Simplify summing up algorithm for aggregations

liketic · liketic · commit 1f07cca93913 · 2018-01-03T19:09:14.000+08:00
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/avg/AvgAggregator.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/avg/AvgAggregator.java
@@ -90,10 +90,8 @@ public void collect(int doc, long bucket) throws IOException {
 
                     for (int i = 0; i < valueCount; i++) {
                         double value = values.nextValue();
-                        if (Double.isNaN(value) || Double.isInfinite(value)) {
+                        if (Double.isFinite(value) == false) {
                             sum += value;
-                            if (Double.isNaN(sum))
-                                break;
                         } else if (Double.isFinite(sum)) {
                             double corrected = value - compensation;
                             double newSum = sum + corrected;
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/avg/InternalAvg.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/avg/InternalAvg.java
@@ -97,15 +97,13 @@ public InternalAvg doReduce(List<InternalAggregation> aggregations, ReduceContex
         for (InternalAggregation aggregation : aggregations) {
             InternalAvg avg = (InternalAvg) aggregation;
             count += avg.count;
-            if (Double.isNaN(sum) == false) {
-                if (Double.isNaN(avg.sum) || Double.isInfinite(avg.sum)) {
-                    sum += avg.sum;
-                } else if (Double.isFinite(sum)) {
-                    double corrected = avg.sum - compensation;
-                    double newSum = sum + corrected;
-                    compensation = (newSum - sum) - corrected;
-                    sum = newSum;
-                }
+            if (Double.isFinite(avg.sum) == false) {
+                sum += avg.sum;
+            } else if (Double.isFinite(sum)) {
+                double corrected = avg.sum - compensation;
+                double newSum = sum + corrected;
+                compensation = (newSum - sum) - corrected;
+                sum = newSum;
             }
         }
         return new InternalAvg(getName(), sum, count, format, pipelineAggregators(), getMetaData());
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/InternalStats.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/InternalStats.java
@@ -160,16 +160,14 @@ public InternalStats doReduce(List<InternalAggregation> aggregations, ReduceCont
             max = Math.max(max, stats.getMax());
             // Compute the sum of double values with Kahan summation algorithm which is more
             // accurate than naive summation.
-            if (Double.isNaN(sum) == false) {
-                double value = stats.getSum();
-                if (Double.isNaN(value) || Double.isInfinite(value)) {
-                    sum += value;
-                } else if (Double.isFinite(sum)) {
-                    double corrected = value - compensation;
-                    double newSum = sum + corrected;
-                    compensation = (newSum - sum) - corrected;
-                    sum = newSum;
-                }
+            double value = stats.getSum();
+            if (Double.isFinite(value) == false) {
+                sum += value;
+            } else if (Double.isFinite(sum)) {
+                double corrected = value - compensation;
+                double newSum = sum + corrected;
+                compensation = (newSum - sum) - corrected;
+                sum = newSum;
             }
         }
         return new InternalStats(name, count, sum, min, max, format, pipelineAggregators(), getMetaData());
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/StatsAggregator.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/StatsAggregator.java
@@ -45,11 +45,10 @@ public class StatsAggregator extends NumericMetricsAggregator.MultiValue {
 
     LongArray counts;
     DoubleArray sums;
+    DoubleArray compensations;
     DoubleArray mins;
     DoubleArray maxes;
 
-    private DoubleArray compensations;
-
 
     public StatsAggregator(String name, ValuesSource.Numeric valuesSource, DocValueFormat format,
             SearchContext context,
@@ -110,15 +109,13 @@ public void collect(int doc, long bucket) throws IOException {
 
