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Published: Sep 2, 2020 License: Apache-2.0, Apache-2.0, MIT Imports: 10 Imported by: 0

README

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

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 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

import (
	...
	"github.com/AndreasBriese/bbloom"
	...
	)

at your header. In the program use

// 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.

Documentation

Index

Constants

View Source
const (
	// MaxArrayLen is a safe maximum length for slices on this architecture.
	MaxArrayLen = 1<<50 - 1
)

Variables

This section is empty.

Functions

func CPUTicks

func CPUTicks() int64

CPUTicks is a faster alternative to NanoTime to measure time duration.

func Calloc

func Calloc(n int) []byte

Calloc allocates a slice of size n.

func CallocNoRef

func CallocNoRef(n int) []byte

CallocNoRef will not give you memory back without jemalloc.

func FastRand

func FastRand() uint32

FastRand is a fast thread local random function.

func Free

func Free(b []byte)

Free does not do anything in this mode.

func HistogramBounds

func HistogramBounds(minExponent, maxExponent uint32) []float64

Creates bounds for an histogram. The bounds are powers of two of the form [2^min_exponent, ..., 2^max_exponent].

func KeyToHash

func KeyToHash(key interface{}) (uint64, uint64)

TODO: Figure out a way to re-use memhash for the second uint64 hash, we

already know that appending bytes isn't reliable for generating a
second hash (see Ristretto PR #88).

We also know that while the Go runtime has a runtime memhash128
function, it's not possible to use it to generate [2]uint64 or
anything resembling a 128bit hash, even though that's exactly what
we need in this situation.

func MemHash

func MemHash(data []byte) uint64

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 MemHashString

func MemHashString(str string) uint64

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 NanoTime

func NanoTime() int64

NanoTime returns the current time in nanoseconds from a monotonic clock.

func NumAllocBytes

func NumAllocBytes() int64

NumAllocBytes returns the number of bytes allocated using calls to z.Calloc. The allocations could be happening via either Go or jemalloc, depending upon the build flags.

func StatsPrint

func StatsPrint()

Types

type Bloom

type Bloom struct {
	ElemNum uint64
	// contains filtered or unexported fields
}

Bloom filter

func JSONUnmarshal

func JSONUnmarshal(dbData []byte) (*Bloom, error)

JSONUnmarshal takes JSON-Object (type bloomJSONImExport) as []bytes returns bloom32 / bloom64 object.

func NewBloomFilter

func NewBloomFilter(params ...float64) (bloomfilter *Bloom)

NewBloomFilter returns a new bloomfilter.

func (*Bloom) Add

func (bl *Bloom) Add(hash uint64)

Add adds hash of a key to the bloomfilter.

func (*Bloom) AddIfNotHas

func (bl *Bloom) AddIfNotHas(hash uint64) bool

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 (*Bloom) Clear

func (bl *Bloom) Clear()

Clear resets the Bloom filter.

func (Bloom) Has

func (bl Bloom) Has(hash uint64) bool

Has checks if bit(s) for entry hash is/are set, returns true if the hash was added to the Bloom Filter.

func (*Bloom) IsSet

func (bl *Bloom) IsSet(idx uint64) bool

IsSet checks if bit[idx] of bitset is set, returns true/false.

func (Bloom) JSONMarshal

func (bl Bloom) JSONMarshal() []byte

JSONMarshal returns JSON-object (type bloomJSONImExport) as []byte.

func (*Bloom) Set

func (bl *Bloom) Set(idx uint64)

Set sets the bit[idx] of bitset.

func (*Bloom) Size

func (bl *Bloom) Size(sz uint64)

Size makes Bloom filter with as bitset of size sz.

type Buffer

type Buffer struct {
	// contains filtered or unexported fields
}

Buffer is equivalent of bytes.Buffer without the ability to read. It uses z.Calloc to allocate memory, which depending upon how the code is compiled could use jemalloc for allocations.

func NewBuffer

func NewBuffer(sz int) *Buffer

NewBuffer would allocate a buffer of size sz upfront.

func (*Buffer) Allocate

func (b *Buffer) Allocate(n int) []byte

Allocate is a way to get a slice of size n back from the buffer. This slice can be directly written to. Warning: Allocate is not thread-safe. The byte slice returned MUST be used before further calls to Buffer.

func (*Buffer) Bytes

func (b *Buffer) Bytes() []byte

Bytes would return all the written bytes as a slice.

func (*Buffer) Grow

func (b *Buffer) Grow(n int)

Grow would grow the buffer to have at least n more bytes. In case the buffer is at capacity, it would reallocate twice the size of current capacity + n, to ensure n bytes can be written to the buffer without further allocation.

func (*Buffer) Len

func (b *Buffer) Len() int

Len would return the number of bytes written to the buffer so far.

func (*Buffer) Release

func (b *Buffer) Release()

Release would free up the memory allocated by the buffer. Once the usage of buffer is done, it is important to call Release, otherwise a memory leak can happen.

func (*Buffer) Reset

func (b *Buffer) Reset()

Reset would reset the buffer to be reused.

func (*Buffer) Slice

func (b *Buffer) Slice(offset int) []byte

Slice would return the slice written at offset.

func (*Buffer) SliceAllocate

func (b *Buffer) SliceAllocate(sz int) []byte

SliceAllocate would encode the size provided into the buffer, followed by a call to Allocate, hence returning the slice of size sz. This can be used to allocate a lot of small buffers into this big buffer. Note that SliceAllocate should NOT be mixed with normal calls to Write. Otherwise, SliceOffsets won't work.

func (*Buffer) SliceOffsets

func (b *Buffer) SliceOffsets(offsets []int) []int

SliceOffsets would return the offsets of all slices written to the buffer. TODO: Perhaps keep the offsets separate in another buffer, and allow access to slices via index.

func (*Buffer) Write

func (b *Buffer) Write(p []byte) (n int, err error)

Write would write p bytes to the buffer.

type HistogramData

type HistogramData struct {
	Bounds         []float64
	Count          int64
	CountPerBucket []int64
	Min            int64
	Max            int64
	Sum            int64
}

HistogramData stores the information needed to represent the sizes of the keys and values as a histogram.

func NewHistogramData

func NewHistogramData(bounds []float64) *HistogramData

NewHistogramData returns a new instance of HistogramData with properly initialized fields.

func (*HistogramData) Copy

func (histogram *HistogramData) Copy() *HistogramData

func (*HistogramData) Mean

func (histogram *HistogramData) Mean() float64

Mean returns the mean value for the histogram.

func (*HistogramData) String

func (histogram *HistogramData) String() string

String converts the histogram data into human-readable string.

func (*HistogramData) Update

func (histogram *HistogramData) Update(value int64)

Update changes the Min and Max fields if value is less than or greater than the current values.

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