xiangfu0 commented on code in PR #19795: URL: https://github.com/apache/pinot/pull/19795#discussion_r4244080796
########## pinot-segment-local/src/main/java/org/apache/pinot/segment/local/customobject/tdigest/PercentileTDigestAccumulator.java: ########## @@ -0,0 +1,1725 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ +/* + * Portions of the CDF, quantile, weighted-average and K1 weight-limit implementation are adapted from + * MergingDigest, AbstractTDigest and ScaleFunction in t-digest 3.3 (https://github.com/tdunning/t-digest). + * Modified for Pinot's primitive centroid storage, lazy serialized inputs and legacy boundary handling. + * Original license notice for these portions: + * + * Licensed to Ted Dunning under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.pinot.segment.local.customobject.tdigest; + +import java.nio.ByteBuffer; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.Collection; +import java.util.List; +import org.apache.pinot.segment.local.customobject.tdigest.TDigestCodec.SerializedTDigestMetadata; + + + +/// Accumulates raw values and serialized TDigests into primitive centroids using Pinot's K1 weight-limit rule. +/// +/// Raw values are sorted in small batches; serialized centroids retain their existing sorted order. Both are +/// linearly merged with accumulated centroids. K1 preserves Pinot's existing middle-quantile behavior, and the +/// legacy verbose and small encodings preserve stored data and mixed-version wire compatibility. +/// +/// Serialized state keeps its first digest pending and allocates centroid buffers only when another input must be +/// merged or the digest is queried. Raw-value buffers remain unallocated until a raw value is added. +/// +/// Historical corrupted payloads remain opaque and byte-exact, with NaN statistics. Their reported historical mass +/// may be invalid; they cannot be mutated or mixed with another distribution. Such an operation fails before +/// changing aggregate mass, because neither invented statistics nor synthetic NaN bytes are safe for old readers. +/// Unchanged historical fractional boundaries retain their original bytes, including when configured compression +/// differs. After a merge, inherited fractional endpoints retain precise verbose weights and finite statistics when +/// unit endpoints cannot preserve their mass. These keep the historical t-digest 3.3 assertion-enabled reader and +/// recompression limitation. Newly introduced unsupported fractional endpoints are rejected. +/// +/// Instances are externally serialized per aggregation or group key and are not safe for concurrent mutation. +public final class PercentileTDigestAccumulator extends TDigest { + private static final int MIN_RAW_BUFFER_SIZE = 256; + private static final int MAX_RAW_BUFFER_SIZE = 10_000; + private static final int TWO_LEVEL_COMPRESSION_MULTIPLIER = 2; + private static final int MIN_INCREMENTAL_COMPRESSION = 50; + + private final double _compression; + private final boolean _useTwoLevelRawCompression; + private final double _workingCompression; + private final double _publicMaxWeightScale; + private final double _workingMaxWeightScale; + private final int _centroidCapacity; + private final int _pendingCentroidCapacity; + private double[] _rawValues; + private double[] _centroidMeans; + private double[] _centroidWeights; + private double[] _outputMeans; + private double[] _outputWeights; + private double[] _incomingMeans; + private double[] _incomingWeights; + private double[] _sortedIncomingMeans; + private double[] _sortedIncomingWeights; + private SerializedTDigestInput _serializedTDigestInput; + private byte[] _pendingSerializedTDigest; + private byte[] _originalFractionalBytes; + private byte[] _originalBoundaryBytes; + private double _historicalFractionalMinMean = Double.NaN; + private double _historicalFractionalMaxMean = Double.NaN; + private double _freshFractionalMinMean = Double.NaN; + private double _freshFractionalMaxMean = Double.NaN; + private SerializedTDigestMetadata _pendingSerializedMetadata; + private boolean _legacyDegraded; + private boolean _hasFractionalWeights; + private boolean _deferBoundaryNormalization; + + private int _numRawValues; + private int _numCentroids; + private int _numIncomingCentroids; + private int _mergeCount; + private boolean _publiclyCompressed; + private boolean _incomingCentroidsSorted = true; + private double _totalWeight; + private double _incomingWeight; + private double _min = Double.POSITIVE_INFINITY; + private double _max = Double.NEGATIVE_INFINITY; + + public PercentileTDigestAccumulator(int compression) { + this((double) compression, true, true); + } + + public PercentileTDigestAccumulator(double compression) { + this(compression, true, true); + } + + private PercentileTDigestAccumulator(double compression, boolean allocateRawBuffer, boolean allocateMergeBuffers) { + this(compression, allocateRawBuffer, allocateMergeBuffers, false); + } + + private PercentileTDigestAccumulator(double compression, boolean allocateRawBuffer, boolean allocateMergeBuffers, + boolean useTwoLevelRawCompression) { + _compression = TDigestCodec.normalizeCompression(compression); + _useTwoLevelRawCompression = useTwoLevelRawCompression; + _workingCompression = TWO_LEVEL_COMPRESSION_MULTIPLIER * _compression; + _publicMaxWeightScale = calculateK1MaxWeightScale(_compression); + _workingMaxWeightScale = calculateK1MaxWeightScale(_workingCompression); + long roundedCompression = (long) Math.ceil(_compression); + _centroidCapacity = TDigestCodec.getDefaultCentroidCapacity(_compression); + _pendingCentroidCapacity = getPendingCentroidCapacity(_centroidCapacity, useTwoLevelRawCompression); + if (allocateRawBuffer) { + _rawValues = new double[getInitialRawBufferSize(roundedCompression)]; + } + if (allocateMergeBuffers) { + int initialCapacity = Math.min(_centroidCapacity, MIN_RAW_BUFFER_SIZE); + _centroidMeans = new double[initialCapacity]; + _centroidWeights = new double[initialCapacity]; + _outputMeans = new double[initialCapacity]; + _outputWeights = new double[initialCapacity]; + } + } + + /// Creates a lazy digest with the legacy two-level compression used by Star-tree and general digest aggregation. + public static PercentileTDigestAccumulator forLegacyAggregation(double compression) { + return new PercentileTDigestAccumulator(compression, false, false, true); + } + + /// Reads and retains one legacy digest, preserving the general aggregation compression policy. + public static PercentileTDigestAccumulator fromBytes(byte[] bytes) { + return fromBytes(ByteBuffer.wrap(bytes)); + } + + /// Reads one payload and advances the buffer past it. + public static PercentileTDigestAccumulator fromBytes(ByteBuffer bytes) { + SerializedTDigestInput input = new SerializedTDigestInput(); + input.reset(bytes); + return fromBytes(input); + } + + /// Retains