--- /dev/null
+/*
+ * Copyright 2013 Facebook, Inc.
+ *
+ * Licensed 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.
+ */
+
+#include "folly/stats/TimeseriesHistogram.h"
+#include "folly/stats/TimeseriesHistogram-defs.h"
+
+#include <gtest/gtest.h>
+
+using namespace std;
+using namespace folly;
+using std::chrono::seconds;
+
+namespace IntMTMHTS {
+ enum Levels {
+ MINUTE,
+ TEN_MINUTE,
+ HOUR,
+ ALLTIME,
+ NUM_LEVELS,
+ };
+
+ const seconds kDurations[] = {
+ seconds(60), seconds(600), seconds(3600), seconds(0)
+ };
+};
+
+namespace IntMHTS {
+ enum Levels {
+ MINUTE,
+ HOUR,
+ ALLTIME,
+ NUM_LEVELS,
+ };
+
+ const seconds kDurations[] = {
+ seconds(60), seconds(3600), seconds(0)
+ };
+};
+
+typedef std::mt19937 RandomInt32;
+
+TEST(TimeseriesHistogram, Percentile) {
+ RandomInt32 random(5);
+ // [10, 109], 12 buckets including above and below
+ {
+ TimeseriesHistogram<int> h(10, 10, 110,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ EXPECT_EQ(0, h.getPercentileEstimate(0, IntMTMHTS::ALLTIME));
+
+ EXPECT_EQ(12, h.getNumBuckets());
+ EXPECT_EQ(10, h.getBucketSize());
+ EXPECT_EQ(10, h.getMin());
+ EXPECT_EQ(110, h.getMax());
+
+ for (int i = 0; i < h.getNumBuckets(); ++i) {
+ EXPECT_EQ(4, h.getBucket(i).numLevels());
+ }
+
+ int maxVal = 120;
+ h.addValue(seconds(0), 0);
+ h.addValue(seconds(0), maxVal);
+ for (int i = 0; i < 98; i++) {
+ h.addValue(seconds(0), random() % maxVal);
+ }
+
+ h.update(std::chrono::duration_cast<std::chrono::seconds>(
+ std::chrono::system_clock::now().time_since_epoch()));
+ // bucket 0 stores everything below min, so its minimum
+ // is the lowest possible number
+ EXPECT_EQ(std::numeric_limits<int>::min(),
+ h.getPercentileBucketMin(1, IntMTMHTS::ALLTIME));
+ EXPECT_EQ(110, h.getPercentileBucketMin(99, IntMTMHTS::ALLTIME));
+
+ EXPECT_EQ(-2, h.getPercentileEstimate(0, IntMTMHTS::ALLTIME));
+ EXPECT_EQ(-1, h.getPercentileEstimate(1, IntMTMHTS::ALLTIME));
+ EXPECT_EQ(119, h.getPercentileEstimate(99, IntMTMHTS::ALLTIME));
+ EXPECT_EQ(120, h.getPercentileEstimate(100, IntMTMHTS::ALLTIME));
+ }
+}
+
+TEST(TimeseriesHistogram, String) {
+ RandomInt32 random(5);
+ // [10, 109], 12 buckets including above and below
+ {
+ TimeseriesHistogram<int> hist(10, 10, 110,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ int maxVal = 120;
+ hist.addValue(seconds(0), 0);
+ hist.addValue(seconds(0), maxVal);
+ for (int i = 0; i < 98; i++) {
+ hist.addValue(seconds(0), random() % maxVal);
+ }
+
+ hist.update(seconds(0));
+
+ const char* const kStringValues1[IntMTMHTS::NUM_LEVELS] = {
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ };
+
+ CHECK_EQ(IntMTMHTS::NUM_LEVELS, hist.getNumLevels());
+
+ for (int level = 0; level < hist.getNumLevels(); ++level) {
+ EXPECT_EQ(kStringValues1[level], hist.getString(level));
+ }
+
+ const char* const kStringValues2[IntMTMHTS::NUM_LEVELS] = {
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ "-2147483648:12:4,10:8:13,20:8:24,30:6:34,40:13:46,50:8:54,60:7:64,"
+ "70:7:74,80:8:84,90:10:94,100:3:103,110:10:115",
+ };
+
+ CHECK_EQ(IntMTMHTS::NUM_LEVELS, hist.getNumLevels());
+
+ for (int level = 0; level < hist.getNumLevels(); ++level) {
+ EXPECT_EQ(kStringValues2[level], hist.getString(level));
+ }
+ }
+}
+
+TEST(TimeseriesHistogram, Clear) {
+ {
+ TimeseriesHistogram<int> hist(10, 0, 100,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ for (int now = 0; now < 3600; now++) {
+ for (int i = 0; i < 100; i++) {
+ hist.addValue(seconds(now), i, 2); // adds each item 2 times
+ }
+ }
+
+ // check clearing
+ hist.clear();
+
+ for (int b = 0; b < hist.getNumBuckets(); ++b) {
+ EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::HOUR));
+ EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::ALLTIME));
+ }
+
+ for (int pct = 0; pct <= 100; pct++) {
+ EXPECT_EQ(0, hist.getPercentileBucketMin(pct, IntMTMHTS::MINUTE));
