HADOOP-13804. MutableStat mean loses accuracy if add(long, long) is used. Contributed by Erik Krogen.
(cherry picked from commit3dbad5d823
) (cherry picked from commitb245e9ce2f
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@ -99,6 +99,10 @@ public class MutableStat extends MutableMetric {
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/**
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/**
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* Add a number of samples and their sum to the running stat
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* Add a number of samples and their sum to the running stat
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*
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* Note that although use of this method will preserve accurate mean values,
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* large values for numSamples may result in inaccurate variance values due
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* to the use of a single step of the Welford method for variance calculation.
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* @param numSamples number of samples
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* @param numSamples number of samples
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* @param sum of the samples
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* @param sum of the samples
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*/
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*/
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@ -27,29 +27,32 @@ import org.apache.hadoop.classification.InterfaceAudience;
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public class SampleStat {
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public class SampleStat {
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private final MinMax minmax = new MinMax();
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private final MinMax minmax = new MinMax();
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private long numSamples = 0;
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private long numSamples = 0;
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private double a0, a1, s0, s1;
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private double a0, a1, s0, s1, total;
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/**
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/**
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* Construct a new running sample stat
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* Construct a new running sample stat
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*/
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*/
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public SampleStat() {
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public SampleStat() {
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a0 = s0 = 0.0;
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a0 = s0 = 0.0;
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total = 0.0;
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}
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}
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public void reset() {
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public void reset() {
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numSamples = 0;
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numSamples = 0;
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a0 = s0 = 0.0;
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a0 = s0 = 0.0;
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total = 0.0;
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minmax.reset();
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minmax.reset();
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}
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}
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// We want to reuse the object, sometimes.
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// We want to reuse the object, sometimes.
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void reset(long numSamples, double a0, double a1, double s0, double s1,
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void reset(long numSamples, double a0, double a1, double s0, double s1,
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MinMax minmax) {
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double total, MinMax minmax) {
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this.numSamples = numSamples;
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this.numSamples = numSamples;
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this.a0 = a0;
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this.a0 = a0;
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this.a1 = a1;
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this.a1 = a1;
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this.s0 = s0;
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this.s0 = s0;
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this.s1 = s1;
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this.s1 = s1;
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this.total = total;
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this.minmax.reset(minmax);
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this.minmax.reset(minmax);
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}
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}
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@ -58,7 +61,7 @@ public class SampleStat {
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* @param other the destination to hold our values
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* @param other the destination to hold our values
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*/
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*/
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public void copyTo(SampleStat other) {
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public void copyTo(SampleStat other) {
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other.reset(numSamples, a0, a1, s0, s1, minmax);
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other.reset(numSamples, a0, a1, s0, s1, total, minmax);
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}
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}
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/**
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/**
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@ -80,6 +83,7 @@ public class SampleStat {
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*/
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*/
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public SampleStat add(long nSamples, double x) {
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public SampleStat add(long nSamples, double x) {
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numSamples += nSamples;
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numSamples += nSamples;
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total += x;
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if (numSamples == 1) {
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if (numSamples == 1) {
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a0 = a1 = x;
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a0 = a1 = x;
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@ -102,11 +106,18 @@ public class SampleStat {
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return numSamples;
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return numSamples;
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}
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}
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/**
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* @return the total of all samples added
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*/
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public double total() {
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return total;
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}
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/**
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/**
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* @return the arithmetic mean of the samples
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* @return the arithmetic mean of the samples
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*/
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*/
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public double mean() {
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public double mean() {
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return numSamples > 0 ? a1 : 0.0;
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return numSamples > 0 ? (total / numSamples) : 0.0;
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}
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}
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/**
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/**
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@ -115,6 +115,23 @@ public class TestMutableMetrics {
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assertGauge("BarAvgTime", 0.0, rb);
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assertGauge("BarAvgTime", 0.0, rb);
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}
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}
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/**
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* Tests that when using {@link MutableStat#add(long, long)}, even with a high
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* sample count, the mean does not lose accuracy.
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*/
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@Test public void testMutableStatWithBulkAdd() {
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MetricsRecordBuilder rb = mockMetricsRecordBuilder();
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MetricsRegistry registry = new MetricsRegistry("test");
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MutableStat stat = registry.newStat("Test", "Test", "Ops", "Val", false);
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stat.add(1000, 1000);
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stat.add(1000, 2000);
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registry.snapshot(rb, false);
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assertCounter("TestNumOps", 2000L, rb);
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assertGauge("TestAvgVal", 1.5, rb);
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}
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/**
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/**
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* Ensure that quantile estimates from {@link MutableQuantiles} are within
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* Ensure that quantile estimates from {@link MutableQuantiles} are within
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* specified error bounds.
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* specified error bounds.
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