Add improvements (#412)
- custom hashmap - avoid string creation - use graal
This commit is contained in:
Pratham
GitHub
@@ -15,18 +15,24 @@
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*/
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package dev.morling.onebrc;
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import static java.nio.charset.StandardCharsets.*;
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import static java.util.stream.Collectors.*;
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import java.io.File;
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import java.io.RandomAccessFile;
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import java.nio.charset.StandardCharsets;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.TreeMap;
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import java.util.concurrent.ConcurrentHashMap;
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import java.util.concurrent.Callable;
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import java.util.concurrent.ExecutionException;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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import java.util.concurrent.Future;
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import java.util.concurrent.TimeUnit;
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import java.util.stream.Collectors;
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import java.util.stream.IntStream;
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public class CalculateAverage_phd3 {
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@@ -34,12 +40,16 @@ public class CalculateAverage_phd3 {
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private static final int NUM_THREADS = Runtime.getRuntime().availableProcessors() * 2;
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private static final String FILE = "./measurements.txt";
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private static final long FILE_SIZE = new File(FILE).length();
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// A chunk is a unit for processing, the file will be divided in chunks of the following size
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private static final int CHUNK_SIZE = 65536 * 1024;
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// Read a little more data into the buffer to finish processing current line
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private static final int PADDING = 512;
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// Minor : Precompute powers to avoid recalculating while parsing doubles (temperatures)
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private static final double[] POWERS_OF_10 = IntStream.range(0, 6).mapToDouble(x -> Math.pow(10.0, x)).toArray();
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private static final Map<String, AggregationInfo> globalMap = new ConcurrentHashMap<>();
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/**
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* A Utility to print aggregated information in the desired format
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*/
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private record ResultRow(double min, double mean, double max) {
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public String toString() {
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@@ -52,7 +62,7 @@ public class CalculateAverage_phd3 {
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};
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public static ResultRow resultRow(AggregationInfo aggregationInfo) {
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return new ResultRow(aggregationInfo.min, aggregationInfo.sum / aggregationInfo.count, aggregationInfo.max);
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return new ResultRow(aggregationInfo.min, (Math.round(aggregationInfo.sum * 10.0) / 10.0) / (aggregationInfo.count), aggregationInfo.max);
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}
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public static void main(String[] args) throws Exception {
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@@ -60,19 +70,37 @@ public class CalculateAverage_phd3 {
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int numChunks = (int) Math.ceil(fileLength * 1.0 / CHUNK_SIZE);
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ExecutorService executorService = Executors.newFixedThreadPool(NUM_THREADS);
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BufferDataProvider provider = new RandomAccessBasedProvider(FILE, FILE_SIZE);
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List<Future<LinearProbingHashMap>> futures = new ArrayList<>();
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// Process chunks in parallel
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for (int chunkIndex = 0; chunkIndex < numChunks; chunkIndex++) {
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executorService.submit(new Aggregator(chunkIndex, provider));
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futures.add(executorService.submit(new Aggregator(chunkIndex, provider)));
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}
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executorService.shutdown();
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executorService.awaitTermination(10, TimeUnit.MINUTES);
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Map<String, ResultRow> measurements = new TreeMap<>(globalMap.entrySet().stream()
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Map<String, AggregationInfo> info = futures.stream().map(f -> {
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try {
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return f.get();
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}
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catch (ExecutionException | InterruptedException e) {
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throw new RuntimeException(e);
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}
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})
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.map(LinearProbingHashMap::toMap)
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.flatMap(map -> map.entrySet().stream())
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.sequential()
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.collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue, AggregationInfo::update));
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Map<String, ResultRow> measurements = new TreeMap<>(info.entrySet().stream()
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.collect(toMap(Map.Entry::getKey, e -> resultRow(e.getValue()))));
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System.out.println(measurements);
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}
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/**
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* Stores required running aggregation information to be able to compute min/max/average at the end
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*/
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private static class AggregationInfo {
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double min = Double.POSITIVE_INFINITY;
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double max = Double.NEGATIVE_INFINITY;
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@@ -108,13 +136,14 @@ public class CalculateAverage_phd3 {
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int read(byte[] buffer, long offset) throws Exception;
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}
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/**
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* uses RandomAccessFile seek and read APIs to load data into a buffer.