+ EXPECT_EQ(0, hist.getPercentileBucketMin(pct, IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(0, hist.getPercentileBucketMin(pct, IntMTMHTS::HOUR));
+ EXPECT_EQ(0, hist.getPercentileBucketMin(pct, IntMTMHTS::ALLTIME));
+
+ EXPECT_EQ(0, hist.getPercentileEstimate(pct, IntMTMHTS::MINUTE));
+ EXPECT_EQ(0, hist.getPercentileEstimate(pct, IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(0, hist.getPercentileEstimate(pct, IntMTMHTS::HOUR));
+ EXPECT_EQ(0, hist.getPercentileEstimate(pct, IntMTMHTS::ALLTIME));
+ }
+ }
+}
+
+
+TEST(TimeseriesHistogram, Basic) {
+ {
+ TimeseriesHistogram<int> hist(10, 0, 100,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ for (int now = 0; now < 3600; now++) {
+ for (int i = 0; i < 100; i++) {
+ hist.addValue(seconds(now), i);
+ }
+ }
+
+ hist.update(seconds(3599));
+ for (int pct = 1; pct <= 100; pct++) {
+ int expected = (pct - 1) / 10 * 10;
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::MINUTE));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct,
+ IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::HOUR));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::ALLTIME));
+ }
+
+ for (int b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
+ EXPECT_EQ(600, hist.getBucket(b).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(6000, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(36000, hist.getBucket(b).count(IntMTMHTS::HOUR));
+ EXPECT_EQ(36000, hist.getBucket(b).count(IntMTMHTS::ALLTIME));
+ }
+ EXPECT_EQ(0, hist.getBucket(0).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(0, hist.getBucket(hist.getNumBuckets() - 1).count(
+ IntMTMHTS::MINUTE));
+ }
+
+ // -----------------
+
+ {
+ TimeseriesHistogram<int> hist(10, 0, 100,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ for (int now = 0; now < 3600; now++) {
+ for (int i = 0; i < 100; i++) {
+ hist.addValue(seconds(now), i, 2); // adds each item 2 times
+ }
+ }
+
+ hist.update(seconds(3599));
+ for (int pct = 1; pct <= 100; pct++) {
+ int expected = (pct - 1) / 10 * 10;
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::MINUTE));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct,
+ IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::HOUR));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::ALLTIME));
+ }
+
+ for (int b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
+ EXPECT_EQ(600 * 2, hist.getBucket(b).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(6000 * 2, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(36000 * 2, hist.getBucket(b).count(IntMTMHTS::HOUR));
+ EXPECT_EQ(36000 * 2, hist.getBucket(b).count(IntMTMHTS::ALLTIME));
+ }
+ EXPECT_EQ(0, hist.getBucket(0).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(0, hist.getBucket(hist.getNumBuckets() - 1).count(
+ IntMTMHTS::MINUTE));
+ }
+
+ // -----------------
+
+ {
+ TimeseriesHistogram<int> hist(10, 0, 100,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ for (int now = 0; now < 3600; now++) {
+ for (int i = 0; i < 50; i++) {
+ hist.addValue(seconds(now), i * 2, 2); // adds each item 2 times
+ }
+ }
+
+ hist.update(seconds(3599));
+ for (int pct = 1; pct <= 100; pct++) {
+ int expected = (pct - 1) / 10 * 10;
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::MINUTE));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct,
+ IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::HOUR));
+ EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::ALLTIME));
+ }
+
+ EXPECT_EQ(0, hist.getBucket(0).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(0, hist.getBucket(0).count(IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(0, hist.getBucket(0).count(IntMTMHTS::HOUR));
+ EXPECT_EQ(0, hist.getBucket(0).count(IntMTMHTS::ALLTIME));
+ EXPECT_EQ(0, hist.getBucket(hist.getNumBuckets() - 1).count(
+ IntMTMHTS::MINUTE));
+ EXPECT_EQ(0,
+ hist.getBucket(hist.getNumBuckets() - 1).
