Remove dead BloomFilter code
We don't use this class for a quite a while. lets trash it.
This commit is contained in:
Simon Willnauer
parent
ee4e470f60
commit
9a9301f7d8
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@ -1,629 +0,0 @@
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/*
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* Licensed to Elasticsearch under one or more contributor
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* license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright
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* ownership. Elasticsearch licenses this file to you under
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* the Apache License, Version 2.0 (the "License"); you may
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* 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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.elasticsearch.common.util;
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import org.apache.lucene.store.DataInput;
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import org.apache.lucene.store.DataOutput;
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import org.apache.lucene.store.IndexInput;
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import org.apache.lucene.util.BytesRef;
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import org.apache.lucene.util.RamUsageEstimator;
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import org.elasticsearch.common.Nullable;
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import org.elasticsearch.common.hash.MurmurHash3;
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import org.elasticsearch.common.io.stream.StreamInput;
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import org.elasticsearch.common.io.stream.StreamOutput;
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import org.elasticsearch.common.unit.SizeValue;
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import java.io.IOException;
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import java.util.Arrays;
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import java.util.Comparator;
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/**
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* A bloom filter. Inspired by Guava bloom filter implementation though with some optimizations.
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*/
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public class BloomFilter {
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/**
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* A factory that can use different fpp based on size.
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*/
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public static class Factory {
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public static final Factory DEFAULT = buildDefault();
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private static Factory buildDefault() {
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// Some numbers:
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// 10k =0.001: 140.4kb , 10 Hashes
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// 10k =0.01 : 93.6kb , 6 Hashes
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// 100k=0.01 : 936.0kb , 6 Hashes
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// 100k=0.03 : 712.7kb , 5 Hashes
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// 500k=0.01 : 4.5mb , 6 Hashes
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// 500k=0.03 : 3.4mb , 5 Hashes
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// 500k=0.05 : 2.9mb , 4 Hashes
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// 1m=0.01 : 9.1mb , 6 Hashes
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// 1m=0.03 : 6.9mb , 5 Hashes
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// 1m=0.05 : 5.9mb , 4 Hashes
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// 5m=0.01 : 45.7mb , 6 Hashes
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// 5m=0.03 : 34.8mb , 5 Hashes
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// 5m=0.05 : 29.7mb , 4 Hashes
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// 50m=0.01 : 457.0mb , 6 Hashes
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// 50m=0.03 : 297.3mb , 4 Hashes
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// 50m=0.10 : 228.5mb , 3 Hashes
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return buildFromString("10k=0.01,1m=0.03");
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}
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/**
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* Supports just passing fpp, as in "0.01", and also ranges, like "50k=0.01,1m=0.05". If
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* its null, returns {@link #buildDefault()}.
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*/
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public static Factory buildFromString(@Nullable String config) {
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if (config == null) {
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return buildDefault();
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}
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String[] sEntries = config.split(",");
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if (sEntries.length == 0) {
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if (config.length() > 0) {
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return new Factory(new Entry[]{new Entry(0, Double.parseDouble(config))});
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}
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return buildDefault();
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}
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Entry[] entries = new Entry[sEntries.length];
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for (int i = 0; i < sEntries.length; i++) {
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int index = sEntries[i].indexOf('=');
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entries[i] = new Entry(
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(int) SizeValue.parseSizeValue(sEntries[i].substring(0, index).trim()).singles(),
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Double.parseDouble(sEntries[i].substring(index + 1).trim())
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);
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}
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return new Factory(entries);
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}
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private final Entry[] entries;
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public Factory(Entry[] entries) {
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this.entries = entries;
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// the order is from the upper most expected insertions to the lowest
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Arrays.sort(this.entries, new Comparator<Entry>() {
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@Override
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public int compare(Entry o1, Entry o2) {
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return o2.expectedInsertions - o1.expectedInsertions;
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}
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});
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}
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public BloomFilter createFilter(int expectedInsertions) {
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for (Entry entry : entries) {
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if (expectedInsertions > entry.expectedInsertions) {
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return BloomFilter.create(expectedInsertions, entry.fpp);
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}
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}
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return BloomFilter.create(expectedInsertions, 0.03);
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}
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public static class Entry {
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public final int expectedInsertions;
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public final double fpp;
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Entry(int expectedInsertions, double fpp) {
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this.expectedInsertions = expectedInsertions;
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this.fpp = fpp;
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}
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}
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}
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/**
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* Creates a bloom filter based on the with the expected number
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* of insertions and expected false positive probability.
