237 lines
9.7 KiB
Java
237 lines
9.7 KiB
Java
/*
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* Copyright 2023 The original authors
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*
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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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*
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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, 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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*/
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package dev.morling.onebrc;
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import java.io.IOException;
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import java.io.RandomAccessFile;
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import java.nio.ByteBuffer;
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import java.nio.channels.FileChannel;
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import java.nio.charset.StandardCharsets;
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import java.util.*;
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import java.util.stream.Collectors;
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import java.util.stream.StreamSupport;
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public class CalculateAverage_palmr {
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private static final String FILE = "./measurements.txt";
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private static final int CHUNK_SIZE = 1024 * 1024 * 10; // Trial and error showed ~10MB to be a good size on our machine
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private static final int STATION_NAME_BUFFER_SIZE = 128;
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private static final int THREAD_COUNT = Math.min(8, Runtime.getRuntime().availableProcessors());
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private static final char SEPARATOR_CHAR = ';';
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private static final char END_OF_RECORD = '\n';
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private static final char MINUS_CHAR = '-';
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private static final char DECIMAL_POINT_CHAR = '.';
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public static void main(String[] args) throws IOException {
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final var file = new RandomAccessFile(FILE, "r");
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final var channel = file.getChannel();
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final TreeMap<String, MeasurementAggregator> results = StreamSupport.stream(ThreadChunk.chunk(file, THREAD_COUNT), true)
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.map(chunk -> parseChunk(chunk, channel))
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.flatMap(bakm -> bakm.getAsUnorderedList().stream())
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.collect(Collectors.toMap(m -> new String(m.stationNameBytes, StandardCharsets.UTF_8), m -> m, MeasurementAggregator::merge, TreeMap::new));
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System.out.println(results);
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}
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private record ThreadChunk(long startPoint, long endPoint, long size) {
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public static Spliterator<CalculateAverage_palmr.ThreadChunk> chunk(final RandomAccessFile file, final int chunkCount) throws IOException {
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final var fileSize = file.length();
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final var idealChunkSize = Math.max(CHUNK_SIZE, fileSize / THREAD_COUNT);
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final var chunks = new CalculateAverage_palmr.ThreadChunk[chunkCount];
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var validChunks = 0;
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var startPoint = 0L;
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for (int i = 0; i < chunkCount; i++) {
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var endPoint = Math.min(startPoint + idealChunkSize, fileSize);
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if (startPoint + idealChunkSize < fileSize)
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{
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file.seek(endPoint);
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while (endPoint++ < fileSize && file.readByte() != END_OF_RECORD) {
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Thread.onSpinWait();
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}
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}
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final var actualSize = endPoint - startPoint;
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if (actualSize > 1) {
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chunks[i] = new CalculateAverage_palmr.ThreadChunk(startPoint, endPoint, actualSize);
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startPoint += actualSize;
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validChunks++;
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}
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else {
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break;
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}
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}
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return Spliterators.spliterator(chunks, 0, validChunks,
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Spliterator.ORDERED |
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Spliterator.DISTINCT |
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Spliterator.SORTED |
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Spliterator.NONNULL |
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Spliterator.IMMUTABLE |
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Spliterator.CONCURRENT
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);
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}
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}
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private static ByteArrayKeyedMap parseChunk(ThreadChunk chunk, FileChannel channel) {
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final var state = new State();
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var offset = chunk.startPoint;
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while (offset < chunk.endPoint) {
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parseData(channel, state, offset, Math.min(CHUNK_SIZE, chunk.endPoint - offset));
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offset += CHUNK_SIZE;
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}
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return state.aggregators;
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}
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private static void parseData(final FileChannel channel,
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final State state,
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final long offset,
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final long bufferSize) {
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final ByteBuffer byteBuffer;
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try {
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byteBuffer = channel.map(FileChannel.MapMode.READ_ONLY, offset, bufferSize);
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while (byteBuffer.hasRemaining()) {
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final var currentChar = byteBuffer.get();
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if (currentChar == SEPARATOR_CHAR) {
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state.parsingValue = true;
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}
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else if (currentChar == END_OF_RECORD) {
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if (state.stationPointerEnd != 0) {
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final var value = state.measurementValue * state.exponent;
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MeasurementAggregator aggregator = state.aggregators.computeIfAbsent(state.stationBuffer, state.stationPointerEnd, state.signedHashCode);
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aggregator.count++;
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aggregator.min = Math.min(aggregator.min, value);