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*/
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private static class RandomAccessBasedProvider implements BufferDataProvider {
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private final String filePath;
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private final long fileSize;
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RandomAccessBasedProvider(String filePath, long fileSize) {
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this.filePath = filePath;
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this.fileSize = fileSize;
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}
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@Override
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@@ -133,7 +162,10 @@ public class CalculateAverage_phd3 {
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}
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}
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private static class Aggregator implements Runnable {
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/**
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* Task to processes a chunk of file and return a custom linear probing hashmap for performance
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*/
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private static class Aggregator implements Callable<LinearProbingHashMap> {
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private final long startByte;
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private final BufferDataProvider dataProvider;
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@@ -143,7 +175,7 @@ public class CalculateAverage_phd3 {
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}
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@Override
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public void run() {
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public LinearProbingHashMap call() {
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try {
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// offset for the last byte to be processed (excluded)
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long endByte = Math.min(startByte + CHUNK_SIZE, FILE_SIZE);
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@@ -151,25 +183,15 @@ public class CalculateAverage_phd3 {
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long bufferSize = endByte - startByte + ((endByte == FILE_SIZE) ? 0 : PADDING);
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byte[] buffer = new byte[(int) bufferSize];
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int bytes = dataProvider.read(buffer, startByte);
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// Partial aggregation to avoid accessing global concurrent map for every entry
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Map<String, AggregationInfo> updated = processBuffer(
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buffer, startByte == 0, endByte - startByte);
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// Full aggregation with global map
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updated.entrySet().forEach(entry -> {
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globalMap.compute(entry.getKey(), (k, v) -> {
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if (v == null) {
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return entry.getValue();
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}
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return v.update(entry.getValue());
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});
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});
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// Partial aggregation in a hashmap
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return processBuffer(buffer, startByte == 0, endByte - startByte);
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}
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catch (Throwable e) {
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throw new RuntimeException(e);
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}
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}
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private static Map<String, AggregationInfo> processBuffer(byte[] buffer, boolean isFileStart, long nextChunkStart) {
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private static LinearProbingHashMap processBuffer(byte[] buffer, boolean isFileStart, long nextChunkStart) {
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int start = 0;
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// Move to the next entry after '\n'. Don't do this if we're at the start of
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// the file to avoid missing first entry.
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@@ -180,13 +202,15 @@ public class CalculateAverage_phd3 {
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start += 1;
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}
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// local map for this thread, don't need thread safety
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Map<String, AggregationInfo> chunkMap = new HashMap<>();
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LinearProbingHashMap chunkLocalMap = new LinearProbingHashMap();
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while (true) {
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LineInfo lineInfo = getNextLine(buffer, start);
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String key = new String(buffer, start, lineInfo.semicolonIndex - start);
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byte[] keyBytes = new byte[lineInfo.semicolonIndex - start];
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System.arraycopy(buffer, start, keyBytes, 0, keyBytes.length);
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double value = parseDouble(buffer, lineInfo.semicolonIndex + 1, lineInfo.nextStart - 1);
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update(chunkMap, key, value);
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// Update aggregated value for the given key with the new line
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AggregationInfo info = chunkLocalMap.get(keyBytes, lineInfo.keyHash);
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info.update(value);
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if ((lineInfo.nextStart > nextChunkStart) || (lineInfo.nextStart >= buffer.length)) {
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// we are already at a point where the next line will be processed in the next chunk,
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@@ -196,9 +220,12 @@ public class CalculateAverage_phd3 {
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start = lineInfo.nextStart();
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}
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return chunkMap;
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return chunkLocalMap;
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}
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/**
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* Converts bytes to double value without intermediate string conversion, faster than Double.parseDouble.