an already validated input without rescanning its centroid bytes. + public static PercentileTDigestAccumulator fromBytes(SerializedTDigestInput input) { + PercentileTDigestAccumulator digest = forLegacyAggregation(input.getCompression()); + digest.addSerializedTDigest(input); + return digest; + } + + public static PercentileTDigestAccumulator forReduction(double compression) { + return new PercentileTDigestAccumulator(compression, false, false); + } + + /// Snapshots buffered inputs and centroid state without materializing or compressing the source. Mutable buffers + /// are copied; immutable retained bytes and metadata are shared. Merge and sort scratch buffers remain lazy. + PercentileTDigestAccumulator copy() { + PercentileTDigestAccumulator copy = + new PercentileTDigestAccumulator(_compression, false, false, _useTwoLevelRawCompression); + copy._rawValues = _rawValues != null ? _rawValues.clone() : null; + copy._centroidMeans = _numCentroids > 0 ? Arrays.copyOf(_centroidMeans, _numCentroids) : null; + copy._centroidWeights = _numCentroids > 0 ? Arrays.copyOf(_centroidWeights, _numCentroids) : null; + copy._incomingMeans = _numIncomingCentroids > 0 ? Arrays.copyOf(_incomingMeans, _numIncomingCentroids) : null; + copy._incomingWeights = _numIncomingCentroids > 0 ? Arrays.copyOf(_incomingWeights, _numIncomingCentroids) : null; + copy._pendingSerializedTDigest = _pendingSerializedTDigest; + copy._pendingSerializedMetadata = _pendingSerializedMetadata; + copy._originalFractionalBytes = _originalFractionalBytes; + copy._originalBoundaryBytes = _originalBoundaryBytes; + copy._historicalFractionalMinMean = _historicalFractionalMinMean; + copy._historicalFractionalMaxMean = _historicalFractionalMaxMean; + copy._freshFractionalMinMean = _freshFractionalMinMean; + copy._freshFractionalMaxMean = _freshFractionalMaxMean; + copy._legacyDegraded = _legacyDegraded; + copy._hasFractionalWeights = _hasFractionalWeights; + copy._deferBoundaryNormalization = _deferBoundaryNormalization; + copy._numRawValues = _numRawValues; + copy._numCentroids = _numCentroids; + copy._numIncomingCentroids = _numIncomingCentroids; + copy._mergeCount = _mergeCount; + copy._publiclyCompressed = _publiclyCompressed; + copy._incomingCentroidsSorted = _incomingCentroidsSorted; + copy._totalWeight = _totalWeight; + copy._incomingWeight = _incomingWeight; + copy._min = _min; + copy._max = _max; + return copy; + } + + /// Copies primitive centroids without encoding and decoding them. Zero weights are ignored, and unordered + /// means are sorted when initializing a stored, already compressed distribution; caller arrays are not mutated. + /// Subsequent inputs use the normal buffered merge. Positive weights and consistent extrema are required. + public void addCentroids(double[] means, double[] weights, int count, double min, double max, + boolean alreadyCompressed) { + addCentroids(means, weights, count, min, max, alreadyCompressed, false); + } + + /// Adds validated legacy centroids without marking their existing fractional mass as fresh input. + void addHistoricalCentroids(double[] means, double[] weights, int count, double min, double max, + boolean alreadyCompressed) { + addCentroids(means, weights, count, min, max, alreadyCompressed, true); + } + + private void addCentroids(double[] means, double[] weights, int count, double min, double max, + boolean alreadyCompressed, boolean historical) { + requireMutable(); + if (count < 0 || count > means.length || count > weights.length) { + throw new IllegalArgumentException("Invalid TDigest centroid count: " + count); + } + double totalWeight = 0.0; + int positiveCount = 0; + boolean sorted = true; + boolean fractionalWeights = false; + double previousMean = Double.NEGATIVE_INFINITY; + for (int i = 0; i < count; i++) { + double weight = weights[i]; + if (weight == 0.0) { + continue; + } + double mean = means[i]; + if (!(weight > 0.0) || !Double.isFinite(weight) || !(mean >= min && mean <= max)) { + throw new IllegalArgumentException("Invalid TDigest centroid"); + } + totalWeight += weight; + sorted &= mean >= previousMean; + previousMean = mean; + fractionalWeights |= weight != Math.rint(weight); + positiveCount++; + } + checkTotalWeight(getTotalWeight() + totalWeight); + if (positiveCount == 0) { + return; + } + prepareForMutation(); + _originalFractionalBytes = null; + _hasFractionalWeights |= fractionalWeights; + if (!historical && fractionalWeights) { + for (int i = 0; i < count; i++) { + recordFreshFractionalMean(means[i], weights[i]); + } + } + if (hasNoInputs() && alreadyCompressed) { + ensureCentroidCapacity(Math.addExact(positiveCount, 2)); + for (int i = 0; i < count; i++) { + if (weights[i] > 0.0) { + _centroidMeans[_numCentroids] = means[i]; + _centroidWeights[_numCentroids++] = weights[i]; + } + } + if (!sorted) { + sortCentroids(_centroidMeans, _centroidWeights, _numCentroids); + } + _totalWeight = totalWeight; + _min = min; + _max = max; + if (!historical) { + normalizeBoundaryCentroids(); + } + _publiclyCompressed = true; + } else { + if (sorted && positiveCount == count) { + bufferIncomingCentroids(means, weights, count, totalWeight, min, max); + } else { + // Caller-owned arrays are copied only when filtering or sorting is necessary. + double[] sortedMeans = new double[positiveCount]; + double[] sortedWeights = new double[positiveCount]; + int index = 0; + for (int i = 0; i < count; i++) { + if (weights[i] > 0.0) { + sortedMeans[index] = means[i]; + sortedWeights[index++] = weights[i]; + } + } + if (!sorted) { + sortCentroids(sortedMeans, sortedWeights, positiveCount); + } + bufferIncomingCentroids(sortedMeans, sortedWeights, positiveCount, totalWeight, min, max); + } + _min = Math.min(_min, min); + _max = Math.max(_max, max); + } + } + + public void add(double[] values, int from, int toExclusive) { + if (from >= toExclusive) { + return; + } + requireMutable(); + prepareForMutation(); + while (from < toExclusive) { + ensureRawBuffer(); + flushIfBuffersFull(true); + int numValues = Math.min(toExclusive - from, Math.min(_rawValues.length - _numRawValues, + getPendingInputLimit() - _numRawValues - _numIncomingCentroids)); + int rawOffset = _numRawValues; + for (int i = 0; i < numValues; i++) { + double value = values[from + i]; + if (Double.isNaN(value)) { + throw new IllegalArgumentException("Cannot add NaN to t-digest"); + } + _rawValues[rawOffset + i] = value; + } + _originalFractionalBytes = null; + from += numValues; + _numRawValues += numValues; + flushIfBuffersFull(!_useTwoLevelRawCompression || _rawValues.length == _pendingCentroidCapacity); + } + } + + @Override + public void add(double value) { + if (Double.isNaN(value)) { + throw new IllegalArgumentException("Cannot add NaN to t-digest"); + } + requireMutable(); + prepareForMutation(); + ensureRawBuffer(); + flushIfBuffersFull(true); + _originalFractionalBytes = null; + _rawValues[_numRawValues++] = value; + } + + @Override + public void add(double value, double weight) { + if (weight == 1) { + add(value); + return; + } + if (Double.isNaN(value)) { + throw new IllegalArgumentException("Cannot add NaN to t-digest"); + } + if (!