+ count(IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(0, hist.getBucket(hist.getNumBuckets() - 1).count(
+ IntMTMHTS::HOUR));
+ EXPECT_EQ(0,
+ hist.getBucket(hist.getNumBuckets() - 1).count(
+ IntMTMHTS::ALLTIME));
+
+ for (int b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
+ EXPECT_EQ(600, hist.getBucket(b).count(IntMTMHTS::MINUTE));
+ EXPECT_EQ(6000, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
+ EXPECT_EQ(36000, hist.getBucket(b).count(IntMTMHTS::HOUR));
+ EXPECT_EQ(36000, hist.getBucket(b).count(IntMTMHTS::ALLTIME));
+ }
+
+ for (int i = 0; i < 100; ++i) {
+ hist.addValue(seconds(3599), 200 + i);
+ }
+ hist.update(seconds(3599));
+ EXPECT_EQ(100,
+ hist.getBucket(hist.getNumBuckets() - 1).count(
+ IntMTMHTS::ALLTIME));
+
+ }
+}
+
+TEST(TimeseriesHistogram, QueryByInterval) {
+ TimeseriesHistogram<int> mhts(8, 8, 120,
+ MultiLevelTimeSeries<int>(
+ 60, IntMHTS::NUM_LEVELS,
+ IntMHTS::kDurations));
+
+ mhts.update(seconds(0));
+
+ int curTime;
+ for (curTime = 0; curTime < 7200; curTime++) {
+ mhts.addValue(seconds(curTime), 1);
+ }
+ for (curTime = 7200; curTime < 7200 + 3540; curTime++) {
+ mhts.addValue(seconds(curTime), 10);
+ }
+ for (curTime = 7200 + 3540; curTime < 7200 + 3600; curTime++) {
+ mhts.addValue(seconds(curTime), 100);
+ }
+
+ mhts.update(seconds(7200 + 3600 - 1));
+
+ struct TimeInterval {
+ TimeInterval(int s, int e)
+ : start(s), end(e) {}
+
+ std::chrono::seconds start;
+ std::chrono::seconds end;
+ };
+ TimeInterval intervals[12] = {
+ { curTime - 60, curTime },
+ { curTime - 3600, curTime },
+ { curTime - 7200, curTime },
+ { curTime - 3600, curTime - 60 },
+ { curTime - 7200, curTime - 60 },
+ { curTime - 7200, curTime - 3600 },
+ { curTime - 50, curTime - 20 },
+ { curTime - 3020, curTime - 20 },
+ { curTime - 7200, curTime - 20 },
+ { curTime - 3000, curTime - 1000 },
+ { curTime - 7200, curTime - 1000 },
+ { curTime - 7200, curTime - 3600 },
+ };
+
+ int expectedSums[12] = {
+ 6000, 41400, 32400, 35400, 32129, 16200, 3000, 33600, 32308, 20000, 27899,
+ 16200
+ };
+
+ int expectedCounts[12] = {
+ 60, 3600, 7200, 3540, 7139, 3600, 30, 3000, 7178, 2000, 6199, 3600
+ };
+
+ // The first 7200 values added all fell below the histogram minimum,
+ // and went into the bucket that tracks all of the too-small values.
+ // This bucket reports a minimum value of the smallest possible integer.