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*
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* @param expectedInsertions the number of expected insertions to the constructed
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* @param fpp the desired false positive probability (must be positive and less than 1.0)
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*/
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public static BloomFilter create(int expectedInsertions, double fpp) {
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return create(expectedInsertions, fpp, -1);
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}
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/**
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* Creates a bloom filter based on the expected number of insertions, expected false positive probability,
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* and number of hash functions.
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*
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* @param expectedInsertions the number of expected insertions to the constructed
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* @param fpp the desired false positive probability (must be positive and less than 1.0)
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* @param numHashFunctions the number of hash functions to use (must be less than or equal to 255)
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*/
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public static BloomFilter create(int expectedInsertions, double fpp, int numHashFunctions) {
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if (expectedInsertions == 0) {
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expectedInsertions = 1;
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}
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/*
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* TODO(user): Put a warning in the javadoc about tiny fpp values,
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* since the resulting size is proportional to -log(p), but there is not
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* much of a point after all, e.g. optimalM(1000, 0.0000000000000001) = 76680
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* which is less that 10kb. Who cares!
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*/
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long numBits = optimalNumOfBits(expectedInsertions, fpp);
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// calculate the optimal number of hash functions
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if (numHashFunctions == -1) {
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numHashFunctions = optimalNumOfHashFunctions(expectedInsertions, numBits);
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}
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try {
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return new BloomFilter(new BitArray(numBits), numHashFunctions, Hashing.DEFAULT);
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} catch (IllegalArgumentException e) {
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throw new IllegalArgumentException("Could not create BloomFilter of " + numBits + " bits", e);
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}
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}
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public static void skipBloom(IndexInput in) throws IOException {
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int version = in.readInt(); // we do nothing with this now..., defaults to 0
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final int numLongs = in.readInt();
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in.seek(in.getFilePointer() + (numLongs * 8) + 4 + 4); // filter + numberOfHashFunctions + hashType
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}
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public static BloomFilter deserialize(DataInput in) throws IOException {
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int version = in.readInt(); // we do nothing with this now..., defaults to 0
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int numLongs = in.readInt();
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long[] data = new long[numLongs];
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for (int i = 0; i < numLongs; i++) {
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data[i] = in.readLong();
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}
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int numberOfHashFunctions = in.readInt();
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int hashType = in.readInt();
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return new BloomFilter(new BitArray(data), numberOfHashFunctions, Hashing.fromType(hashType));
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}
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public static void serilaize(BloomFilter filter, DataOutput out) throws IOException {
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out.writeInt(0); // version
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BitArray bits = filter.bits;
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out.writeInt(bits.data.length);
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for (long l : bits.data) {
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out.writeLong(l);
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}
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out.writeInt(filter.numHashFunctions);
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out.writeInt(filter.hashing.type()); // hashType
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}
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public static BloomFilter readFrom(StreamInput in) throws IOException {
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int version = in.readVInt(); // we do nothing with this now..., defaults to 0
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int numLongs = in.readVInt();
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long[] data = new long[numLongs];
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for (int i = 0; i < numLongs; i++) {
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data[i] = in.readLong();
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}
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int numberOfHashFunctions = in.readVInt();
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int hashType = in.readVInt(); // again, nothing to do now...
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return new BloomFilter(new BitArray(data), numberOfHashFunctions, Hashing.fromType(hashType));
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}
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public static void writeTo(BloomFilter filter, StreamOutput out) throws IOException {
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out.writeVInt(0); // version
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BitArray bits = filter.bits;
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out.writeVInt(bits.data.length);
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for (long l : bits.data) {
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out.writeLong(l);
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}
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out.writeVInt(filter.numHashFunctions);
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out.writeVInt(filter.hashing.type()); // hashType
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}
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/**
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* The bit set of the BloomFilter (not necessarily power of 2!)
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*/
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final BitArray bits;
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/**
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* Number of hashes per element
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*/
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final int numHashFunctions;
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final Hashing hashing;
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BloomFilter(BitArray bits, int numHashFunctions, Hashing hashing) {
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this.bits = bits;
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this.numHashFunctions = numHashFunctions;
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this.hashing = hashing;
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/*
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* This only exists to forbid BFs that cannot use the compact persistent representation.