(weight > 0.0) || !Double.isFinite(weight)) { + throw new IllegalArgumentException("TDigest weight must be positive: " + weight); + } + requireMutable(); + prepareForMutation(); + bufferIncomingCentroid(value, weight); + _originalFractionalBytes = null; + _hasFractionalWeights |= weight != Math.rint(weight); + recordFreshFractionalMean(value, weight); + _min = Math.min(_min, value); + _max = Math.max(_max, value); + } + + @Override + public void add(TDigest other) { + if (other.hasValidStatistics() && other.getTotalWeight() == 0.0) { + return; + } + requireMutable(); + if (other instanceof PercentileTDigestAccumulator) { + addAccumulator((PercentileTDigestAccumulator) other); + return; + } + if (other instanceof NonFiniteAwareTDigest) { + PercentileTDigestAccumulator finiteDigest = ((NonFiniteAwareTDigest) other).finiteDigestIfNoTails(); + if (finiteDigest != null) { + addAccumulator(finiteDigest); + return; + } + } + if (!other.hasValidStatistics()) { + materializePendingSerializedTDigest(); + SerializedTDigestInput input = getSerializedTDigestInput(); + input.reset(ByteBuffer.wrap(other.serialize()), false); + addSerializedTDigest(input); + return; + } + double otherWeight = other.getTotalWeight(); + checkTotalWeight(getTotalWeight() + otherWeight); + Collection<Centroid> centroids = other.centroids(); + boolean wrapped = other instanceof NonFiniteAwareTDigest; + int capacity = wrapped ? Math.addExact(centroids.size(), 2) : centroids.size(); + double[] means = new double[capacity]; + double[] weights = new double[capacity]; + int count = 0; + for (Centroid centroid : centroids) { + double weight = centroid.weight(); + if (weight == 0.0) { + continue; + } + if (!(weight > 0.0) || !Double.isFinite(weight) || Double.isNaN(centroid.mean())) { + throw new IllegalArgumentException("Invalid TDigest centroid"); + } + means[count] = centroid.mean(); + weights[count++] = weight; + } + if (wrapped) { + count = normalizeSerializedBoundaries(means, weights, count, other.getMin(), other.getMax()); + } + // Validate all generic centroids before changing the target, then use the same whole-source primitive path. + addCentroids(means, weights, count, other.getMin(), other.getMax(), false, wrapped); + inheritHistoricalFractionalBoundaries(other); + } + + private void addAccumulator(PercentileTDigestAccumulator other) { + if (other == this) { + compress(); + prepareForMutation(); + if (_numCentroids == 0) { + return; + } + // Snapshot only self-merges; fresh fractional mass need not be representable by a legacy wire payload. + addHistoricalCentroids(Arrays.copyOf(_centroidMeans, _numCentroids), + Arrays.copyOf(_centroidWeights, _numCentroids), _numCentroids, _min, _max, false); + return; + } + if (_deferBoundaryNormalization && !other._deferBoundaryNormalization) { + other.prepareForMutation(); + } + if (other._originalBoundaryBytes != null) { + if (getTotalWeight() != 0.0) { + throw unrepresentableBoundaryMutation(); + } + addSerializedTDigest(other._originalBoundaryBytes); + return; + } + if (other._originalFractionalBytes != null && getTotalWeight() == 0.0) { + materializePendingSerializedTDigest(); + SerializedTDigestInput input = getSerializedTDigestInput(); + input.reset(other._originalFractionalBytes); + input._retainedBytes = other._originalFractionalBytes; + addSerializedTDigest(input); + return; + } + if (other._pendingSerializedTDigest != null) { + // Materialize before resetting the reusable reader: materialization uses that same reader. + materializePendingSerializedTDigest(); + SerializedTDigestInput input = getSerializedTDigestInput(); + input.reset(other._pendingSerializedTDigest, other._pendingSerializedMetadata); + input._retainedBytes = other._pendingSerializedTDigest; + addSerializedTDigest(input); + return; + } + if (other._legacyDegraded) { + addSerializedTDigest(other.serialize()); + return; + } + + // MergingDigest compressed merge sources in place. Aggregation owns these mutable inputs exclusively. + other.compress(); + other.prepareForMutation(); + prepareForMutation(); + checkTotalWeight(_totalWeight + _incomingWeight + _numRawValues + other._totalWeight); + _hasFractionalWeights |= other._hasFractionalWeights; + inheritHistoricalFractionalBoundaries(other); + bufferIncomingCentroids(other._centroidMeans, other._centroidWeights, other._numCentroids, other._totalWeight, + other._min, other._max); + if (other._totalWeight > 0.0) { + _originalFractionalBytes = null; + } + _min = Math.min(_min, other._min); + _max = Math.max(_max, other._max); + } + + public void addSerializedTDigest(byte[] bytes) { + if (_legacyDegraded || _originalBoundaryBytes != null) { + SerializedTDigestInput input = getSerializedTDigestInput(); + input.reset(bytes); + addSerializedTDigest(input); + return; + } + requireMutable(); + materializePendingSerializedTDigest(); + SerializedTDigestInput input = getSerializedTDigestInput(); + input.reset(bytes); + addSerializedTDigest(input); + } + + private SerializedTDigestInput getSerializedTDigestInput() { + if (_serializedTDigestInput == null) { + _serializedTDigestInput = new SerializedTDigestInput(); + } + return _serializedTDigestInput; + } + + public void addSerializedTDigest(SerializedTDigestInput input) { + if (ignoreEmptyInputForDegradedState(input)) { + return; + } + requireMutable(); + if (prepareSerializedTDigest(input)) { + mergeSerializedTDigest(input, false); + } + } + + public void addSerializedTDigestDirect(SerializedTDigestInput input) { + if (ignoreEmptyInputForDegradedState(input)) { + return; + } + requireMutable(); + if (prepareSerializedTDigest(input)) { + mergeSerializedTDigest(input, true); + } + } + + private boolean ignoreEmptyInputForDegradedState(SerializedTDigestInput input) { + if (!_legacyDegraded && _originalBoundaryBytes == null + && (_pendingSerializedMetadata == null || !_pendingSerializedMetadata.weightedBoundaries())) { + return false; + } + input.inspectMetadata(); + return !input._metadata._needsLegacyFallback && input._metadata._totalWeight == 0.0; + } + + private boolean prepareSerializedTDigest(SerializedTDigestInput input) { + if (_pendingSerializedTDigest == null && hasNoInputs()) { + input.inspectMetadata(); + _hasFractionalWeights |= input._metadata._fractionalWeights; + _pendingSerializedTDigest = input.retainBytes(); + _pendingSerializedMetadata = input.getMetadata(); + if (input.recordHistoricalFractionalBoundaries(this)) { + // Alias the retained snapshot; historical fractional bytes remain byte-exact after read-only materialization. + _originalFractionalBytes = _pendingSerializedTDigest; + } + if (input._metadata._needsLegacyFallback) { + _legacyDegraded = true; + } + return false; + } + materializePendingSerializedTDigest(); + input.decode(); + if (input._metadata._needsLegacyFallback) { + if (hasNoInputs()) { + _pendingSerializedTDigest = input.retainBytes(); + _pendingSerializedMetadata = input.getMetadata(); + _legacyDegraded = true; + return false; + } + throw corruptedMutation(); + } + if (!