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Posted to commits@pinot.apache.org by GitBox <gi...@apache.org> on 2022/12/07 00:30:06 UTC
[GitHub] [pinot] jasperjiaguo commented on a diff in pull request #9910: Add Variance and Standard Deviation Aggregation Functions
jasperjiaguo commented on code in PR #9910:
URL: https://github.com/apache/pinot/pull/9910#discussion_r1041477398
##########
pinot-core/src/main/java/org/apache/pinot/core/common/ObjectSerDeUtils.java:
##########
@@ -123,7 +124,9 @@ public enum ObjectType {
FloatLongPair(29),
DoubleLongPair(30),
StringLongPair(31),
- CovarianceTuple(32);
+ CovarianceTuple(32),
+
Review Comment:
(nit) remove blank line?
##########
pinot-core/src/test/java/org/apache/pinot/queries/VarianceQueriesTest.java:
##########
@@ -0,0 +1,446 @@
+/**
+ * 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.
+ */
+package org.apache.pinot.queries;
+
+import java.io.File;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Random;
+import org.apache.commons.io.FileUtils;
+import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation;
+import org.apache.commons.math3.stat.descriptive.moment.Variance;
+import org.apache.commons.math3.util.Precision;
+import org.apache.pinot.common.response.broker.BrokerResponseNative;
+import org.apache.pinot.core.operator.blocks.results.AggregationResultsBlock;
+import org.apache.pinot.core.operator.blocks.results.GroupByResultsBlock;
+import org.apache.pinot.core.operator.query.AggregationOperator;
+import org.apache.pinot.core.operator.query.GroupByOperator;
+import org.apache.pinot.core.query.aggregation.groupby.AggregationGroupByResult;
+import org.apache.pinot.segment.local.customobject.VarianceTuple;
+import org.apache.pinot.segment.local.indexsegment.immutable.ImmutableSegmentLoader;
+import org.apache.pinot.segment.local.segment.creator.impl.SegmentIndexCreationDriverImpl;
+import org.apache.pinot.segment.local.segment.readers.GenericRowRecordReader;
+import org.apache.pinot.segment.spi.ImmutableSegment;
+import org.apache.pinot.segment.spi.IndexSegment;
+import org.apache.pinot.segment.spi.creator.SegmentGeneratorConfig;
+import org.apache.pinot.spi.config.table.TableConfig;
+import org.apache.pinot.spi.config.table.TableType;
+import org.apache.pinot.spi.data.FieldSpec;
+import org.apache.pinot.spi.data.Schema;
+import org.apache.pinot.spi.data.readers.GenericRow;
+import org.apache.pinot.spi.utils.ReadMode;
+import org.apache.pinot.spi.utils.builder.TableConfigBuilder;
+import org.testng.annotations.BeforeClass;
+import org.testng.annotations.Test;
+
+import static org.testng.Assert.assertEquals;
+import static org.testng.Assert.assertNotNull;
+import static org.testng.Assert.assertTrue;
+
+
+public class VarianceQueriesTest extends BaseQueriesTest {
+
+ private static final File INDEX_DIR = new File(FileUtils.getTempDirectory(), "VarianceQueriesTest");
+
+ private static final String RAW_TABLE_NAME = "testTable";
+ private static final String SEGMENT_NAME = "testSegment";
+
+ private static final int NUM_RECORDS = 2000;
+ private static final int NUM_GROUPS = 10;
+ private static final int MAX_VALUE = 500;
+ private static final double RELATIVE_EPSILON = 0.0001;
+ private static final double DELTA = 0.0001;
+
+ private static final String INT_COLUMN = "intColumn";
+ private static final String LONG_COLUMN = "longColumn";
+ private static final String FLOAT_COLUMN = "floatColumn";
+ private static final String DOUBLE_COLUMN = "doubleColumn";
+ private static final String GROUP_BY_COLUMN = "groupByColumn";
+
+ private static final Schema SCHEMA =
+ new Schema.SchemaBuilder().addSingleValueDimension(INT_COLUMN, FieldSpec.DataType.INT)
