConfig struct {
Consumer ringConsumer
Stripes int64
Capacity int64
}
// ringBuffer stores multiple buffers (stripes) and distributes Pushed items
// between them to lower contention.
//
// This implements the "batching" process described in the BP-Wrapper paper
// (section III part A).
type ringBuffer struct {
stripes []*ringStripe
pool *sync.Pool
push func(*ringBuffer, uint64)
rand int
mask int
}
// newRingBuffer returns a striped ring buffer. The Type can be either LOSSY or
// LOSSLESS. LOSSY should provide better performance. The Consumer in ringConfig
// will be called when individual stripes are full and need to drain their
// elements.
func newRingBuffer(ringType byte, config *ringConfig) *ringBuffer {
if ringType == ringLossy {
// LOSSY buffers use a very simple sync.Pool for concurrently reusing
// stripes. We do lose some stripes due to GC (unheld items in sync.Pool
// are cleared), but the performance gains generally outweigh the small
// percentage of elements lost. The performance primarily comes from
// low-level runtime functions used in the standard library that aren't
// available to us (such as runtime_procPin()).
return &ringBuffer{
pool: &sync.Pool{
New: func() interface{} { return newRingStripe(config) },
},
push: pushLossy,
}
}
// begin LOSSLESS buffer handling
//
// unlike lossy, lossless manually handles all stripes
stripes := make([]*ringStripe, config.Stripes)
for i := range stripes {
stripes[i] = newRingStripe(config)
}
return &ringBuffer{
stripes: stripes,
mask: int(config.Stripes - 1),
rand: int(time.Now().UnixNano()), // random seed for picking stripes
push: pushLossless,
}
}
// Push adds an element to one of the internal stripes and possibly drains if
// the stripe becomes full.
func (b *ringBuffer) Push(item uint64) {
b.push(b, item)
}
func pushLossy(b *ringBuffer, item uint64) {
// reuse or create a new stripe
stripe := b.pool.Get().(*ringStripe)
stripe.Push(item)
b.pool.Put(stripe)
}
func pushLossless(b *ringBuffer, item uint64) {
// try to find an available stripe
for i := 0; ; i = (i + 1) & b.mask {
if atomic.CompareAndSwapInt32(&b.stripes[i].busy, 0, 1) {
// try to get exclusive lock on the stripe
b.stripes[i].Push(item)
// unlock
atomic.StoreInt32(&b.stripes[i].busy, 0)
return
}
}
}

189
vendor/github.com/dgraph-io/ristretto/sketch.go generated vendored Normal file
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/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// This package includes multiple probabalistic data structures needed for
// admission/eviction metadata. Most are Counting Bloom Filter variations, but
// a caching-specific feature that is also required is a "freshness" mechanism,
// which basically serves as a "lifetime" process. This freshness mechanism
// was described in the original TinyLFU paper [1], but other mechanisms may
// be better suited for certain data distributions.
//
// [1]: https://arxiv.org/abs/1512.00727
package ristretto
import (
"fmt"
)
// cmSketch is a Count-Min sketch implementation with 4-bit counters, heavily
// based on Damian Gryski's CM4 [1].
//
// [1]: https://github.com/dgryski/go-tinylfu/blob/master/cm4.go
type cmSketch struct {
rows [cmDepth]cmRow
mask uint32
}
const (
// cmDepth is the number of counter copies to store (think of it as rows)
cmDepth = 4
)
func newCmSketch(numCounters int64) *cmSketch {
if numCounters == 0 {
panic("cmSketch: bad numCounters")
}
// get the next power of 2 for better cache performance
numCounters = next2Power(numCounters)
// sketch with FNV-64a hashing algorithm
sketch := &cmSketch{
mask: uint32(numCounters - 1),
}
// initialize rows of counters
for i := 0; i < cmDepth; i++ {
sketch.rows[i] = newCmRow(numCounters)
}
return sketch
}
// Increment increments the count(ers) for the specified key.
func (s *cmSketch) Increment(hashed uint64) {
l, r := uint32(hashed), uint32(hashed>>32)
for i := range s.rows {
// increment the counter on each row
s.rows[i].increment((l + uint32(i)*r) & s.mask)
}
}
// Estimate returns the value of the specified key.