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* If it ever throws, at a user who was not intending to use that representation, we should
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* reconsider
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*/
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if (numHashFunctions > 255) {
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throw new IllegalArgumentException("Currently we don't allow BloomFilters that would use more than 255 hash functions");
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}
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}
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public boolean put(BytesRef value) {
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return hashing.put(value, numHashFunctions, bits);
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}
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public boolean mightContain(BytesRef value) {
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return hashing.mightContain(value, numHashFunctions, bits);
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}
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public int getNumHashFunctions() {
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return this.numHashFunctions;
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}
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public long getSizeInBytes() {
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return bits.ramBytesUsed();
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}
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@Override
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public int hashCode() {
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return bits.hashCode() + numHashFunctions;
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}
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/*
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* Cheat sheet:
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*
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* m: total bits
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* n: expected insertions
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* b: m/n, bits per insertion
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* p: expected false positive probability
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*
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* 1) Optimal k = b * ln2
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* 2) p = (1 - e ^ (-kn/m))^k
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* 3) For optimal k: p = 2 ^ (-k) ~= 0.6185^b
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* 4) For optimal k: m = -nlnp / ((ln2) ^ 2)
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*/
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/**
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* Computes the optimal k (number of hashes per element inserted in Bloom filter), given the
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* expected insertions and total number of bits in the Bloom filter.
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* <p>
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* See http://en.wikipedia.org/wiki/File:Bloom_filter_fp_probability.svg for the formula.
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*
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* @param n expected insertions (must be positive)
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* @param m total number of bits in Bloom filter (must be positive)
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*/
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static int optimalNumOfHashFunctions(long n, long m) {
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return Math.max(1, (int) Math.round(m / n * Math.log(2)));
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}
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/**
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* Computes m (total bits of Bloom filter) which is expected to achieve, for the specified
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* expected insertions, the required false positive probability.
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* <p>
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* See http://en.wikipedia.org/wiki/Bloom_filter#Probability_of_false_positives for the formula.
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*
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* @param n expected insertions (must be positive)
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* @param p false positive rate (must be 0 < p < 1)
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*/
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static long optimalNumOfBits(long n, double p) {
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if (p == 0) {
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p = Double.MIN_VALUE;
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}
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return (long) (-n * Math.log(p) / (Math.log(2) * Math.log(2)));
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}
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// Note: We use this instead of java.util.BitSet because we need access to the long[] data field
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static final class BitArray {
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final long[] data;
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final long bitSize;
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long bitCount;
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BitArray(long bits) {
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this(new long[size(bits)]);
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}
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private static int size(long bits) {
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long quotient = bits / 64;
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long remainder = bits - quotient * 64;
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return Math.toIntExact(remainder == 0 ? quotient : 1 + quotient);
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}
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// Used by serialization
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BitArray(long[] data) {
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this.data = data;
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long bitCount = 0;
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for (long value : data) {
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bitCount += Long.bitCount(value);
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}
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this.bitCount = bitCount;
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this.bitSize = data.length * Long.SIZE;
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}
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/** Returns true if the bit changed value. */
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boolean set(long index) {
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if (!get(index)) {
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data[(int) (index >>> 6)] |= (1L << index);
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bitCount++;
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return true;
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}
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return false;
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}
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boolean get(long index) {
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return (data[(int) (index >>> 6)] & (1L << index)) != 0;
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}
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/** Number of bits */
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long bitSize() {
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return bitSize;
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}
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/** Number of set bits (1s) */
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long bitCount() {
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return bitCount;
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}
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BitArray copy() {
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return new BitArray(data.clone());
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}
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/** Combines the two BitArrays using bitwise OR. */
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void putAll(BitArray array) {
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bitCount = 0;
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for (int i = 0; i < data.length; i++) {
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data[i] |= array.data[i];
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bitCount += Long.bitCount(data[i]);
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}
