Attempt nicer threading via streams and spliterators

src/main/java/dev/morling/onebrc/CalculateAverage_palmr.java

@@ -21,91 +21,68 @@ import java.nio.ByteBuffer;
 import java.nio.channels.FileChannel;
 import java.nio.charset.StandardCharsets;
 import java.util.*;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
 
 public class CalculateAverage_palmr {
-
     private static final String FILE = "./measurements.txt";
-    public static final int CHUNK_SIZE = 1024 * 1024 * 10; // Trial and error showed ~10MB to be a good size on our machine
+    private static final int CHUNK_SIZE = 1024 * 1024 * 10; // Trial and error showed ~10MB to be a good size on our machine
-    public static final int LITTLE_CHUNK_SIZE = 128; // Enough bytes to cover a station name and measurement value :fingers-crossed:
+    private static final int STATION_NAME_BUFFER_SIZE = 50;
-    public static final int STATION_NAME_BUFFER_SIZE = 50;
+    private static final int THREAD_COUNT = Math.min(8, Runtime.getRuntime().availableProcessors());
-    public static final int THREAD_COUNT = Math.min(8, Runtime.getRuntime().availableProcessors());
+    private static final char SEPARATOR_CHAR = ';';
+    private static final char NEWLINE_CHAR = '\n';
+    private static final char MINUS_CHAR = '-';
+    private static final char DECIMAL_POINT_CHAR = '.';
 
     public static void main(String[] args) throws IOException {
 
         @SuppressWarnings("resource") // It's faster to leak the file than be well-behaved
-        RandomAccessFile file = new RandomAccessFile(FILE, "r");
+        final var file = new RandomAccessFile(FILE, "r");
-        FileChannel channel = file.getChannel();
+        final var channel = file.getChannel();
-        long fileSize = channel.size();
 
-        long threadChunk = fileSize / THREAD_COUNT;
+        final TreeMap<String, MeasurementAggregator> results = StreamSupport.stream(ThreadChunk.chunk(file, THREAD_COUNT), true)
-
+                .map(chunk -> parseChunk(chunk, channel))
-        Thread[] threads = new Thread[THREAD_COUNT];
+                .flatMap(bakm -> bakm.getAsUnorderedList().stream())
-        ByteArrayKeyedMap[] results = new ByteArrayKeyedMap[THREAD_COUNT];
+                .collect(Collectors.toMap(m -> new String(m.stationNameBytes, StandardCharsets.UTF_8), m -> m, MeasurementAggregator::merge, TreeMap::new));
-        for (int i = 0; i < THREAD_COUNT; i++) {
+        System.out.println(results);
-            final int j = i;
-            long startPoint = j * threadChunk;
-            long endPoint = startPoint + threadChunk;
-            Thread thread = new Thread(() -> {
-                try {
-                    results[j] = readAndParse(channel, startPoint, endPoint, fileSize);
-                }
-                catch (Throwable t) {
-                    System.err.println("It's broken :(");
-                    // noinspection CallToPrintStackTrace
-                    t.printStackTrace();
-                }
-            });
-            threads[i] = thread;
-            thread.start();
-        }
-
-        final Map<String, MeasurementAggregator> finalAggregator = new TreeMap<>();
-
-        for (int i = 0; i < THREAD_COUNT; i++) {
-            try {
-                threads[i].join();
-            }
-            catch (InterruptedException e) {
-                throw new RuntimeException(e);
-            }
-
-            results[i].getAsUnorderedList().forEach(v -> {
-                String stationName = new String(v.stationNameBytes, StandardCharsets.UTF_8);
-                finalAggregator.compute(stationName, (_, x) -> {
-                    if (x == null) {
-                        return v;
-                    }
-                    else {
-                        x.count += v.count;
-                        x.min = Math.min(x.min, v.min);
-                        x.max = Math.max(x.max, v.max);
-                        x.sum += v.sum;
-                        return x;
-                    }
-                });
-            });
-        }
-        System.out.println(finalAggregator);
     }
 
-    private static ByteArrayKeyedMap readAndParse(final FileChannel channel,
+    private record ThreadChunk(long startPoint, long endPoint, long size) {
-                                                  final long startPoint,
+        public static Spliterator<CalculateAverage_palmr.ThreadChunk> chunk(final RandomAccessFile file, final int chunkCount) throws IOException {
-                                                  final long endPoint,
+            final var fileSize = file.length();
-                                                  final long fileSize) {
+            final var idealChunkSize = fileSize / THREAD_COUNT;
-        final State state = new State();
+            final var chunks = new CalculateAverage_palmr.ThreadChunk[chunkCount];
 
