87 lines
3 KiB
Markdown
87 lines
3 KiB
Markdown
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Blobloom
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========
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A Bloom filter package for Go (golang) with no compile-time dependencies.
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This package implements a version of Bloom filters called [blocked Bloom filters](
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https://algo2.iti.kit.edu/documents/cacheefficientbloomfilters-jea.pdf),
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which get a speed boost from using the CPU cache more efficiently
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than regular Bloom filters.
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Unlike most Bloom filter packages for Go,
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this one doesn't run a hash function for you.
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That's a benefit if you need a custom hash
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or you want pick the fastest one for an application.
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Usage
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-----
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To construct a Bloom filter, you need to know how many keys you want to store
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and what rate of false positives you find acceptable.
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f := blobloom.NewOptimized(blobloom.Config{
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Capacity: nkeys, // Expected number of keys.
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FPRate: 1e-4, // Accept one false positive per 10,000 lookups.
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})
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To add a key:
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// import "github.com/cespare/xxhash/v2"
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f.Add(xxhash.Sum64(key))
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To test for the presence of a key in the filter:
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if f.Has(xxhash.Sum64(key)) {
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// Key is probably in f.
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} else {
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// Key is certainly not in f.
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}
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The false positive rate is defined as usual:
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if you look up 10,000 random keys in a Bloom filter filled to capacity,
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an expected one of those is a false positive for FPRate 1e-4.
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See the examples/ directory and the
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[package documentation](https://pkg.go.dev/github.com/greatroar/blobloom)
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for further usage information and examples.
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Hash functions
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--------------
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Blobloom does not provide hash functions. Instead, it requires client code to
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represent each key as a single 64-bit hash value, leaving it to the user to
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pick the right hash function for a particular problem. Here are some general
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suggestions:
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* If you use Bloom filters to speed up access to a key-value store, you might
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want to look at [xxh3](https://github.com/zeebo/xxh3) or [xxhash](
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https://github.com/cespare/xxhash).
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* If your keys are cryptographic hashes, consider using the first 8 bytes of those hashes.
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* If you use Bloom filters to make probabilistic decisions, a randomized hash
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function such as [maphash](https://golang.org/pkg/hash/maphash) should prevent
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the same false positives occurring every time.
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When evaluating a hash function, or designing a custom one,
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make sure it is a 64-bit hash that properly mixes its input bits.
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Casting a 32-bit hash to uint64 gives suboptimal results.
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So does passing integer keys in without running them through a mixing function.
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License
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-------
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Copyright © 2020-2023 the Blobloom authors
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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