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aggregator.max = Math.max(aggregator.max, value);
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aggregator.sum += value;
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}
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// reset
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state.reset();
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}
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else {
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if (!state.parsingValue) {
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state.stationBuffer[state.stationPointerEnd++] = currentChar;
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state.signedHashCode = 31 * state.signedHashCode + (currentChar & 0xff);
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}
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else {
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if (currentChar == MINUS_CHAR) {
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state.exponent = -0.1;
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}
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else if (currentChar != DECIMAL_POINT_CHAR) {
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state.measurementValue = state.measurementValue * 10 + (currentChar - '0');
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}
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}
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}
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}
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}
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catch (IOException e) {
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throw new RuntimeException(e);
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}
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}
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private static final class State {
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ByteArrayKeyedMap aggregators = new ByteArrayKeyedMap();
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boolean parsingValue = false;
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byte[] stationBuffer = new byte[STATION_NAME_BUFFER_SIZE];
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int signedHashCode = 0;
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int stationPointerEnd = 0;
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double measurementValue = 0;
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double exponent = 0.1;
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public void reset() {
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parsingValue = false;
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signedHashCode = 0;
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stationPointerEnd = 0;
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measurementValue = 0;
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exponent = 0.1;
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}
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}
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private static class MeasurementAggregator {
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final byte[] stationNameBytes;
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final int stationNameHashCode;
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private double min = Double.POSITIVE_INFINITY;
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private double max = Double.NEGATIVE_INFINITY;
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private double sum;
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private long count;
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public MeasurementAggregator(final byte[] stationNameBytes, final int stationNameHashCode) {
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this.stationNameBytes = stationNameBytes;
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this.stationNameHashCode = stationNameHashCode;
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}
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public String toString() {
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return STR."\{round(min)}/\{round(sum / count)}/\{round(max)}";
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}
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private double round(final double value) {
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return Math.round(value * 10.0) / 10.0;
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}
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private MeasurementAggregator merge(final MeasurementAggregator b) {
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this.count += b.count;
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this.min = Math.min(this.min, b.min);
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this.max = Math.max(this.max, b.max);
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this.sum += b.sum;
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return this;
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}
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}
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/**
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* Very basic hash table implementation, only implementing computeIfAbsent since that's all the code needs.
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* It's sized to give minimal collisions with the example test set. this may not hold true if the stations list
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* changes, but it should still perform fairly well.
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* It uses Open Addressing, meaning it's just one array, rather Separate Chaining which is what the default java HashMap uses.
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* IT also uses Linear probing for collision resolution, which given the minimal collision count should hold up well.
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*/
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private static class ByteArrayKeyedMap {
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private final int BUCKET_COUNT = 0xFFFF;
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private final MeasurementAggregator[] buckets = new MeasurementAggregator[BUCKET_COUNT + 1];
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private final List<MeasurementAggregator> compactUnorderedBuckets = new ArrayList<>(413);
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public MeasurementAggregator computeIfAbsent(final byte[] key, final int keyLength, final int keyHashCode) {
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var index = keyHashCode & BUCKET_COUNT;
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while (true) {
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MeasurementAggregator maybe = buckets[index];
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if (maybe != null) {
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if (Arrays.equals(key, 0, keyLength, maybe.stationNameBytes, 0, maybe.stationNameBytes.length)) {
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return maybe;
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}
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index++;
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index &= BUCKET_COUNT;
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}
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else {
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final var copiedKey = Arrays.copyOf(key, keyLength);
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MeasurementAggregator measurementAggregator = new MeasurementAggregator(copiedKey, keyHashCode);
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buckets[index] = measurementAggregator;
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compactUnorderedBuckets.add(measurementAggregator);
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return measurementAggregator;
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}
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}
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}
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public List<MeasurementAggregator> getAsUnorderedList() {
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return compactUnorderedBuckets;
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}
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}
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}
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