+ .addSingleValueDimension(LONG_COLUMN, FieldSpec.DataType.LONG)
+ .addSingleValueDimension(FLOAT_COLUMN, FieldSpec.DataType.FLOAT)
+ .addSingleValueDimension(DOUBLE_COLUMN, FieldSpec.DataType.DOUBLE)
+ .addSingleValueDimension(GROUP_BY_COLUMN, FieldSpec.DataType.DOUBLE).build();
+
+ private static final TableConfig TABLE_CONFIG =
+ new TableConfigBuilder(TableType.OFFLINE).setTableName(RAW_TABLE_NAME).build();
+
+ private IndexSegment _indexSegment;
+ private List<IndexSegment> _indexSegments;
+
+ int[] _intValues = new int[NUM_RECORDS];
+ long[] _longValues = new long[NUM_RECORDS];
+ float[] _floatValues = new float[NUM_RECORDS];
+ double[] _doubleValues = new double[NUM_RECORDS];
+
+ @Override
+ protected String getFilter() {
+ // filter out half of the rows based on group id
+ return " WHERE groupByColumn < " + (NUM_GROUPS / 2);
+ }
+
+ @Override
+ protected IndexSegment getIndexSegment() {
+ return _indexSegment;
+ }
+
+ @Override
+ protected List<IndexSegment> getIndexSegments() {
+ return _indexSegments;
+ }
+
+ @BeforeClass
+ public void setUp()
+ throws Exception {
+ FileUtils.deleteDirectory(INDEX_DIR);
+ Random random = new Random();
+ List<GenericRow> records = new ArrayList<>(NUM_RECORDS);
+
+ for (int i = 0; i < NUM_RECORDS; i++) {
+ GenericRow record = new GenericRow();
+ int intValue = -MAX_VALUE + random.nextInt() * 2 * MAX_VALUE;
+ long longValue = -MAX_VALUE + random.nextLong() * 2 * MAX_VALUE;
+ float floatValue = -MAX_VALUE + random.nextFloat() * 2 * MAX_VALUE;
+ double doubleValue = -MAX_VALUE + random.nextDouble() * 2 * MAX_VALUE;
+
+ _intValues[i] = intValue;
+ _longValues[i] = longValue;
+ _floatValues[i] = floatValue;
+ _doubleValues[i] = doubleValue;
+
+ record.putValue(INT_COLUMN, _intValues[i]);
+ record.putValue(LONG_COLUMN, _longValues[i]);
+ record.putValue(FLOAT_COLUMN, _floatValues[i]);
+ record.putValue(DOUBLE_COLUMN, _doubleValues[i]);
+ record.putValue(GROUP_BY_COLUMN, Math.floor(i / (NUM_RECORDS / NUM_GROUPS)));
+ records.add(record);
+ }
+
+ SegmentGeneratorConfig segmentGeneratorConfig = new SegmentGeneratorConfig(TABLE_CONFIG, SCHEMA);
+ segmentGeneratorConfig.setTableName(RAW_TABLE_NAME);
+ segmentGeneratorConfig.setSegmentName(SEGMENT_NAME);
+ segmentGeneratorConfig.setOutDir(INDEX_DIR.getPath());
+
+ SegmentIndexCreationDriverImpl driver = new SegmentIndexCreationDriverImpl();
+ driver.init(segmentGeneratorConfig, new GenericRowRecordReader(records));
+ driver.build();
+
+ ImmutableSegment immutableSegment = ImmutableSegmentLoader.load(new File(INDEX_DIR, SEGMENT_NAME), ReadMode.mmap);
+ _indexSegment = immutableSegment;
+ _indexSegments = Arrays.asList(immutableSegment, immutableSegment);
+ }
+
+ @Test
+ public void testVarianceAggregationOnly() {
+ // Compute the expected values
+ Variance[] expectedVariances = new Variance[8];
+ for (int i = 0; i < 8; i++) {
+ if (i < 4) {
+ expectedVariances[i] = new Variance(false);
+ } else {
+ expectedVariances[i] = new Variance(true);
+ }
+ }
+ for (int i = 0; i < NUM_RECORDS; i++) {
+ expectedVariances[0].increment(_intValues[i]);
+ expectedVariances[1].increment(_longValues[i]);
+ expectedVariances[2].increment(_floatValues[i]);
+ expectedVariances[3].increment(_doubleValues[i]);
+ expectedVariances[4].increment(_intValues[i]);
+ expectedVariances[5].increment(_longValues[i]);
+ expectedVariances[6].increment(_floatValues[i]);
+ expectedVariances[7].increment(_doubleValues[i]);
+ }
+ double expectedIntSum = Arrays.stream(_intValues).asDoubleStream().sum();
+ double expectedLongSum = Arrays.stream(_longValues).asDoubleStream().sum();
+ double expectedFloatSum = 0.0;
+ for (int i = 0; i < _floatValues.length; i++) {