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}
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@Override public boolean equals(Object o) {
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if (o instanceof BitArray) {
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BitArray bitArray = (BitArray) o;
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return Arrays.equals(data, bitArray.data);
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}
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return false;
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}
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@Override public int hashCode() {
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return Arrays.hashCode(data);
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}
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public long ramBytesUsed() {
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return Long.BYTES * data.length + RamUsageEstimator.NUM_BYTES_ARRAY_HEADER + 16;
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}
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}
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static enum Hashing {
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V0() {
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@Override
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protected boolean put(BytesRef value, int numHashFunctions, BitArray bits) {
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long bitSize = bits.bitSize();
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long hash64 = hash3_x64_128(value.bytes, value.offset, value.length, 0);
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int hash1 = (int) hash64;
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int hash2 = (int) (hash64 >>> 32);
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boolean bitsChanged = false;
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for (int i = 1; i <= numHashFunctions; i++) {
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int nextHash = hash1 + i * hash2;
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if (nextHash < 0) {
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nextHash = ~nextHash;
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}
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bitsChanged |= bits.set(nextHash % bitSize);
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}
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return bitsChanged;
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}
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@Override
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protected boolean mightContain(BytesRef value, int numHashFunctions, BitArray bits) {
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long bitSize = bits.bitSize();
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long hash64 = hash3_x64_128(value.bytes, value.offset, value.length, 0);
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int hash1 = (int) hash64;
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int hash2 = (int) (hash64 >>> 32);
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for (int i = 1; i <= numHashFunctions; i++) {
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int nextHash = hash1 + i * hash2;
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if (nextHash < 0) {
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nextHash = ~nextHash;
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}
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if (!bits.get(nextHash % bitSize)) {
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return false;
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}
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}
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return true;
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}
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@Override
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protected int type() {
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return 0;
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}
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},
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V1() {
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@Override
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protected boolean put(BytesRef value, int numHashFunctions, BitArray bits) {
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long bitSize = bits.bitSize();
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MurmurHash3.Hash128 hash128 = MurmurHash3.hash128(value.bytes, value.offset, value.length, 0, new MurmurHash3.Hash128());
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boolean bitsChanged = false;
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long combinedHash = hash128.h1;
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for (int i = 0; i < numHashFunctions; i++) {
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// Make the combined hash positive and indexable
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bitsChanged |= bits.set((combinedHash & Long.MAX_VALUE) % bitSize);
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combinedHash += hash128.h2;
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}
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return bitsChanged;
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}
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@Override
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protected boolean mightContain(BytesRef value, int numHashFunctions, BitArray bits) {
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long bitSize = bits.bitSize();
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MurmurHash3.Hash128 hash128 = MurmurHash3.hash128(value.bytes, value.offset, value.length, 0, new MurmurHash3.Hash128());
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long combinedHash = hash128.h1;
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for (int i = 0; i < numHashFunctions; i++) {
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// Make the combined hash positive and indexable
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if (!bits.get((combinedHash & Long.MAX_VALUE) % bitSize)) {
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return false;
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}
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combinedHash += hash128.h2;
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}
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return true;
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}
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@Override
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protected int type() {
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return 1;
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}
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}
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;
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protected abstract boolean put(BytesRef value, int numHashFunctions, BitArray bits);
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protected abstract boolean mightContain(BytesRef value, int numHashFunctions, BitArray bits);
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protected abstract int type();
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public static final Hashing DEFAULT = Hashing.V1;
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public static Hashing fromType(int type) {
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if (type == 0) {
|
||||
return Hashing.V0;
|
||||
} if (type == 1) {
|
||||
return Hashing.V1;
|
||||
} else {
|
||||
throw new IllegalArgumentException("no hashing type matching " + type);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// START : MURMUR 3_128 USED FOR Hashing.V0
|
||||
// NOTE: don't replace this code with the o.e.common.hashing.MurmurHash3 method which returns a different hash
|
||||
|
||||
protected static long getblock(byte[] key, int offset, int index) {
|
||||
int i_8 = index << 3;
|
||||
int blockOffset = offset + i_8;
|
||||
return ((long) key[blockOffset + 0] & 0xff) + (((long) key[blockOffset + 1] & 0xff) << 8) +
|
||||
(((long) key[blockOffset + 2] & 0xff) << 16) + (((long) key[blockOffset + 3] & 0xff) << 24) +
|
||||
(((long) key[blockOffset + 4] & 0xff) << 32) + (((long) key[blockOffset + 5] & 0xff) << 40) +
|
||||
(((long) key[blockOffset + 6] & 0xff) << 48) + (((long) key[blockOffset + 7] & 0xff) << 56);
|
||||
}
|
||||
|
||||
protected static long rotl64(long v, int n) {
|
||||
return ((v << n) | (v >>> (64 - n)));
|
||||
}
|
||||
|
||||
protected static long fmix(long k) {
|
||||
k ^= k >>> 33;
|
||||
k *= 0xff51afd7ed558ccdL;
|
||||
k ^= k >>> 33;
|
||||
k *= 0xc4ceb9fe1a85ec53L;
|
||||
k ^= k >>> 33;
|
||||
|
||||
return k;
|
||||
}
|
||||
|
||||
@SuppressWarnings("fallthrough") // Uses fallthrough to implement a well know hashing algorithm
|
||||
public static long hash3_x64_128(byte[] key, int offset, int length, long seed) {
|
||||
final int nblocks = length >> 4; // Process as 128-bit blocks.