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*/
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private static double parseDouble(byte[] bytes, int offset, int end) {
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boolean negative = (bytes[offset] == '-');
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int current = negative ? offset + 1 : offset;
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@@ -216,26 +243,97 @@ public class CalculateAverage_phd3 {
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return (preFloat + ((postFloat) / POWERS_OF_10[end - postFloatStart])) * (negative ? -1 : 1);
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}
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private static void update(Map<String, AggregationInfo> state, String key, double value) {
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AggregationInfo info = state.computeIfAbsent(key, k -> new AggregationInfo());
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info.update(value);
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}
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// identifies indexes of the next ';' and '\n', which will be used to get entry key and value from line
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/**
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* Identifies indexes of the next ';' and '\n', which will be used to get entry key and value from line. Also
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* computes the hash value for the key while iterating.
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*/
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private static LineInfo getNextLine(byte[] buffer, int start) {
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// caller guarantees that the access is in bounds, so no index check
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int hash = 0;
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while (buffer[start] != ';') {
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start++;
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hash = hash * 31 + buffer[start];
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}
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// The following is just to further reduce the probability of collisions
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hash = hash ^ (hash << 16);
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int semicolonIndex = start;
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// caller guarantees that the access is in bounds, so no index check
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while (buffer[start] != '\n') {
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start++;
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}
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return new LineInfo(semicolonIndex, start + 1);
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return new LineInfo(semicolonIndex, start + 1, hash);
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}
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}
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private record LineInfo(int semicolonIndex, int nextStart) {
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private record LineInfo(int semicolonIndex, int nextStart, int keyHash) {
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}
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/**
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* A simple map with pre-configured fixed bucket count. With 2^13 buckets and current hash function, seeing 4
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* collisions which is not too bad. Every bucket is implemented with a linked list. The map is NOT thread safe.
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*/
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private static class LinearProbingHashMap {
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private final static int BUCKET_COUNT = 8191;
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private final Node[] buckets;
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LinearProbingHashMap() {
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this.buckets = new Node[BUCKET_COUNT];
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}
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/**
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* Given a key, returns the current value of AggregationInfo. If not present, creates a new empty node at the
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* front of the bucket
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*/
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public AggregationInfo get(byte[] key, int keyHash) {
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// find bucket index through bitwise AND, works for bucketCount = (2^p - 1)
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int bucketIndex = BUCKET_COUNT & keyHash;
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Node current = buckets[bucketIndex];
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while (current != null) {
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if (Arrays.equals(current.entry.key(), key)) {
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return current.entry.aggregationInfo();
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}
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current = current.next;
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}
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// Entry does not exist, so add a new node in the linked list
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AggregationInfo newInfo = new AggregationInfo();
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KeyValuePair pair = new KeyValuePair(key, keyHash, newInfo);
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Node newNode = new Node(pair, buckets[bucketIndex]);
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buckets[bucketIndex] = newNode;
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return newNode.entry.aggregationInfo();
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}
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/**
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* A helper to convert to Java's hash map to build the final aggregation after partial aggregations
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*/
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private Map<String, AggregationInfo> toMap() {
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Map<String, AggregationInfo> map = new HashMap<>();
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for (Node bucket : buckets) {
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while (bucket != null) {
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map.put(new String(bucket.entry.key, StandardCharsets.UTF_8), bucket.entry.aggregationInfo());
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bucket = bucket.next;
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}
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}
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return map;
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}
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}
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/**
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* Linked List node to implement a bucket of custom hash map
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*/
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private static class Node {
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KeyValuePair entry;
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Node next;
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public Node(KeyValuePair entry, Node next) {
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this.entry = entry;
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this.next = next;
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}
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}
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/**
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* a wrapper class to store information needed for storing a measurement information in the hashmap
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*/
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private record KeyValuePair(byte[] key, int keyHash, AggregationInfo aggregationInfo) {
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}
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}
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