func (s *cmSketch) Estimate(hashed uint64) int64 {
l, r := uint32(hashed), uint32(hashed>>32)
min := byte(255)
for i := range s.rows {
// find the smallest counter value from all the rows
if v := s.rows[i].get((l + uint32(i)*r) & s.mask); v < min {
min = v
}
}
return int64(min)
}
// Reset halves all counter values.
func (s *cmSketch) Reset() {
for _, r := range s.rows {
r.reset()
}
}
func (s *cmSketch) string() string {
var state string
for i := range s.rows {
state += " [ "
state += s.rows[i].string()
state += " ]\n"
}
return state
}
// cmRow is a row of bytes, with each byte holding two counters
type cmRow []byte
func newCmRow(numCounters int64) cmRow {
return make(cmRow, numCounters/2)
}
func (r cmRow) get(n uint32) byte {
return byte(r[n/2]>>((n&1)*4)) & 0x0f
}
func (r cmRow) increment(n uint32) {
// index of the counter
i := n / 2
// shift distance (even 0, odd 4)
s := (n & 1) * 4
// counter value
v := (r[i] >> s) & 0x0f
// only increment if not max value (overflow wrap is bad for LFU)
if v < 15 {
r[i] += 1 << s
}
}
func (r cmRow) reset() {
// halve each counter
for i := range r {
r[i] = (r[i] >> 1) & 0x77
}
}
func (r cmRow) string() string {
var state string
for i := uint64(0); i < uint64(len(r)*2); i++ {
state += fmt.Sprintf("%02d ", (r[(i/2)]>>((i&1)*4))&0x0f)
}
state = state[:len(state)-1]
return state
}
// next2Power rounds x up to the next power of 2, if it's not already one.
func next2Power(x int64) int64 {
x--
x |= x >> 1
x |= x >> 2
x |= x >> 4
x |= x >> 8
x |= x >> 16
x |= x >> 32
x++
return x
}
/*
// TODO
//
// Fingerprint Counting Bloom Filter (FP-CBF): lower false positive rates than
// basic CBF with little added complexity.
//
// https://doi.org/10.1016/j.ipl.2015.11.002
type FPCBF struct {
}
func (c *FPCBF) Push(keys []ring.Element) {}
func (c *FPCBF) Estimate(hashed int64) int64 { return 0 }
// TODO
//
// d-left Counting Bloom Filter: based on d-left hashing which allows for much
// better space efficiency (usually saving a factor of 2 or more).
//
// https://link.springer.com/chapter/10.1007/11841036_61
type DLCBF struct {
}
func (c *DLCBF) Push(keys []ring.Element) {}
func (c *DLCBF) Estimate(hashed int64) int64 { return 0 }
// TODO
//
// Bloom Clock: this might be a good route for keeping track of LRU information
// in a space efficient, probabilistic manner.
//
// https://arxiv.org/abs/1905.13064
type BC struct{}
func (c *BC) Push(keys []ring.Element) {}
func (c *BC) Estimate(hashed int64) int64 { return 0 }
*/

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/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package ristretto
import (
"sync"
)
// store is the interface fulfilled by all hash map implementations in this
// file. Some hash map implementations are better suited for certain data
// distributions than others, so this allows us to abstract that out for use
// in Ristretto.
//
// Every store is safe for concurrent usage.
type store interface {
// Get returns the value associated with the key parameter.
Get(uint64) (interface{}, bool)
// Set adds the key-value pair to the Map or updates the value if it's
// already present.
Set(uint64, interface{})
// Del deletes the key-value pair from the Map.
Del(uint64)
}
// newStore returns the default store implementation.