                     for (int i = 0; i < valuesCount; i++) {
                         double value = values.nextValue();
-                        if (Double.isNaN(sum) == false) {
-                            if (Double.isNaN(value) || Double.isInfinite(value)) {
-                                sum += value;
-                            } else if (Double.isFinite(sum)) {
-                                double corrected = value - compensation;
-                                double newSum = sum + corrected;
-                                compensation = (newSum - sum) - corrected;
-                                sum = newSum;
-                            }
+                        if (Double.isFinite(value) == false) {
+                            sum += value;
+                        } else if (Double.isFinite(sum)) {
+                            double corrected = value - compensation;
+                            double newSum = sum + corrected;
+                            compensation = (newSum - sum) - corrected;
+                            sum = newSum;
                         }
                         min = Math.min(min, value);
                         max = Math.max(max, value);
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/extended/ExtendedStatsAggregator.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/extended/ExtendedStatsAggregator.java
@@ -121,7 +121,7 @@ public void collect(int doc, long bucket) throws IOException {
                     double compensationOfSqr = compensationOfSqrs.get(bucket);
                     for (int i = 0; i < valuesCount; i++) {
                         double value = values.nextValue();
-                        if (Double.isNaN(value) || Double.isInfinite(value)) {
+                        if (Double.isFinite(value) == false) {
                             sum += value;
                             sumOfSqr += value * value;
                         } else {
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/extended/InternalExtendedStats.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/stats/extended/InternalExtendedStats.java
@@ -45,7 +45,7 @@ public static Metrics resolve(String name) {
     private final double sigma;
 
     public InternalExtendedStats(String name, long count, double sum, double min, double max, double sumOfSqrs, double sigma,
-            DocValueFormat formatter, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) {
+                                 DocValueFormat formatter, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) {
         super(name, count, sum, min, max, formatter, pipelineAggregators, metaData);
         this.sumOfSqrs = sumOfSqrs;
         this.sigma = sigma;
@@ -148,21 +148,19 @@ public InternalExtendedStats doReduce(List<InternalAggregation> aggregations, Re
             if (stats.sigma != sigma) {
                 throw new IllegalStateException("Cannot reduce other stats aggregations that have a different sigma");
             }
-            if (Double.isNaN(sumOfSqrs) == false) {
-                double value = stats.getSumOfSquares();
-                if (Double.isNaN(value) || Double.isInfinite(value)) {
-                    sumOfSqrs += value;
-                } else if (Double.isFinite(sumOfSqrs)) {
-                    double correctedOfSqrs = value - compensationOfSqrs;
-                    double newSumOfSqrs = sumOfSqrs + correctedOfSqrs;
-                    compensationOfSqrs = (newSumOfSqrs - sumOfSqrs) - correctedOfSqrs;
-                    sumOfSqrs = newSumOfSqrs;
-                }
+            double value = stats.getSumOfSquares();
+            if (Double.isFinite(value) == false) {
+                sumOfSqrs += value;
+            } else if (Double.isFinite(sumOfSqrs)) {
+                double correctedOfSqrs = value - compensationOfSqrs;
+                double newSumOfSqrs = sumOfSqrs + correctedOfSqrs;
+                compensationOfSqrs = (newSumOfSqrs - sumOfSqrs) - correctedOfSqrs;
+                sumOfSqrs = newSumOfSqrs;
             }
         }
         final InternalStats stats = super.doReduce(aggregations, reduceContext);
         return new InternalExtendedStats(name, stats.getCount(), stats.getSum(), stats.getMin(), stats.getMax(), sumOfSqrs, sigma,
-                format, pipelineAggregators(), getMetaData());
+            format, pipelineAggregators(), getMetaData());
     }
 