_deferBoundaryNormalization) { + input.normalizeBoundaries(); + } + prepareForMutation(); + checkTotalWeight(_totalWeight + _incomingWeight + _numRawValues + input._metadata._totalWeight); + input.recordHistoricalFractionalBoundaries(this); + if (input._metadata._totalWeight > 0.0) { + _originalFractionalBytes = null; + } + _hasFractionalWeights |= input._metadata._fractionalWeights; + return true; + } + + private boolean hasNoInputs() { + return _numCentroids == 0 && _totalWeight == 0.0 && _numRawValues == 0 && _numIncomingCentroids == 0; + } + + private void mergeSerializedTDigest(SerializedTDigestInput input, boolean direct) { + if (input._metadata._totalWeight == 0.0) { + return; + } + if (hasNoInputs()) { + ensureCentroidCapacity(input._numCentroids); + System.arraycopy(input._means, 0, _centroidMeans, 0, input._numCentroids); + System.arraycopy(input._weights, 0, _centroidWeights, 0, input._numCentroids); + _numCentroids = input._numCentroids; + _totalWeight = input._metadata._totalWeight; + _min = input._metadata._min; + _max = input._metadata._max; + // Stored centroids already went through the writer's public compression. Reading or repairing their + // endpoints needs another K1 pass only when the output compression differs from the stored compression. + _publiclyCompressed = _compression == input._metadata._compression; + return; + } + if (direct) { + flush(); + boolean runBackwards = (_mergeCount++ & 1) != 0; + if (!mergeSorted(input._means, input._weights, input._numCentroids, input._metadata._totalWeight, + getIncrementalCompression(), runBackwards)) { + return; + } + } else { + bufferIncomingCentroids(input._means, input._weights, input._numCentroids, input._metadata._totalWeight, + input._metadata._min, input._metadata._max); + } + _min = Math.min(_min, input._metadata._min); + _max = Math.max(_max, input._metadata._max); + } + + @Override + public void compress() { + if (_legacyDegraded) { + return; + } + materializePendingSerializedTDigest(); + if (_useTwoLevelRawCompression) { + // Public compression and serialization both retain the legacy working pass before final compression. + flush(); + } + if (_numRawValues > 0 || _numIncomingCentroids > 0) { + // SQL reduction combines pending values and existing centroids directly at public compression, matching + // MergingDigest 3.3. Its writer avoids an extra working-compression pass that can increase reducer rank error. + flush(_compression); + _publiclyCompressed = true; + } else if (!_publiclyCompressed && _numCentroids > 0) { + recompressCentroids(_compression); + _publiclyCompressed = true; + } + } + + @Override + public boolean hasValidStatistics() { + return !_legacyDegraded; + } + + @Override + public double getTotalWeight() { + return _pendingSerializedTDigest != null ? _pendingSerializedMetadata.totalWeight() + : _totalWeight + _incomingWeight + _numRawValues; + } + + /// Bounds serialized output centroids from buffered inputs, including up to two boundary splits before a merge + /// and two more before writing, without flushing or using the potentially huge input mass. + public long getCentroidCountUpperBound() { + return _pendingSerializedTDigest != null ? (long) _pendingSerializedMetadata.centroidCount() + 4L + : (long) _numCentroids + _numRawValues + _numIncomingCentroids + 4L; + } + + /// Whether unchanged historical fractional boundaries still require their original byte representation. + public boolean hasOriginalFractionalPayload() { + return _originalFractionalBytes != null; + } + + @Override + public double cdf(double value) { + if (Double.isNaN(value) || Double.isInfinite(value)) { + throw new IllegalArgumentException(String.format("Invalid value: %f", value)); + } + if (_legacyDegraded) { + return Double.NaN; + } + materializePendingSerializedTDigest(); + flush(); + if (_numCentroids == 0) { + return Double.NaN; + } + if (_numCentroids == 1) { + double width = _max - _min; + if (value < _min) { + return 0.0; + } else if (value > _max) { + return 1.0; + } else if (value - _min <= width) { + return 0.5; + } else { + return (value - _min) / width; + } + } + if (value < _min) { + return 0.0; + } + if (value > _max) { + return 1.0; + } + if (value < _centroidMeans[0]) { + double width = _centroidMeans[0] - _min; + if (width > 0.0) { + if (_centroidWeights[0] < 1.0) { + return (_centroidWeights[0] / 2.0 * (value - _min) / width) / _totalWeight; + } + return value == _min ? 0.5 / _totalWeight + : (1.0 + (value - _min) / width * (_centroidWeights[0] / 2.0 - 1.0)) / _totalWeight; + } + return 0.0; + } + int lastIndex = _numCentroids - 1; + if (value > _centroidMeans[lastIndex]) { + double width = _max - _centroidMeans[lastIndex]; + if (width > 0.0) { + if (_centroidWeights[lastIndex] < 1.0) { + return 1.0 - (_centroidWeights[lastIndex] / 2.0 * (_max - value) / width) / _totalWeight; + } + return value == _max ? 1.0 - 0.5 / _totalWeight + : 1.0 - (1.0 + (_max - value) / width * (_centroidWeights[lastIndex] / 2.0 - 1.0)) + / _totalWeight; + } + return 1.0; + } + + double weightSoFar = 0.0; + for (int i = 0; i < lastIndex; i++) { + if (_centroidMeans[i] == value) { + double equalWeight = 0.0; + int equalIndex = i; + while (equalIndex < _numCentroids && _centroidMeans[equalIndex] == value) { + equalWeight += _centroidWeights[equalIndex]; + equalIndex++; + } + return (weightSoFar + equalWeight / 2.0) / _totalWeight; + } + if (_centroidMeans[i] <= value && _centroidMeans[i + 1] > value) { + if (!Double.isFinite(_centroidMeans[i]) || !Double.isFinite(_centroidMeans[i + 1])) { + if (_centroidMeans[i] == Double.NEGATIVE_INFINITY) { + return (weightSoFar + _centroidWeights[i]) / _totalWeight; + } + if (_centroidWeights[i] == 1.0 && _centroidWeights[i + 1] == 1.0) { + return (weightSoFar + 1.0) / _totalWeight; + } + double leftExcludedWeight = _centroidWeights[i] == 1.0 ? 0.5 : 0.0; + double rightExcludedWeight = _centroidWeights[i + 1] == 1.0 ? 