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/*
 * Copyright The OpenTelemetry Authors
 * SPDX-License-Identifier: Apache-2.0
 */

package io.opentelemetry.sdk.metrics.internal.aggregator;

import static io.opentelemetry.sdk.common.export.MemoryMode.IMMUTABLE_DATA;
import static io.opentelemetry.sdk.common.export.MemoryMode.REUSABLE_DATA;

import io.opentelemetry.sdk.common.export.MemoryMode;
import io.opentelemetry.sdk.internal.DynamicPrimitiveLongList;
import io.opentelemetry.sdk.internal.PrimitiveLongList;
import io.opentelemetry.sdk.metrics.data.ExponentialHistogramBuckets;
import java.util.Collections;
import java.util.List;
import javax.annotation.Nullable;

/**
 * This class handles the operations for recording, scaling, and exposing data related to the base2
 * exponential histogram.
 *
 * 

This class is internal and is hence not for public use. Its APIs are unstable and can change * at any time. */ final class DoubleBase2ExponentialHistogramBuckets implements ExponentialHistogramBuckets { private final MemoryMode memoryMode; private AdaptingCircularBufferCounter counts; private int scale; private Base2ExponentialHistogramIndexer base2ExponentialHistogramIndexer; private long totalCount; // Only used when memory mode is REUSABLE_DATA @Nullable private AdaptingCircularBufferCounter reusableCounts; DoubleBase2ExponentialHistogramBuckets(int scale, int maxBuckets, MemoryMode memoryMode) { this.memoryMode = memoryMode; this.counts = new AdaptingCircularBufferCounter(maxBuckets); this.scale = scale; this.base2ExponentialHistogramIndexer = Base2ExponentialHistogramIndexer.get(this.scale); this.totalCount = 0; } // For copying DoubleBase2ExponentialHistogramBuckets(DoubleBase2ExponentialHistogramBuckets buckets) { this.counts = new AdaptingCircularBufferCounter(buckets.counts); this.scale = buckets.scale; this.base2ExponentialHistogramIndexer = buckets.base2ExponentialHistogramIndexer; this.totalCount = buckets.totalCount; this.memoryMode = buckets.memoryMode; this.reusableCounts = buckets.reusableCounts; } /** Returns a copy of this bucket. */ DoubleBase2ExponentialHistogramBuckets copy() { return new DoubleBase2ExponentialHistogramBuckets(this); } /** Resets all counters in this bucket set to zero and resets the scale to {@code scale}. */ void clear(int scale) { this.totalCount = 0; this.scale = scale; this.base2ExponentialHistogramIndexer = Base2ExponentialHistogramIndexer.get(this.scale); this.counts.clear(); } boolean record(double value) { if (value == 0.0) { // Guarded by caller. If passed 0 it would be a bug in the SDK. throw new IllegalStateException("Illegal attempted recording of zero at bucket level."); } int index = base2ExponentialHistogramIndexer.computeIndex(value); boolean recordingSuccessful = this.counts.increment(index, 1); if (recordingSuccessful) { totalCount++; } return recordingSuccessful; } @Override public int getOffset() { // We need to unify the behavior of empty buckets. // Unfortunately, getIndexStart is not meaningful for empty counters, so we default to // returning 0 for offset and an empty list. if (counts.isEmpty()) { return 0; } return counts.getIndexStart(); } @Override public List getBucketCounts() { if (counts.isEmpty()) { return Collections.emptyList(); } int length = counts.getIndexEnd() - counts.getIndexStart() + 1; long[] countsArr = new long[length]; for (int i = 0; i < length; i++) { countsArr[i] = counts.get(i + counts.getIndexStart()); } return PrimitiveLongList.wrap(countsArr); } /** * Fills the given reusable list with the bucket counts. * *