-        boolean skipFirstEntry = startPoint != 0;
+            var startPoint = 0L;
+            for (int i = 0; i < chunkCount; i++) {
+                var endPoint = Math.min(startPoint + idealChunkSize, fileSize);
+                file.seek(endPoint);
+                while (endPoint < fileSize && file.readByte() != NEWLINE_CHAR) {
+                    endPoint++;
+                }
+                final var actualSize = endPoint - startPoint;
+                chunks[i] = new CalculateAverage_palmr.ThreadChunk(startPoint, endPoint, actualSize);
+                startPoint += actualSize;
+            }
 
-        long offset = startPoint;
+            return Spliterators.spliterator(chunks,
-        while (offset < endPoint) {
+                    Spliterator.ORDERED |
-            parseData(channel, state, offset, Math.min(CHUNK_SIZE, fileSize - offset), false, skipFirstEntry);
+                            Spliterator.DISTINCT |
-            skipFirstEntry = false;
+                            Spliterator.SORTED |
-            offset += CHUNK_SIZE;
+                            Spliterator.NONNULL |
+                            Spliterator.IMMUTABLE |
+                            Spliterator.CONCURRENT
+            );
         }
+    }
 
-        if (offset < fileSize) {
+    private static ByteArrayKeyedMap parseChunk(ThreadChunk chunk, FileChannel channel) {
-            // Make sure we finish reading any partially read entry by going a little in to the next chunk, stopping at the first newline
+        final var state = new State();
-            parseData(channel, state, offset, Math.min(LITTLE_CHUNK_SIZE, fileSize - offset), true, false);
+
+        var offset = chunk.startPoint;
+        while (offset < chunk.endPoint) {
+            parseData(channel, state, offset, Math.min(CHUNK_SIZE, chunk.endPoint - offset));
+            offset += CHUNK_SIZE;
         }
 
         return state.aggregators;
@@ -114,69 +91,48 @@ public class CalculateAverage_palmr {
     private static void parseData(final FileChannel channel,
                                   final State state,
                                   final long offset,
-                                  final long bufferSize,
+                                  final long bufferSize) {
-                                  final boolean stopAtNewline,
+        final ByteBuffer byteBuffer;
-                                  final boolean skipFirstEntry) {
-        ByteBuffer byteBuffer;
         try {
             byteBuffer = channel.map(FileChannel.MapMode.READ_ONLY, offset, bufferSize);
-        }
+
-        catch (IOException e) {
+            while (byteBuffer.hasRemaining()) {
+                final var currentChar = byteBuffer.get();
+
+                if (currentChar == SEPARATOR_CHAR) {
+                    state.parsingValue = true;
+                } else if (currentChar == NEWLINE_CHAR) {
+                    if (state.stationPointerEnd != 0) {
+                        final var value = state.measurementValue * state.exponent;
+
+                        MeasurementAggregator aggregator = state.aggregators.computeIfAbsent(state.stationBuffer, state.stationPointerEnd, state.signedHashCode);
+                        aggregator.count++;
+                        aggregator.min = Math.min(aggregator.min, value);
+                        aggregator.max = Math.max(aggregator.max, value);
+                        aggregator.sum += value;
+                    }
+
+                    // reset
+                    state.reset();
+                } else {
+                    if (!state.parsingValue) {
+                        state.stationBuffer[state.stationPointerEnd++] = currentChar;
+                        state.signedHashCode = 31 * state.signedHashCode + (currentChar & 0xff);
+                    } else {
+                        if (currentChar == MINUS_CHAR) {
+                            state.exponent = -0.1;
+                        } else if (currentChar != DECIMAL_POINT_CHAR) {
+                            state.measurementValue = state.measurementValue * 10 + (currentChar - '0');
+                        }
+                    }
+                }
+            }
+        } catch (IOException e) {
             throw new RuntimeException(e);
         }
-
-        boolean isSkippingToFirstCleanEntry = skipFirstEntry;
-
-        while (byteBuffer.hasRemaining()) {
-            byte currentChar = byteBuffer.get();
-
-            if (isSkippingToFirstCleanEntry) {
-                if (currentChar == '\n') {
-                    isSkippingToFirstCleanEntry = false;
-                }
-
-                continue;
-            }
-
-            if (currentChar == ';') {
-                state.parsingValue = true;
-            }
-            else if (currentChar == '\n') {
-                if (state.stationPointerEnd != 0) {
-                    double value = state.measurementValue * state.exponent;
-
-                    MeasurementAggregator aggregator = state.aggregators.computeIfAbsent(state.stationBuffer, state.stationPointerEnd, state.signedHashCode);
-                    aggregator.count++;
-                    aggregator.min = Math.min(aggregator.min, value);
-                    aggregator.max = Math.max(aggregator.max, value);
-                    aggregator.sum += value;
-                }
-
-                if (stopAtNewline) {
-                    return;
-                }
-
-                // reset
-                state.reset();
-            }
-            else {
-                if (!state.parsingValue) {
-                    state.stationBuffer[state.stationPointerEnd++] = currentChar;
-                    state.signedHashCode = 31 * state.signedHashCode + (currentChar & 0xff);
-                }
-                else {
-                    if (currentChar == '-') {
-                        state.exponent = -0.1;
-                    }
-                    else if (currentChar != '.') {
-                        state.measurementValue = state.measurementValue * 10 + (currentChar - '0');
-                    }
-                }
-            }
-        }
     }
 