0.5 : 0.0; + double interpolatedWeight = (_centroidWeights[i] + _centroidWeights[i + 1]) / 2.0 + - leftExcludedWeight - rightExcludedWeight; + double base = weightSoFar + _centroidWeights[i] / 2.0 + leftExcludedWeight; + return (base + interpolatedWeight * (value - _centroidMeans[i]) + / (_centroidMeans[i + 1] - _centroidMeans[i])) / _totalWeight; + } + double width = _centroidMeans[i + 1] - _centroidMeans[i]; + if (width > 0.0) { + double leftExcludedWeight = getPointMassHalfWeight(i); + double rightExcludedWeight = getPointMassHalfWeight(i + 1); + double halfWeight = (_centroidWeights[i] + _centroidWeights[i + 1]) / 2.0; + double interpolatedWeight = halfWeight - leftExcludedWeight - rightExcludedWeight; + double base = weightSoFar + _centroidWeights[i] / 2.0 + leftExcludedWeight; + return (base + interpolatedWeight * (value - _centroidMeans[i]) / width) / _totalWeight; + } + return (weightSoFar + (_centroidWeights[i] + _centroidWeights[i + 1]) / 2.0) / _totalWeight; + } + weightSoFar += _centroidWeights[i]; + } + if (value == _centroidMeans[lastIndex]) { + return 1.0 - Math.min(1.0, _centroidWeights[lastIndex]) / 2.0 / _totalWeight; + } + throw new IllegalStateException("Unable to compute TDigest CDF"); + } + + @Override + public double quantile(double quantile) { + if (Double.isNaN(quantile) || quantile < 0.0 || quantile > 1.0) { + throw new IllegalArgumentException("q should be in [0,1], got " + quantile); + } + if (_legacyDegraded) { + return Double.NaN; + } + materializePendingSerializedTDigest(); + flush(); + if (_numCentroids == 0) { + return Double.NaN; + } + if (_numCentroids == 1) { + return _centroidMeans[0]; + } + if (quantile == 0.0) { + return _min; + } + if (quantile == 1.0) { + return _max; + } + + double index = quantile * _totalWeight; + double firstWeight = _centroidWeights[0]; + if (firstWeight < 1.0 && index < firstWeight / 2.0) { + return weightedAverage(_min, firstWeight / 2.0 - index, _centroidMeans[0], index); + } + if (firstWeight >= 1.0 && index < 1.0) { + return _min; + } + if (_centroidWeights[0] > 1.0 && index < _centroidWeights[0] / 2.0) { + return _min + (index - 1.0) / (_centroidWeights[0] / 2.0 - 1.0) * (_centroidMeans[0] - _min); + } + int lastIndex = _numCentroids - 1; + double lastWeight = _centroidWeights[lastIndex]; + if (lastWeight < 1.0 && index >= _totalWeight - lastWeight / 2.0) { + return weightedAverage(_centroidMeans[lastIndex], _totalWeight - index, _max, + index - (_totalWeight - lastWeight / 2.0)); + } + if (lastWeight >= 1.0 && index > _totalWeight - 1.0) { + return _max; + } + if (_centroidWeights[lastIndex] > 1.0 + && _totalWeight - index <= _centroidWeights[lastIndex] / 2.0) { + return _max - (_totalWeight - index - 1.0) / (_centroidWeights[lastIndex] / 2.0 - 1.0) + * (_max - _centroidMeans[lastIndex]); + } + + double weightSoFar = _centroidWeights[0] / 2.0; + for (int i = 0; i < lastIndex; i++) { + double halfWeight = (_centroidWeights[i] + _centroidWeights[i + 1]) / 2.0; + if (weightSoFar + halfWeight > index) { + double leftExcludedWeight = getPointMassHalfWeight(i); + if (index - weightSoFar < leftExcludedWeight) { + return _centroidMeans[i]; + } + double rightExcludedWeight = getPointMassHalfWeight(i + 1); + if (weightSoFar + halfWeight - index <= rightExcludedWeight) { + return _centroidMeans[i + 1]; + } + double leftWeight = index - weightSoFar - leftExcludedWeight; + double rightWeight = weightSoFar + halfWeight - index - rightExcludedWeight; + return weightedAverage(_centroidMeans[i], rightWeight, _centroidMeans[i + 1], leftWeight); + } + weightSoFar += halfWeight; + } + // Rounded cumulative weights can leave a small gap before the directly computed last centroid center. + double weightToMax = Math.max(0.0, index - (_totalWeight - lastWeight / 2.0)); + double weightFromLastCentroid = lastWeight / 2.0 - weightToMax; + return weightedAverage(_centroidMeans[lastIndex], weightFromLastCentroid, _max, weightToMax); + } + + private double getPointMassHalfWeight(int index) { + // Adjacent equal means establish a repeated-value plateau. Keep its complete mass out of interpolation at + // either edge; an isolated weighted centroid still represents an unknown distribution around its mean. + double mean = _centroidMeans[index]; + boolean pointMass = _centroidWeights[index] == 1.0 || index > 0 && _centroidMeans[index - 1] == mean + || index + 1 < _numCentroids && _centroidMeans[index + 1] == mean; + return pointMass ? _centroidWeights[index] / 2.0 : 0.0; + } + + private static double weightedAverage(double firstValue, double firstWeight, double secondValue, + double secondWeight) { + if (firstValue > secondValue) { + return weightedAverage(secondValue, secondWeight, firstValue, firstWeight); + } + if (firstWeight == 0.0) { + return secondValue; + } + if (secondWeight == 0.0 || firstValue == secondValue) { + return firstValue; + } + if (!Double.isFinite(firstValue)) { + return firstValue; + } + if (!Double.isFinite(secondValue)) { + return secondValue; + } + double average = (firstValue * firstWeight + secondValue * secondWeight) / (firstWeight + secondWeight); + return Math.max(firstValue, Math.min(average, secondValue)); + } + + @Override + public Collection<Centroid> centroids() { + if (_legacyDegraded) { + byte[] bytes = serialize(); + ByteBuffer encoded = ByteBuffer.wrap(bytes); + SerializedTDigestMetadata metadata = TDigestCodec.readSerializedHeader(encoded); + encoded.position(metadata.centroidOffset()); + List<Centroid> centroids = new ArrayList<>(metadata.centroidCount()); + // Expose degraded historical centroids verbatim, without the healthy decoder's endpoint clamp. + // Their original bytes and NaN statistics must remain intact instead of implying a repaired distribution. + for (int i = 0; i < metadata.centroidCount(); i++) { + double weight = metadata.centroidSize() == TDigestCodec.VERBOSE_CENTROID_SIZE + ? encoded.getDouble() : encoded.getFloat(); + double mean = metadata.centroidSize() == TDigestCodec.VERBOSE_CENTROID_SIZE + ? encoded.getDouble() : encoded.getFloat(); + centroids.add(new Centroid(mean, weight)); + } + return centroids; + } + materializePendingSerializedTDigest(); + flush(); + List<Centroid> centroids = new ArrayList<>(_numCentroids); + for (int i = 0; i < _numCentroids; i++) { + centroids.add(new Centroid(_centroidMeans[i], _centroidWeights[i])); + } + return centroids; + } + + /// Copies a valid distribution's primitive centroid arrays after flushing buffered inputs. This does not apply + /// public compression or serialize a finite sub-distribution; callers can include surrounding infinity mass. + public void copyCentroids(double[] means, double[] weights, int offset) { + if (_legacyDegraded) { + throw corruptedMutation(); + } + materializePendingSerializedTDigest(); + flush(); + if (means == weights || offset < 0 || offset > means.length - _numCentroids + || offset > weights.length - _numCentroids) { + throw new IllegalArgumentException("Insufficient distinct TDigest centroid arrays"); + } + if (_numCentroids == 0) { + return; + } + System.arraycopy(_centroidMeans, 0, means, offset, _numCentroids); + System.arraycopy(_centroidWeights, 0, weights, offset, _numCentroids); + } + + @Override + public double compression() { + return _compression; + } + + /// Bounds compatible output without flushing. Unchanged historical bytes and retained pending payloads can + /// exceed the newly encoded legacy-capacity bound and retain their actual length. + @Override + public int maxSerializedByteSize() { + if (_legacyDegraded) { + return _pendingSerializedTDigest.length; + } + if (_originalFractionalBytes != null) { + return _originalFractionalBytes.length; + } + if (_originalBoundaryBytes != null) { + return _originalBoundaryBytes.length; + } + long centroidCount = getCentroidCountUpperBound(); + if (!