     static class Fields {
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/sum/InternalSum.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/sum/InternalSum.java
@@ -79,10 +79,8 @@ public InternalSum doReduce(List<InternalAggregation> aggregations, ReduceContex
         double compensation = 0;
         for (InternalAggregation aggregation : aggregations) {
             double value = ((InternalSum) aggregation).sum;
-            if (Double.isNaN(value) || Double.isInfinite(value)) {
+            if (Double.isFinite(value) == false) {
                 sum += value;
-                if (Double.isNaN(sum))
-                    break;
             } else if (Double.isFinite(sum)) {
                 double corrected = value - compensation;
                 double newSum = sum + corrected;
diff --git a/core/src/main/java/org/elasticsearch/search/aggregations/metrics/sum/SumAggregator.java b/core/src/main/java/org/elasticsearch/search/aggregations/metrics/sum/SumAggregator.java
@@ -83,10 +83,8 @@ public void collect(int doc, long bucket) throws IOException {
                     double compensation = compensations.get(bucket);
                     for (int i = 0; i < valuesCount; i++) {
                         double value = values.nextValue();
-                        if (Double.isNaN(value) || Double.isInfinite(value)) {
+                        if (Double.isFinite(value) == false) {
                             sum += value;
-                            if (Double.isNaN(sum))
-                                break;
                         } else if (Double.isFinite(sum)) {
                             double corrected = value - compensation;
                             double newSum = sum + corrected;
diff --git a/core/src/test/java/org/elasticsearch/search/aggregations/metrics/InternalSumTests.java b/core/src/test/java/org/elasticsearch/search/aggregations/metrics/InternalSumTests.java
@@ -35,9 +35,11 @@
 
 public class InternalSumTests extends InternalAggregationTestCase<InternalSum> {
 
+    private static final double TOLERANCE = 1e-10;
+
     @Override
     protected InternalSum createTestInstance(String name, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) {
-        double value = frequently() ? randomDouble() : randomFrom(Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY);
+        double value = frequently() ? randomDouble() : randomFrom(Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY, Double.NaN);
         DocValueFormat formatter = randomFrom(new DocValueFormat.Decimal("###.##"), DocValueFormat.BOOLEAN, DocValueFormat.RAW);
         return new InternalSum(name, value, formatter, pipelineAggregators, metaData);
     }
@@ -54,15 +56,45 @@ protected void assertReduced(InternalSum reduced, List<InternalSum> inputs) {
     }
 
     public void testSummationAccuracy() throws IOException {
+        // Summing up a normal array and expect an accurate value
         double[] values = new double[]{0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.9, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7};
+        verifySummationOfDoubles(values, 13.5, 0);
+
+        // Summing up an array which contains NaN and infinities and expect a result same as naive summation
+        int n = randomIntBetween(5, 10);
+        values = new double[n];
+        double sum = 0;
+        for (int i = 0; i < n; i++) {
+            values[i] = frequently()
+                ? randomFrom(Double.NaN, Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY)
+                : randomDoubleBetween(Double.MIN_VALUE, Double.MAX_VALUE, true);
+            sum += values[i];
+        }
+        verifySummationOfDoubles(values, sum, TOLERANCE);
+
+        // Summing up some big double values and expect infinity result
+        n = randomIntBetween(5, 10);
+        double[] bigPositiveDoubles = new double[n];
+        for (int i = 0; i < n; i++) {
+            bigPositiveDoubles[i] = Double.MAX_VALUE;
+        }
+        verifySummationOfDoubles(bigPositiveDoubles, Double.POSITIVE_INFINITY, 0d);
+
+        double[] bigNegativeDoubles = new double[n];
+        for (int i = 0; i < n; i++) {
+            bigNegativeDoubles[i] = -Double.MAX_VALUE;
+        }
+        verifySummationOfDoubles(bigNegativeDoubles, Double.NEGATIVE_INFINITY, 0d);
+    }
+
+    private void verifySummationOfDoubles(double[] values, double expected, double delta) throws IOException {
         List<InternalAggregation> aggregations = new ArrayList<>(values.length);
         for (double value : values) {
             aggregations.add(new InternalSum("dummy1", value, null, null, null));
         }
         InternalSum internalSum = new InternalSum("dummy", 0, null, null, null);
         InternalSum reduced = internalSum.doReduce(aggregations, null);
-        assertEquals(13.5, reduced.value(), 0d);
-        assertEquals("dummy", reduced.getName());
+        assertEquals(expected, reduced.value(), delta);
     }
 
     @Override