func newStore() store {
// return newSyncMap()
return newShardedMap()
}
type syncMap struct {
*sync.Map
}
func newSyncMap() store {
return &syncMap{&sync.Map{}}
}
func (m *syncMap) Get(key uint64) (interface{}, bool) {
return m.Load(key)
}
func (m *syncMap) Set(key uint64, value interface{}) {
m.Store(key, value)
}
func (m *syncMap) Del(key uint64) {
m.Delete(key)
}
const numShards uint64 = 256
type shardedMap struct {
shards []*lockedMap
}
func newShardedMap() *shardedMap {
sm := &shardedMap{shards: make([]*lockedMap, int(numShards))}
for i := range sm.shards {
sm.shards[i] = newLockedMap()
}
return sm
}
func (sm *shardedMap) Get(key uint64) (interface{}, bool) {
idx := key % numShards
return sm.shards[idx].Get(key)
}
func (sm *shardedMap) Set(key uint64, value interface{}) {
idx := key % numShards
sm.shards[idx].Set(key, value)
}
func (sm *shardedMap) Del(key uint64) {
idx := key % numShards
sm.shards[idx].Del(key)
}
type lockedMap struct {
sync.RWMutex
data map[uint64]interface{}
}
func newLockedMap() *lockedMap {
return &lockedMap{data: make(map[uint64]interface{})}
}
func (m *lockedMap) Get(key uint64) (interface{}, bool) {
m.RLock()
defer m.RUnlock()
val, found := m.data[key]
return val, found
}
func (m *lockedMap) Set(key uint64, value interface{}) {
m.Lock()
defer m.Unlock()
m.data[key] = value
}
func (m *lockedMap) Del(key uint64) {
m.Lock()
defer m.Unlock()
delete(m.data, key)
}

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bbloom.go
// The MIT License (MIT)
// Copyright (c) 2014 Andreas Briese, eduToolbox@Bri-C GmbH, Sarstedt
// Permission is hereby granted, free of charge, to any person obtaining a copy of
// this software and associated documentation files (the "Software"), to deal in
// the Software without restriction, including without limitation the rights to
// use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
// the Software, and to permit persons to whom the Software is furnished to do so,
// subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
// FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
// COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
// IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
// CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
rtutil.go
// MIT License
// Copyright (c) 2019 Ewan Chou
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
Modifications:
/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

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## bbloom: a bitset Bloom filter for go/golang
===
package implements a fast bloom filter with real 'bitset' and JSONMarshal/JSONUnmarshal to store/reload the Bloom filter.
NOTE: the package uses unsafe.Pointer to set and read the bits from the bitset. If you're uncomfortable with using the unsafe package, please consider using my bloom filter package at github.com/AndreasBriese/bloom
===
changelog 11/2015: new thread safe methods AddTS(), HasTS(), AddIfNotHasTS() following a suggestion from Srdjan Marinovic (github @a-little-srdjan), who used this to code a bloomfilter cache.
This bloom filter was developed to strengthen a website-log database and was tested and optimized for this log-entry mask: "2014/%02i/%02i %02i:%02i:%02i /info.html".
Nonetheless bbloom should work with any other form of entries.
~~Hash function is a modified Berkeley DB sdbm hash (to optimize for smaller strings). sdbm http://www.cse.yorku.ca/~oz/hash.html~~
Found sipHash (SipHash-2-4, a fast short-input PRF created by Jean-Philippe Aumasson and Daniel J. Bernstein.) to be about as fast. sipHash had been ported by Dimtry Chestnyk to Go (github.com/dchest/siphash )
Minimum hashset size is: 512 ([4]uint64; will be set automatically).
###install
```sh
go get github.com/AndreasBriese/bbloom
```
###test
+ change to folder ../bbloom
+ create wordlist in file "words.txt" (you might use `python permut.py`)
+ run 'go test -bench=.' within the folder
```go
go test -bench=.
```
~~If you've installed the GOCONVEY TDD-framework http://goconvey.co/ you can run the tests automatically.~~
using go's testing framework now (have in mind that the op timing is related to 65536 operations of Add, Has, AddIfNotHas respectively)
### usage
after installation add
```go
import (
...
"github.com/AndreasBriese/bbloom"
...