_hasFractionalWeights) { + centroidCount = (long) Math.min(centroidCount, Math.ceil(getTotalWeight())); + } + int maximumBytes = TDigestCodec.getMaxLegacyCompatibleByteSize(_compression, centroidCount); + return _pendingSerializedTDigest != null ? Math.max(maximumBytes, _pendingSerializedTDigest.length) : maximumBytes; + } + + /// Returns the centroid view's count, including repaired endpoints and excluding zero-mass serialized entries. + @Override + public int centroidCount() { + if (_pendingSerializedTDigest != null) { + if (_legacyDegraded) { + return _pendingSerializedMetadata.centroidCount(); + } + if (_pendingSerializedMetadata.isCanonicalPayload()) { + return _pendingSerializedMetadata.centroidCount(); + } + materializePendingSerializedTDigest(); + } + flush(); + return _numCentroids; + } + + @Override + public double getMin() { + if (_pendingSerializedTDigest != null) { + return !_legacyDegraded && _pendingSerializedMetadata.totalWeight() == 0.0 + ? Double.POSITIVE_INFINITY : _pendingSerializedMetadata.min(); + } + flush(); + return _min; + } + + @Override + public double getMax() { + if (_pendingSerializedTDigest != null) { + return !_legacyDegraded && _pendingSerializedMetadata.totalWeight() == 0.0 + ? Double.NEGATIVE_INFINITY : _pendingSerializedMetadata.max(); + } + flush(); + return _max; + } + + @Override + public byte[] serialize() { + if (_legacyDegraded) { + return _pendingSerializedTDigest.clone(); + } + if (_originalFractionalBytes != null) { + return _originalFractionalBytes.clone(); + } + if (_originalBoundaryBytes != null) { + return _originalBoundaryBytes.clone(); + } + if (_pendingSerializedTDigest != null) { + if (!_pendingSerializedMetadata.isCanonicalPayload()) { + materializePendingSerializedTDigest(); + } else { + if (ByteBuffer.wrap(_pendingSerializedTDigest).getInt() == TDigestCodec.VERBOSE_ENCODING) { + byte[] serialized = TDigestCodec.makeLegacyCompatible(_pendingSerializedTDigest, _pendingSerializedMetadata); + return serialized == _pendingSerializedTDigest ? serialized.clone() : serialized; + } + return _pendingSerializedTDigest.clone(); + } + } + if (_originalBoundaryBytes != null) { + return _originalBoundaryBytes.clone(); + } + compress(); + normalizeBoundaryCentroids(); + checkFractionalBoundaryEncoding(); + return TDigestCodec.serializeCompatibleCentroids(_compression, _min, _max, _centroidMeans, _centroidWeights, + _numCentroids, hasInheritedFractionalBoundaryEncoding()); + } + + private void recompressCentroids(double compression) { + normalizeBoundaryCentroids(); + double[] means = _centroidMeans; + double[] weights = _centroidWeights; + int numCentroids = _numCentroids; + double totalWeight = _totalWeight; + _numCentroids = 0; + _totalWeight = 0.0; + boolean runBackwards = (_mergeCount++ & 1) != 0; + if (!mergeSorted(means, weights, numCentroids, totalWeight, compression, runBackwards)) { + throw new IllegalStateException("Cannot recompress an empty TDigest"); + } + } + + private void checkFractionalBoundaryEncoding() { + if (_numCentroids > 0 && !hasInheritedFractionalBoundaryEncoding()) { + TDigestCodec.checkLegacyBoundaryWeights(_numCentroids, _centroidWeights[0], _centroidWeights[_numCentroids - 1]); + } + } + + private boolean hasInheritedFractionalBoundaryEncoding() { + return hasInheritedFractionalBoundaryEncoding(_centroidMeans, _centroidWeights, _numCentroids); + } + + /// Applies the canonical inherited-endpoint check to a complete digest's sorted centroid view. Enclosing writers + /// use this after adding their infinity tails; unsupported fresh global endpoints never inherit permission. + boolean hasInheritedFractionalBoundaryEncoding(double[] means, double[] weights, int count) { + if (count < 0 || count > 0 && (count > means.length || count > weights.length)) { + throw new IllegalArgumentException("Invalid TDigest centroid count: " + count); + } + if (count == 0) { + return false; + } + return TDigestCodec.hasInheritedFractionalBoundaryEncoding(this, count, means[0], weights[0], + means[count - 1], weights[count - 1]); + } + + @Override + double getHistoricalFractionalBoundaryMean(boolean lowerBoundary) { + return lowerBoundary ? _historicalFractionalMinMean : _historicalFractionalMaxMean; + } + + @Override + double getFreshFractionalBoundaryMean(boolean lowerBoundary) { + return lowerBoundary ? _freshFractionalMinMean : _freshFractionalMaxMean; + } + + void recordFreshFractionalMean(double mean, double weight) { + if (weight != Math.rint(weight)) { + inheritFreshFractionalMeans(mean, mean); + } + } + + private void inheritFreshFractionalMeans(double minMean, double maxMean) { + if (!Double.isNaN(minMean)) { + _freshFractionalMinMean = Double.isNaN(_freshFractionalMinMean) ? minMean + : Math.min(_freshFractionalMinMean, minMean); + } + if (!Double.isNaN(maxMean)) { + _freshFractionalMaxMean = Double.isNaN(_freshFractionalMaxMean) ? maxMean + : Math.max(_freshFractionalMaxMean, maxMean); + } + } + + /// Propagates provenance from a validated source without exposing arbitrary endpoint setters. + void inheritHistoricalFractionalBoundaries(TDigest source) { + requireMutable(); + inheritFreshFractionalMeans(source.getFreshFractionalBoundaryMean(true), + source.getFreshFractionalBoundaryMean(false)); + inheritHistoricalFractionalBoundaries(source.getHistoricalFractionalBoundaryMean(true), + source.getHistoricalFractionalBoundaryMean(false)); + } + + void inheritHistoricalFractionalBoundaries(double minMean, double maxMean) { + if (!Double.isNaN(minMean)) { + _historicalFractionalMinMean = Double.isNaN(_historicalFractionalMinMean) ? minMean + : Math.min(_historicalFractionalMinMean, minMean); + } + if (!Double.isNaN(maxMean)) { + _historicalFractionalMaxMean = Double.isNaN(_historicalFractionalMaxMean) ? maxMean + : Math.max(_historicalFractionalMaxMean, maxMean); + } + } + + private void flush() { + // SQL accumulators merge raw inputs incrementally at configured compression. General digest aggregation keeps + // the legacy two-level raw merge, preserving sparse Star-tree query accuracy. Incremental buffer exhaustion or + // centroid/statistics reads use working compression for reducer inputs; final serialization bypasses that pass. + flush(_numIncomingCentroids == 0 && !