|
||||
|
||||
long h1 = seed;
|
||||
long h2 = seed;
|
||||
|
||||
long c1 = 0x87c37b91114253d5L;
|
||||
long c2 = 0x4cf5ad432745937fL;
|
||||
|
||||
//----------
|
||||
// body
|
||||
|
||||
for (int i = 0; i < nblocks; i++) {
|
||||
long k1 = getblock(key, offset, i * 2 + 0);
|
||||
long k2 = getblock(key, offset, i * 2 + 1);
|
||||
|
||||
k1 *= c1;
|
||||
k1 = rotl64(k1, 31);
|
||||
k1 *= c2;
|
||||
h1 ^= k1;
|
||||
|
||||
h1 = rotl64(h1, 27);
|
||||
h1 += h2;
|
||||
h1 = h1 * 5 + 0x52dce729;
|
||||
|
||||
k2 *= c2;
|
||||
k2 = rotl64(k2, 33);
|
||||
k2 *= c1;
|
||||
h2 ^= k2;
|
||||
|
||||
h2 = rotl64(h2, 31);
|
||||
h2 += h1;
|
||||
h2 = h2 * 5 + 0x38495ab5;
|
||||
}
|
||||
|
||||
//----------
|
||||
// tail
|
||||
|
||||
// Advance offset to the unprocessed tail of the data.
|
||||
offset += nblocks * 16;
|
||||
|
||||
long k1 = 0;
|
||||
long k2 = 0;
|
||||
|
||||
switch (length & 15) {
|
||||
case 15:
|
||||
k2 ^= ((long) key[offset + 14]) << 48;
|
||||
case 14:
|
||||
k2 ^= ((long) key[offset + 13]) << 40;
|
||||
case 13:
|
||||
k2 ^= ((long) key[offset + 12]) << 32;
|
||||
case 12:
|
||||
k2 ^= ((long) key[offset + 11]) << 24;
|
||||
case 11:
|
||||
k2 ^= ((long) key[offset + 10]) << 16;
|
||||
case 10:
|
||||
k2 ^= ((long) key[offset + 9]) << 8;
|
||||
case 9:
|
||||
k2 ^= ((long) key[offset + 8]) << 0;
|
||||
k2 *= c2;
|
||||
k2 = rotl64(k2, 33);
|
||||
k2 *= c1;
|
||||
h2 ^= k2;
|
||||
|
||||
case 8:
|
||||
k1 ^= ((long) key[offset + 7]) << 56;
|
||||
case 7:
|
||||
k1 ^= ((long) key[offset + 6]) << 48;
|
||||
case 6:
|
||||
k1 ^= ((long) key[offset + 5]) << 40;
|
||||
case 5:
|
||||
k1 ^= ((long) key[offset + 4]) << 32;
|
||||
case 4:
|
||||
k1 ^= ((long) key[offset + 3]) << 24;
|
||||
case 3:
|
||||
k1 ^= ((long) key[offset + 2]) << 16;
|
||||
case 2:
|
||||
k1 ^= ((long) key[offset + 1]) << 8;
|
||||
case 1:
|
||||
k1 ^= (key[offset]);
|
||||
k1 *= c1;
|
||||
k1 = rotl64(k1, 31);
|
||||
k1 *= c2;
|
||||
h1 ^= k1;
|
||||
}
|
||||
|
||||
//----------
|
||||
// finalization
|
||||
|
||||
h1 ^= length;
|
||||
h2 ^= length;
|
||||
|
||||
h1 += h2;
|
||||
h2 += h1;
|
||||
|
||||
h1 = fmix(h1);
|
||||
h2 = fmix(h2);
|
||||
|
||||
h1 += h2;
|
||||
h2 += h1;
|
||||
|
||||
//return (new long[]{h1, h2});
|
||||
// SAME AS GUAVA, they take the first long out of the 128bit
|
||||
return h1;
|
||||
}
|
||||
|
||||
// END: MURMUR 3_128
|
||||
}
|
||||
Loading…
Reference in New Issue