)
```
at your header. In the program use
```go
// create a bloom filter for 65536 items and 1 % wrong-positive ratio
bf := bbloom.New(float64(1<<16), float64(0.01))
// or
// create a bloom filter with 650000 for 65536 items and 7 locs per hash explicitly
// bf = bbloom.New(float64(650000), float64(7))
// or
bf = bbloom.New(650000.0, 7.0)
// add one item
bf.Add([]byte("butter"))
// Number of elements added is exposed now
// Note: ElemNum will not be included in JSON export (for compatability to older version)
nOfElementsInFilter := bf.ElemNum
// check if item is in the filter
isIn := bf.Has([]byte("butter")) // should be true
isNotIn := bf.Has([]byte("Butter")) // should be false
// 'add only if item is new' to the bloomfilter
added := bf.AddIfNotHas([]byte("butter")) // should be false because 'butter' is already in the set
added = bf.AddIfNotHas([]byte("buTTer")) // should be true because 'buTTer' is new
// thread safe versions for concurrent use: AddTS, HasTS, AddIfNotHasTS
// add one item
bf.AddTS([]byte("peanutbutter"))
// check if item is in the filter
isIn = bf.HasTS([]byte("peanutbutter")) // should be true
isNotIn = bf.HasTS([]byte("peanutButter")) // should be false
// 'add only if item is new' to the bloomfilter
added = bf.AddIfNotHasTS([]byte("butter")) // should be false because 'peanutbutter' is already in the set
added = bf.AddIfNotHasTS([]byte("peanutbuTTer")) // should be true because 'penutbuTTer' is new
// convert to JSON ([]byte)
Json := bf.JSONMarshal()
// bloomfilters Mutex is exposed for external un-/locking
// i.e. mutex lock while doing JSON conversion
bf.Mtx.Lock()
Json = bf.JSONMarshal()
bf.Mtx.Unlock()
// restore a bloom filter from storage
bfNew := bbloom.JSONUnmarshal(Json)
isInNew := bfNew.Has([]byte("butter")) // should be true
isNotInNew := bfNew.Has([]byte("Butter")) // should be false
```
to work with the bloom filter.
### why 'fast'?
It's about 3 times faster than William Fitzgeralds bitset bloom filter https://github.com/willf/bloom . And it is about so fast as my []bool set variant for Boom filters (see https://github.com/AndreasBriese/bloom ) but having a 8times smaller memory footprint:
Bloom filter (filter size 524288, 7 hashlocs)
github.com/AndreasBriese/bbloom 'Add' 65536 items (10 repetitions): 6595800 ns (100 ns/op)
github.com/AndreasBriese/bbloom 'Has' 65536 items (10 repetitions): 5986600 ns (91 ns/op)
github.com/AndreasBriese/bloom 'Add' 65536 items (10 repetitions): 6304684 ns (96 ns/op)
github.com/AndreasBriese/bloom 'Has' 65536 items (10 repetitions): 6568663 ns (100 ns/op)
github.com/willf/bloom 'Add' 65536 items (10 repetitions): 24367224 ns (371 ns/op)
github.com/willf/bloom 'Test' 65536 items (10 repetitions): 21881142 ns (333 ns/op)
github.com/dataence/bloom/standard 'Add' 65536 items (10 repetitions): 23041644 ns (351 ns/op)
github.com/dataence/bloom/standard 'Check' 65536 items (10 repetitions): 19153133 ns (292 ns/op)
github.com/cabello/bloom 'Add' 65536 items (10 repetitions): 131921507 ns (2012 ns/op)
github.com/cabello/bloom 'Contains' 65536 items (10 repetitions): 131108962 ns (2000 ns/op)
(on MBPro15 OSX10.8.5 i7 4Core 2.4Ghz)
With 32bit bloom filters (bloom32) using modified sdbm, bloom32 does hashing with only 2 bit shifts, one xor and one substraction per byte. smdb is about as fast as fnv64a but gives less collisions with the dataset (see mask above). bloom.New(float64(10 * 1<<16),float64(7)) populated with 1<<16 random items from the dataset (see above) and tested against the rest results in less than 0.05% collisions.

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// The MIT License (MIT)
// Copyright (c) 2014 Andreas Briese, eduToolbox@Bri-C GmbH, Sarstedt
// Permission is hereby granted, free of charge, to any person obtaining a copy of
// this software and associated documentation files (the "Software"), to deal in
// the Software without restriction, including without limitation the rights to
// use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
// the Software, and to permit persons to whom the Software is furnished to do so,
// subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
// FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
// COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
// IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
// CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
package z
import (
"bytes"
"encoding/json"
"log"
"math"
"unsafe"
)
// helper
var mask = []uint8{1, 2, 4, 8, 16, 32, 64, 128}
func getSize(ui64 uint64) (size uint64, exponent uint64) {
if ui64 < uint64(512) {
ui64 = uint64(512)
}
size = uint64(1)
for size < ui64 {
size <<= 1
exponent++
}
return size, exponent
}
func calcSizeByWrongPositives(numEntries, wrongs float64) (uint64, uint64) {
size := -1 * numEntries * math.Log(wrongs) / math.Pow(float64(0.69314718056), 2)
locs := math.Ceil(float64(0.69314718056) * size / numEntries)
return uint64(size), uint64(locs)
}
// NewBloomFilter returns a new bloomfilter.