_useTwoLevelRawCompression + ? getIncrementalCompression() + : _workingCompression); + } + + private double getIncrementalCompression() { + // Very low compression leaves too little centroid headroom for incremental public-compression merges to retain + // t-digest 3.3's accuracy. Keep the two-level strategy for those uncommon configurations. + return _compression >= MIN_INCREMENTAL_COMPRESSION ? _compression : _workingCompression; + } + + private void flush(double compression) { + if (_numIncomingCentroids > 0) { + flushIncoming(compression); + return; + } + if (_numRawValues == 0) { + return; + } + + Arrays.sort(_rawValues, 0, _numRawValues); + double rawMin = _rawValues[0]; + double rawMax = _rawValues[_numRawValues - 1]; + boolean runBackwards = (_mergeCount++ & 1) != 0; + mergeSorted(_rawValues, null, _numRawValues, _numRawValues, compression, runBackwards); + _numRawValues = 0; + _min = Math.min(_min, rawMin); + _max = Math.max(_max, rawMax); + } + + private void flushIncoming(double compression) { + // Match mergeSorted's association before rearranging raw or paired centroid buffers. + checkTotalWeight(_totalWeight + (_incomingWeight + _numRawValues)); + double rawMin = Double.POSITIVE_INFINITY; + double rawMax = Double.NEGATIVE_INFINITY; + if (_numRawValues > 0) { + Arrays.sort(_rawValues, 0, _numRawValues); + rawMin = _rawValues[0]; + rawMax = _rawValues[_numRawValues - 1]; + ensureIncomingCapacity(Math.addExact(_numIncomingCentroids, _numRawValues)); + System.arraycopy(_incomingMeans, 0, _incomingMeans, _numRawValues, _numIncomingCentroids); + System.arraycopy(_incomingWeights, 0, _incomingWeights, _numRawValues, _numIncomingCentroids); + for (int i = 0; i < _numRawValues; i++) { + _incomingMeans[i] = _rawValues[i]; + _incomingWeights[i] = 1.0; + } + _numIncomingCentroids += _numRawValues; + _incomingWeight += _numRawValues; + _numRawValues = 0; + _incomingCentroidsSorted = false; + } + + int incomingCount = _numIncomingCentroids; + double incomingWeight = _incomingWeight; + double[] incomingMeans = _incomingMeans; + double[] incomingWeights = _incomingWeights; + if (!_incomingCentroidsSorted) { + ensureSortedIncomingCapacity(incomingCount); + stableSortIncoming(incomingCount); + incomingMeans = _incomingMeans; + incomingWeights = _incomingWeights; + _incomingCentroidsSorted = true; + } + boolean runBackwards = (_mergeCount & 1) != 0; + if (!mergeSorted(incomingMeans, incomingWeights, incomingCount, incomingWeight, compression, runBackwards)) { + throw new IllegalStateException("Cannot flush an empty TDigest input buffer"); + } + _mergeCount++; + _numIncomingCentroids = 0; + _incomingWeight = 0.0; + _incomingCentroidsSorted = true; + _min = Math.min(_min, rawMin); + _max = Math.max(_max, rawMax); + } + + private boolean mergeSorted(double[] incomingMeans, double[] incomingWeights, int incomingCount, + double incomingWeight, double compression, boolean runBackwards) { + if (incomingWeight == 0.0) { + return false; + } + + double newTotalWeight = _totalWeight + incomingWeight; + checkTotalWeight(newTotalWeight); + normalizeBoundaryCentroids(); + int preferredOutputCapacity = getPreferredOutputCapacity(incomingCount); + ensureOutputCapacity(1); + double totalWeightNormalizer = 1.0 / newTotalWeight; + double weightNormalizer = totalWeightNormalizer / getK1MaxWeightScale(compression); + int incomingIndex = runBackwards ? incomingCount - 1 : 0; + int centroidIndex = runBackwards ? _numCentroids - 1 : 0; + int incomingLimit = runBackwards ? -1 : incomingCount; + int centroidLimit = runBackwards ? -1 : _numCentroids; + int direction = runBackwards ? -1 : 1; + int numInputs = incomingCount + _numCentroids; + int inputIndex = 0; + int numOutputCentroids = 0; + double weightSoFar = 0.0; + double firstInputMean = _numCentroids == 0 ? incomingMeans[0] + : Math.min(incomingMeans[0], _centroidMeans[0]); + double lastInputMean = _numCentroids == 0 ? incomingMeans[incomingCount - 1] + : Math.max(incomingMeans[incomingCount - 1], _centroidMeans[_numCentroids - 1]); + boolean allFiniteMeans = Double.isFinite(firstInputMean) && Double.isFinite(lastInputMean); + boolean sameSignMeans = firstInputMean > 0.0 || lastInputMean < 0.0; + while (incomingIndex != incomingLimit || centroidIndex != centroidLimit) { + double mean; + double weight; + boolean takeIncoming = centroidIndex == centroidLimit || (incomingIndex != incomingLimit + && (runBackwards ? incomingMeans[incomingIndex] > _centroidMeans[centroidIndex] + : incomingMeans[incomingIndex] <= _centroidMeans[centroidIndex])); + if (takeIncoming) { + mean = incomingMeans[incomingIndex]; + weight = incomingWeights == null ? 1.0 : incomingWeights[incomingIndex]; + incomingIndex += direction; + } else { + mean = _centroidMeans[centroidIndex]; + weight = _centroidWeights[centroidIndex]; + centroidIndex += direction; + } + if (numOutputCentroids == 0) { + _outputMeans[0] = mean; + _outputWeights[0] = weight; + numOutputCentroids = 1; + } else { + int currentIndex = numOutputCentroids - 1; + double proposedWeight = _outputWeights[currentIndex] + weight; + double q0 = weightSoFar * totalWeightNormalizer; + double q2 = (weightSoFar + proposedWeight) * totalWeightNormalizer; + double normalizedWeight = proposedWeight * weightNormalizer; + double normalizedWeightSquared = normalizedWeight * normalizedWeight; + boolean canMerge = (allFiniteMeans || canMergeMeans(_outputMeans[currentIndex], mean)) + && normalizedWeightSquared <= q0 * (1.0 - q0) + && normalizedWeightSquared <= q2 * (1.0 - q2); + if (inputIndex == 1 || inputIndex == numInputs - 1) { + canMerge = false; + } + if (canMerge) { + _outputWeights[currentIndex] = proposedWeight; + _outputMeans[currentIndex] = + TDigestCodec.weightedMean(_outputMeans[currentIndex], proposedWeight - weight, mean, weight, + proposedWeight, sameSignMeans); + } else { + weightSoFar += _outputWeights[currentIndex]; + ensureOutputCapacity(Math.max(preferredOutputCapacity, numOutputCentroids + 1)); + _outputMeans[numOutputCentroids] = mean; + _outputWeights[numOutputCentroids] = weight; + numOutputCentroids++; + } + } + inputIndex++; + } + if (runBackwards) { + reverse(_outputMeans, numOutputCentroids); + reverse(_outputWeights, numOutputCentroids); + } + finishMerge(numOutputCentroids, newTotalWeight, compression); + return true; + } + + private void finishMerge(int numOutputCentroids, double totalWeight, double compression) { + double[] temporary = _centroidMeans; + _centroidMeans = _outputMeans; + _outputMeans = temporary; + temporary = _centroidWeights; + _centroidWeights = _outputWeights; + _outputWeights = temporary; + _numCentroids = numOutputCentroids; + _totalWeight = totalWeight; + _publiclyCompressed = compression == _compression; + } + + private void ensureIncomingCapacity(int capacity) { + if (_incomingMeans == null || capacity > _incomingMeans.length) { + int newCapacity = _incomingMeans == null + ? Math.max(capacity, Math.min(_centroidCapacity, _pendingCentroidCapacity)) + : Math.max(capacity, (int) Math.min(_pendingCentroidCapacity, + (long) _incomingMeans.length * TDigestCodec.DEFAULT_MERGE_BUFFER_MULTIPLIER)); + _incomingMeans = _incomingMeans == null ? new double[newCapacity] : Arrays.copyOf(_incomingMeans, newCapacity); + _incomingWeights = + _incomingWeights == null ? new double[newCapacity] : Arrays.copyOf(_incomingWeights, newCapacity); + } + } + + private void stableSortIncoming(int count) { + if (stableSortCentroids(_incomingMeans, _incomingWeights, _sortedIncomingMeans, _sortedIncomingWeights, count, + false)) { + double[] temporary = _incomingMeans; + _incomingMeans = _sortedIncomingMeans; + _sortedIncomingMeans = temporary; + temporary = _incomingWeights; + _incomingWeights = _sortedIncomingWeights; + _sortedIncomingWeights = temporary; + } + } + + // Returns whether the result is in the scratch arrays. The hot merge path retains numeric-equal input order, + // including signed zeros; stored payload repair requires Double.compare's total ordering (including NaNs). + private static boolean stableSortCentroids(double[] means, double[] weights, double[] scratchMeans, + double[] scratchWeights, int count, boolean totalOrder) { + double[] sourceMeans = means; + double[] sourceWeights = weights; + double[] destinationMeans = scratchMeans; + double[] destinationWeights = scratchWeights; + for (int width = 1; width < count; width *= 2) { + for (int start = 0; start < count; start += 2 * width) { + int middle = Math.min(start + width, count); + int end = Math.min(start + 2 * width, count); + int left = start; + int right = middle; + int output = start; + while (left < middle && right < end) { + boolean leftFirst = totalOrder ? Double.compare(sourceMeans[left], sourceMeans[right]) <= 0 + : sourceMeans[left] <= sourceMeans[right]; + int source = leftFirst ? left++ : right++; + destinationMeans[output] = sourceMeans[source]; + destinationWeights[output++] = sourceWeights[source]; + } + int remaining = left < middle ? middle - left : end - right; + int source = left < middle ? left : right; + System.arraycopy(sourceMeans, source, destinationMeans, output, remaining); + System.arraycopy(sourceWeights, source, destinationWeights, output, remaining); + } + double[] temporary = sourceMeans; + sourceMeans = destinationMeans; + destinationMeans = temporary; + temporary = sourceWeights; + sourceWeights = destinationWeights; + destinationWeights = temporary; + } + return sourceMeans != means; + } + + private void ensureSortedIncomingCapacity(int capacity) { + if (_sortedIncomingMeans == null || capacity > _sortedIncomingMeans.length) { + int newCapacity = _sortedIncomingMeans == null + ? Math.max(capacity, Math.min(_centroidCapacity, _pendingCentroidCapacity)) + : Math.max(capacity, Math.multiplyExact(_sortedIncomingMeans.length, 2)); + _sortedIncomingMeans = new double[newCapacity]; + _sortedIncomingWeights = new double[newCapacity]; + } + } + + private void bufferIncomingCentroid(double mean, double weight) { + checkTotalWeight(_totalWeight + _incomingWeight + _numRawValues + weight); + // The caller will widen global extrema after buffering. Repair materialized endpoints against their own + // existing bounds first, so a later merge cannot move old point mass to a newly introduced extreme. + normalizeBoundaryCentroids(); + flushIfBuffersFull(false); + ensureIncomingCapacity(_numIncomingCentroids + 1); + if (_incomingCentroidsSorted && _numIncomingCentroids > 0 + && mean < _incomingMeans[_numIncomingCentroids - 1]) { + _incomingCentroidsSorted = false; + } + _incomingMeans[_numIncomingCentroids] = mean; + _incomingWeights[_numIncomingCentroids] = weight; + _numIncomingCentroids++; + _incomingWeight += weight; + } + + private void bufferIncomingCentroids(double[] means, double[] weights, int count, double totalWeight, + double min, double max) { + if (count == 0) { + return; + } + checkTotalWeight(_totalWeight + (_incomingWeight + _numRawValues + totalWeight)); + normalizeBoundaryCentroids(); + boolean canSplitSource = count <= getPendingInputLimit() && weights[0] == 1.0 && weights[count - 1] == 1.0 + && means[0] == min && means[count - 1] == max; + if (!canSplitSource && count > getPendingInputLimit() - _numRawValues - _numIncomingCentroids) { + // Sources without identifiable unit endpoints, or larger than a whole batch, are merged in one pass. + flush(); + if (count > getPendingInputLimit()) { + boolean runBackwards = (_mergeCount++ & 1) != 0; + mergeSorted(means, weights, count, totalWeight, + _useTwoLevelRawCompression ? _workingCompression : getIncrementalCompression(), runBackwards); + _min = Math.min(_min, min); + _max = Math.max(_max, max); + return; + } + } + int offset = 0; + while (offset < count) { + flushIfBuffersFull(false); + // A previous prefix can end inside a weighted source. Repair it using only its consumed bounds before + // the next prefix widens those bounds; the source's full extrema are used only at its actual endpoints. + normalizeBoundaryCentroids(); + int copied = Math.min(count - offset, + getPendingInputLimit() - _numRawValues - _numIncomingCentroids); + int existingCount = _numIncomingCentroids; + int combinedCount = Math.addExact(existingCount, copied); + ensureIncomingCapacity(combinedCount); + if (existingCount == 0 || !_incomingCentroidsSorted) { + System.arraycopy(means, offset, _incomingMeans, existingCount, copied); + System.arraycopy(weights, offset, _incomingWeights, existingCount, copied); + } else { + int existingIndex = existingCount - 1; + int addedIndex = offset + copied - 1; + int outputIndex = combinedCount - 1; + while (existingIndex >= 0 && addedIndex >= offset) { + if (_incomingMeans[existingIndex] > means[addedIndex]) { + _incomingMeans[outputIndex] = _incomingMeans[existingIndex]; Review Comment: **[review] Chunk-boundary flushes can manufacture an artificial plateau from an interior weighted centroid.** When a mid-source chunk flush lands so that the last copied centroid is a weighted interior centroid of a `canSplitSource` source and its mean exceeds the prior `_max`, `_max` becomes that centroid's own mean and `normalizeBoundaryCentroids` splits it into `(m, w-1) + (m, 1)`. `getPointMassHalfWeight` then treats the adjacent equal-means pair as a repeated-value point mass and excludes its half-weight from cdf/quantile interpolation — so quantiles near that mean depend on where the internal pending-buffer boundary happens to fall (buffer-size dependent results, beyond t-digest's inherent merge-order dependence). Mass/moment/sort order are preserved, so the error is a bounded local interpolation shift. Consider deferring the endpoint split for interior chunk boundaries (e.g. only normalize against the source's true extrema once the source is fully consumed). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