NOTE: This is the same as {@link #getBucketCounts()} but instead of returning a List with * the values is fill the values into {@code reusableLongList} * * @param reusableLongList The list to fill with the bucket counts */ void getBucketCountsIntoReusableList(DynamicPrimitiveLongList reusableLongList) { if (counts.isEmpty()) { reusableLongList.resizeAndClear(0); return; } int length = counts.getIndexEnd() - counts.getIndexStart() + 1; if (reusableLongList.size() != length) { reusableLongList.resizeAndClear(length); } for (int i = 0; i < length; i++) { reusableLongList.setLong(i, counts.get(i + counts.getIndexStart())); } } @Override public long getTotalCount() { return totalCount; } void downscale(int by) { if (by == 0) { return; } else if (by < 0) { // This should never happen without an SDK bug throw new IllegalStateException("Cannot downscale by negative amount. Was given " + by + "."); } if (!counts.isEmpty()) { // We want to preserve other optimisations here as well, e.g. integer size. // Instead of creating a new counter, we copy the existing one (for bucket size // optimisations), and clear the values before writing the new ones. AdaptingCircularBufferCounter newCounts; if (memoryMode == IMMUTABLE_DATA) { newCounts = new AdaptingCircularBufferCounter(counts); } else { if (reusableCounts == null) { reusableCounts = new AdaptingCircularBufferCounter(counts); } newCounts = reusableCounts; } newCounts.clear(); for (int i = counts.getIndexStart(); i <= counts.getIndexEnd(); i++) { long count = counts.get(i); if (count > 0) { if (!newCounts.increment(i >> by, count)) { // Theoretically won't happen unless there's an overflow on index throw new IllegalStateException("Failed to create new downscaled buckets."); } } } if (memoryMode == REUSABLE_DATA) { AdaptingCircularBufferCounter existingCounts = this.counts; this.counts = newCounts; reusableCounts = existingCounts; } else { this.counts = newCounts; } } this.scale = this.scale - by; this.base2ExponentialHistogramIndexer = Base2ExponentialHistogramIndexer.get(this.scale); } @Override public int getScale() { return scale; } /** * Returns the minimum scale reduction required to record the given value in these buckets, by * calculating the new required window to allow the new value to be recorded. To be used with * downScale(). * * @param value The proposed value to be recorded. * @return The required scale reduction in order to fit the value in these buckets. */ int getScaleReduction(double value) { long index = base2ExponentialHistogramIndexer.computeIndex(value); long newStart = Math.min(index, counts.getIndexStart()); long newEnd = Math.max(index, counts.getIndexEnd()); return getScaleReduction(newStart, newEnd); } int getScaleReduction(long newStart, long newEnd) { int scaleReduction = 0; while (newEnd - newStart + 1 > counts.getMaxSize()) { newStart >>= 1; newEnd >>= 1; scaleReduction++; } return scaleReduction; } @Override public boolean equals(@Nullable Object obj) { if (!(obj instanceof DoubleBase2ExponentialHistogramBuckets)) { return false; } DoubleBase2ExponentialHistogramBuckets other = (DoubleBase2ExponentialHistogramBuckets) obj; // Don't need to compare getTotalCount() because equivalent bucket counts // imply equivalent overall count. // Additionally, we compare the "semantics" of bucket counts, that is // it's ok for getOffset() to diverge as long as the populated counts remain // the same. This is because we don't "normalize" buckets after doing // difference/subtraction operations. return this.scale == other.scale && sameBucketCounts(other); } /** * Tests if two bucket counts are equivalent semantically. * *

Semantic equivalence means: * *

    *
  • All counts are stored between indexStart/indexEnd. *
  • Offset does NOT need to be the same *
*/ private boolean sameBucketCounts(DoubleBase2ExponentialHistogramBuckets other) { if (this.totalCount != other.totalCount) { return false; } int min = Math.min(this.counts.getIndexStart(), other.counts.getIndexStart()); // This check is so we avoid iterating from Integer.MIN_VALUE. // In this case, we can assume that those buckets are empty. // We start iterating from the other bucket index instead. // They still may be equal as it is possible for another set of buckets // to be empty but have a higher start index. if (min == Integer.MIN_VALUE) { min = Math.max(this.counts.getIndexStart(), other.counts.getIndexStart()); } int max = Math.max(this.counts.getIndexEnd(), other.counts.getIndexEnd()); for (int idx = min; idx <= max; idx++) { if (this.counts.get(idx) != other.counts.get(idx)) { return false; } } return true; } @Override public int hashCode() { int hash = 1; hash *= 1000003; // We need a new algorithm here that lines up w/ equals, so we only use non-zero counts. for (int idx = this.counts.getIndexStart(); idx <= this.counts.getIndexEnd(); idx++) { long count = this.counts.get(idx); if (count != 0) { hash ^= idx; hash *= 1000003; hash = (int) (hash ^ count); hash *= 1000003; } } hash ^= scale; // Don't need to hash getTotalCount() because equivalent bucket // counts imply equivalent overall count. return hash; } @Override public String toString() { return "DoubleExponentialHistogramBuckets{" + "scale: " + scale + ", offset: " + getOffset() + ", counts: " + counts + " }"; } }




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