func NewBloomFilter(params ...float64) (bloomfilter *Bloom) {
var entries, locs uint64
if len(params) == 2 {
if params[1] < 1 {
entries, locs = calcSizeByWrongPositives(params[0], params[1])
} else {
entries, locs = uint64(params[0]), uint64(params[1])
}
} else {
log.Fatal("usage: New(float64(number_of_entries), float64(number_of_hashlocations))" +
" i.e. New(float64(1000), float64(3)) or New(float64(number_of_entries)," +
" float64(number_of_hashlocations)) i.e. New(float64(1000), float64(0.03))")
}
size, exponent := getSize(uint64(entries))
bloomfilter = &Bloom{
sizeExp: exponent,
size: size - 1,
setLocs: locs,
shift: 64 - exponent,
}
bloomfilter.Size(size)
return bloomfilter
}
// Bloom filter
type Bloom struct {
bitset []uint64
ElemNum uint64
sizeExp uint64
size uint64
setLocs uint64
shift uint64
}
// <--- http://www.cse.yorku.ca/~oz/hash.html
// modified Berkeley DB Hash (32bit)
// hash is casted to l, h = 16bit fragments
// func (bl Bloom) absdbm(b *[]byte) (l, h uint64) {
// hash := uint64(len(*b))
// for _, c := range *b {
// hash = uint64(c) + (hash << 6) + (hash << bl.sizeExp) - hash
// }
// h = hash >> bl.shift
// l = hash << bl.shift >> bl.shift
// return l, h
// }
// Add adds hash of a key to the bloomfilter.
func (bl *Bloom) Add(hash uint64) {
h := hash >> bl.shift
l := hash << bl.shift >> bl.shift
for i := uint64(0); i < bl.setLocs; i++ {
bl.Set((h + i*l) & bl.size)
bl.ElemNum++
}
}
// Has checks if bit(s) for entry hash is/are set,
// returns true if the hash was added to the Bloom Filter.
func (bl Bloom) Has(hash uint64) bool {
h := hash >> bl.shift
l := hash << bl.shift >> bl.shift
for i := uint64(0); i < bl.setLocs; i++ {
switch bl.IsSet((h + i*l) & bl.size) {
case false:
return false
}
}
return true
}
// AddIfNotHas only Adds hash, if it's not present in the bloomfilter.
// Returns true if hash was added.
// Returns false if hash was already registered in the bloomfilter.
func (bl *Bloom) AddIfNotHas(hash uint64) bool {
if bl.Has(hash) {
return false
}
bl.Add(hash)
return true
}
// Size makes Bloom filter with as bitset of size sz.
func (bl *Bloom) Size(sz uint64) {
bl.bitset = make([]uint64, sz>>6)
}
// Clear resets the Bloom filter.
func (bl *Bloom) Clear() {
for i := range bl.bitset {
bl.bitset[i] = 0
}
}
// Set sets the bit[idx] of bitset.
func (bl *Bloom) Set(idx uint64) {
ptr := unsafe.Pointer(uintptr(unsafe.Pointer(&bl.bitset[idx>>6])) + uintptr((idx%64)>>3))
*(*uint8)(ptr) |= mask[idx%8]
}
// IsSet checks if bit[idx] of bitset is set, returns true/false.
func (bl *Bloom) IsSet(idx uint64) bool {
ptr := unsafe.Pointer(uintptr(unsafe.Pointer(&bl.bitset[idx>>6])) + uintptr((idx%64)>>3))
r := ((*(*uint8)(ptr)) >> (idx % 8)) & 1
return r == 1
}
// bloomJSONImExport
// Im/Export structure used by JSONMarshal / JSONUnmarshal
type bloomJSONImExport struct {
FilterSet []byte
SetLocs uint64
}
// NewWithBoolset takes a []byte slice and number of locs per entry,
// returns the bloomfilter with a bitset populated according to the input []byte.
func newWithBoolset(bs *[]byte, locs uint64) *Bloom {
bloomfilter := NewBloomFilter(float64(len(*bs)<<3), float64(locs))
for i, b := range *bs {
*(*uint8)(unsafe.Pointer(uintptr(unsafe.Pointer(&bloomfilter.bitset[0])) + uintptr(i))) = b
}
return bloomfilter
}
// JSONUnmarshal takes JSON-Object (type bloomJSONImExport) as []bytes
// returns bloom32 / bloom64 object.