-    static final class State {
+    private static final class State {
         ByteArrayKeyedMap aggregators = new ByteArrayKeyedMap();
         boolean parsingValue = false;
         byte[] stationBuffer = new byte[STATION_NAME_BUFFER_SIZE];
@@ -208,37 +164,51 @@ public class CalculateAverage_palmr {
         }
 
         public String toString() {
-            return round(min) + "/" + round(sum / count) + "/" + round(max);
+            return STR."\{round(min)}/\{round(sum / count)}/\{round(max)}";
         }
 
-        private double round(double value) {
+        private double round(final double value) {
             return Math.round(value * 10.0) / 10.0;
         }
+
+        private MeasurementAggregator merge(final MeasurementAggregator b) {
+            this.count += b.count;
+            this.min = Math.min(this.min, b.min);
+            this.max = Math.max(this.max, b.max);
+            this.sum += b.sum;
+            return this;
+        }
     }
 
+    /**
+     * Very basic hash table implementation, only implementing computeIfAbsent since that's all the code needs.
+     * It's sized to give minimal collisions with the example test set. this may not hold true if the stations list
+     * changes, but it should still perform fairly well.
+     * It uses Open Addressing, meaning it's just one array, rather Separate Chaining which is what the default java HashMap uses.
+     * IT also uses Linear probing for collision resolution, which given the minimal collision count should hold up well.
+     */
     private static class ByteArrayKeyedMap {
         private final int BUCKET_COUNT = 0xFFF; // 413 unique stations in the data set, & 0xFFF ~= 399 (only 14 collisions (given our hashcode implementation))
         private final MeasurementAggregator[] buckets = new MeasurementAggregator[BUCKET_COUNT + 1];
         private final List<MeasurementAggregator> compactUnorderedBuckets = new ArrayList<>(413);
 
         public MeasurementAggregator computeIfAbsent(final byte[] key, final int keyLength, final int keyHashCode) {
-            int index = keyHashCode & BUCKET_COUNT;
+            var index = keyHashCode & BUCKET_COUNT;
 
             while (true) {
                 MeasurementAggregator maybe = buckets[index];
-                if (maybe == null) {
+                if (maybe != null) {
-                    final byte[] copiedKey = Arrays.copyOf(key, keyLength);
-                    MeasurementAggregator measurementAggregator = new MeasurementAggregator(copiedKey, keyHashCode);
-                    buckets[index] = measurementAggregator;
-                    compactUnorderedBuckets.add(measurementAggregator);
-                    return measurementAggregator;
-                }
-                else {
                     if (Arrays.equals(key, 0, keyLength, maybe.stationNameBytes, 0, maybe.stationNameBytes.length)) {
                         return maybe;
                     }
                     index++;
                     index &= BUCKET_COUNT;
+                } else {
+                    final var copiedKey = Arrays.copyOf(key, keyLength);
+                    MeasurementAggregator measurementAggregator = new MeasurementAggregator(copiedKey, keyHashCode);
+                    buckets[index] = measurementAggregator;
+                    compactUnorderedBuckets.add(measurementAggregator);
+                    return measurementAggregator;
                 }
             }
         }