+ int belowMinBucket = std::numeric_limits<int>::min();
+
+ int expectedValues[12][3] = {
+ {96, 96, 96},
+ { 8, 8, 96},
+ { belowMinBucket, belowMinBucket, 8}, // alltime
+ { 8, 8, 8},
+ { belowMinBucket, belowMinBucket, 8}, // alltime
+ { belowMinBucket, belowMinBucket, 8}, // alltime
+ {96, 96, 96},
+ { 8, 8, 96},
+ { belowMinBucket, belowMinBucket, 8}, // alltime
+ { 8, 8, 8},
+ { belowMinBucket, belowMinBucket, 8}, // alltime
+ { belowMinBucket, belowMinBucket, 8} // alltime
+ };
+
+ for (int i = 0; i < 12; i++) {
+ const auto& itv = intervals[i];
+ int s = mhts.sum(itv.start, itv.end);
+ EXPECT_EQ(expectedSums[i], s);
+
+ int c = mhts.count(itv.start, itv.end);
+ EXPECT_EQ(expectedCounts[i], c);
+ }
+
+ // 3 levels
+ for (int i = 1; i <= 100; i++) {
+ EXPECT_EQ(96, mhts.getPercentileBucketMin(i, 0));
+ EXPECT_EQ(96, mhts.getPercentileBucketMin(i, seconds(curTime - 60),
+ seconds(curTime)));
+ EXPECT_EQ(8, mhts.getPercentileBucketMin(i, seconds(curTime - 3540),
+ seconds(curTime - 60)));
+ }
+
+ EXPECT_EQ(8, mhts.getPercentileBucketMin(1, 1));
+ EXPECT_EQ(8, mhts.getPercentileBucketMin(98, 1));
+ EXPECT_EQ(96, mhts.getPercentileBucketMin(99, 1));
+ EXPECT_EQ(96, mhts.getPercentileBucketMin(100, 1));
+
+ EXPECT_EQ(belowMinBucket, mhts.getPercentileBucketMin(1, 2));
+ EXPECT_EQ(belowMinBucket, mhts.getPercentileBucketMin(66, 2));
+ EXPECT_EQ(8, mhts.getPercentileBucketMin(67, 2));
+ EXPECT_EQ(8, mhts.getPercentileBucketMin(99, 2));
+ EXPECT_EQ(96, mhts.getPercentileBucketMin(100, 2));
+
+ // 0 is currently the value for bucket 0 (below min)
+ for (int i = 0; i < 12; i++) {
+ const auto& itv = intervals[i];
+ int v = mhts.getPercentileBucketMin(1, itv.start, itv.end);
+ EXPECT_EQ(expectedValues[i][0], v);
+
+ v = mhts.getPercentileBucketMin(50, itv.start, itv.end);
+ EXPECT_EQ(expectedValues[i][1], v);
+
+ v = mhts.getPercentileBucketMin(99, itv.start, itv.end);
+ EXPECT_EQ(expectedValues[i][2], v);
+ }
+
+ for (int i = 0; i < 12; i++) {
+ const auto& itv = intervals[i];
+ int c = mhts.count(itv.start, itv.end);
+ // Some of the older intervals that fall in the alltime bucket
+ // are off by 1 or 2 in their estimated counts.
+ size_t tolerance = 0;
+ if (itv.start <= seconds(curTime - 7200)) {
+ tolerance = 2;
+ } else if (itv.start <= seconds(curTime - 3000)) {
+ tolerance = 1;
+ }
+ size_t actualCount = (itv.end - itv.start).count();
+ size_t estimatedCount = mhts.count(itv.start, itv.end);
+ EXPECT_GE(actualCount, estimatedCount);
+ EXPECT_LE(actualCount - tolerance, estimatedCount);
+ }
+}
+
+TEST(TimeseriesHistogram, SingleUniqueValue) {
+ int values[] = {-1, 0, 500, 1000, 1500};
+ for (int ii = 0; ii < 5; ++ii) {
+ int value = values[ii];
+ TimeseriesHistogram<int> h(10, 0, 1000,
+ MultiLevelTimeSeries<int>(
+ 60, IntMTMHTS::NUM_LEVELS,
+ IntMTMHTS::kDurations));
+
+ const int kNumIters = 1000;
+ for (int jj = 0; jj < kNumIters; ++jj) {
+ h.addValue(seconds(time(nullptr)), value);
+ }
+ h.update(seconds(time(nullptr)));
+ // since we've only added one unique value, all percentiles should
+ // be that value
+ EXPECT_EQ(h.getPercentileEstimate(10, 0), value);
+ EXPECT_EQ(h.getPercentileEstimate(50, 0), value);
+ EXPECT_EQ(h.getPercentileEstimate(99, 0), value);
+
+ // Things get trickier if there are multiple unique values.
+ const int kNewValue = 750;
+ for (int kk = 0; kk < 2*kNumIters; ++kk) {
+ h.addValue(seconds(time(nullptr)), kNewValue);
+ }
+ h.update(seconds(time(nullptr)));
+ EXPECT_NEAR(h.getPercentileEstimate(50, 0), kNewValue+5, 5);
+ if (value >= 0 && value <= 1000) {
+ // only do further testing if value is within our bucket range,
+ // else estimates can be wildly off
+ if (kNewValue > value) {
+ EXPECT_NEAR(h.getPercentileEstimate(10, 0), value+5, 5);
+ EXPECT_NEAR(h.getPercentileEstimate(99, 0), kNewValue+5, 5);
+ } else {
+ EXPECT_NEAR(h.getPercentileEstimate(10, 0), kNewValue+5, 5);
+ EXPECT_NEAR(h.getPercentileEstimate(99, 0), value+5, 5);
+ }
+ }
+ }
+}
+
projects / folly.git / blobdiff