func JSONUnmarshal(dbData []byte) *Bloom {
bloomImEx := bloomJSONImExport{}
json.Unmarshal(dbData, &bloomImEx)
buf := bytes.NewBuffer(bloomImEx.FilterSet)
bs := buf.Bytes()
bf := newWithBoolset(&bs, bloomImEx.SetLocs)
return bf
}
// JSONMarshal returns JSON-object (type bloomJSONImExport) as []byte.
func (bl Bloom) JSONMarshal() []byte {
bloomImEx := bloomJSONImExport{}
bloomImEx.SetLocs = uint64(bl.setLocs)
bloomImEx.FilterSet = make([]byte, len(bl.bitset)<<3)
for i := range bloomImEx.FilterSet {
bloomImEx.FilterSet[i] = *(*byte)(unsafe.Pointer(uintptr(unsafe.Pointer(&bl.bitset[0])) +
uintptr(i)))
}
data, err := json.Marshal(bloomImEx)
if err != nil {
log.Fatal("json.Marshal failed: ", err)
}
return data
}

64
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// MIT License
// Copyright (c) 2019 Ewan Chou
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
package z
import (
"unsafe"
)
// NanoTime returns the current time in nanoseconds from a monotonic clock.
//go:linkname NanoTime runtime.nanotime
func NanoTime() int64
// CPUTicks is a faster alternative to NanoTime to measure time duration.
//go:linkname CPUTicks runtime.cputicks
func CPUTicks() int64
type stringStruct struct {
str unsafe.Pointer
len int
}
//go:noescape
//go:linkname memhash runtime.memhash
func memhash(p unsafe.Pointer, h, s uintptr) uintptr
// MemHash is the hash function used by go map, it utilizes available hardware instructions(behaves
// as aeshash if aes instruction is available).
// NOTE: The hash seed changes for every process. So, this cannot be used as a persistent hash.
func MemHash(data []byte) uint64 {
ss := (*stringStruct)(unsafe.Pointer(&data))
return uint64(memhash(ss.str, 0, uintptr(ss.len)))
}
// MemHashString is the hash function used by go map, it utilizes available hardware instructions
// (behaves as aeshash if aes instruction is available).
// NOTE: The hash seed changes for every process. So, this cannot be used as a persistent hash.
func MemHashString(str string) uint64 {
ss := (*stringStruct)(unsafe.Pointer(&str))
return uint64(memhash(ss.str, 0, uintptr(ss.len)))
}
// FastRand is a fast thread local random function.
//go:linkname FastRand runtime.fastrand
func FastRand() uint32

0
vendor/github.com/dgraph-io/ristretto/z/rtutil.s generated vendored Normal file
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41
vendor/github.com/dgraph-io/ristretto/z/z.go generated vendored Normal file
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/*
* Copyright 2019 Dgraph Labs, Inc. and Contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package z
// KeyToHash interprets the type of key and converts it to a uint64 hash.
func KeyToHash(key interface{}) uint64 {
switch k := key.(type) {
case uint64:
return k
case string:
return MemHashString(k)
case []byte:
return MemHash(k)
case byte:
return MemHash([]byte{k})
case int:
return uint64(k)
case int32:
return uint64(k)
case uint32:
return uint64(k)
case int64:
return uint64(k)
default:
panic("Key type not supported")
}
}

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@ -74,6 +74,18 @@
"revision": "504e848d77ea4752b3057b8fb46da0e7f746ccf3",
"revisionTime": "2018-06-03T19:32:48Z"
},
{
"checksumSHA1": "WBgnO6VroXxhpYS6kCiFS4jrW/c=",
"path": "github.com/dgraph-io/ristretto",
"revision": "ae326c3348e84b72d4f9db6b0ccb2f3551a0ed3e",
"revisionTime": "2019-09-24T01:22:51Z"
},
{
"checksumSHA1": "fp+NtBZPTvGfWtsxZWUQct/e0ZM=",
"path": "github.com/dgraph-io/ristretto/z",
"revision": "ae326c3348e84b72d4f9db6b0ccb2f3551a0ed3e",
"revisionTime": "2019-09-24T01:22:51Z"
},
{
"checksumSHA1": "Ad8LPSCP9HctFrmskh+S5HpHXcs=",
"path": "github.com/docker/docker/pkg/reexec",