+ expectedFloatSum += _floatValues[i];
+ }
+ double expectedDoubleSum = Arrays.stream(_doubleValues).sum();
+
+ // Compute the query
+ String query = "SELECT VAR_POP(intColumn), VAR_POP(longColumn), VAR_POP(floatColumn), VAR_POP(doubleColumn),"
+ + "VAR_SAMP(intColumn), VAR_SAMP(longColumn), VAR_SAMP(floatColumn), VAR_SAMP(doubleColumn) FROM testTable";
+ AggregationOperator aggregationOperator = getOperator(query);
+ AggregationResultsBlock resultsBlock = aggregationOperator.nextBlock();
+ QueriesTestUtils.testInnerSegmentExecutionStatistics(aggregationOperator.getExecutionStatistics(), NUM_RECORDS, 0,
+ NUM_RECORDS * 4, NUM_RECORDS);
+ List<Object> aggregationResult = resultsBlock.getResults();
+
+ // Validate the aggregation results
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(0), NUM_RECORDS, expectedIntSum,
+ expectedVariances[0].getResult(), false);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(1), NUM_RECORDS, expectedLongSum,
+ expectedVariances[1].getResult(), false);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(2), NUM_RECORDS, expectedFloatSum,
+ expectedVariances[2].getResult(), false);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(3), NUM_RECORDS, expectedDoubleSum,
+ expectedVariances[3].getResult(), false);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(4), NUM_RECORDS, expectedIntSum,
+ expectedVariances[4].getResult(), true);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(5), NUM_RECORDS, expectedLongSum,
+ expectedVariances[5].getResult(), true);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(6), NUM_RECORDS, expectedFloatSum,
+ expectedVariances[6].getResult(), true);
+ checkWithPrecisionForVariance((VarianceTuple) aggregationResult.get(7), NUM_RECORDS, expectedDoubleSum,
+ expectedVariances[7].getResult(), true);
+
+ // Update the expected result by 3 more times (broker query will compute 4 identical segments)
+ for (int i = 0; i < NUM_RECORDS * 3; i++) {
+ int pos = i % NUM_RECORDS;
+ expectedVariances[0].increment(_intValues[pos]);
+ expectedVariances[1].increment(_longValues[pos]);
+ expectedVariances[2].increment(_floatValues[pos]);
+ expectedVariances[3].increment(_doubleValues[pos]);
+ expectedVariances[4].increment(_intValues[pos]);
+ expectedVariances[5].increment(_longValues[pos]);
+ expectedVariances[6].increment(_floatValues[pos]);
+ expectedVariances[7].increment(_doubleValues[pos]);
+ }
+
+ // Validate the response
+ BrokerResponseNative brokerResponse = getBrokerResponse(query);
+ brokerResponse.getResultTable();
+ Object[] results = brokerResponse.getResultTable().getRows().get(0);
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[0], expectedVariances[0].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[1], expectedVariances[1].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[2], expectedVariances[2].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[3], expectedVariances[3].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[4], expectedVariances[4].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[5], expectedVariances[5].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[6], expectedVariances[6].getResult(), RELATIVE_EPSILON));
+ assertTrue(
+ Precision.equalsWithRelativeTolerance((double) results[7], expectedVariances[7].getResult(), RELATIVE_EPSILON));
+
+ // Validate the response for a query with a filter
+ query = "SELECT VAR_POP(intColumn) from testTable" + getFilter();
+ brokerResponse = getBrokerResponse(query);
+ brokerResponse.getResultTable();
+ results = brokerResponse.getResultTable().getRows().get(0);
+ Variance filterExpectedVariance = new Variance(false);
+ for (int i = 0; i < NUM_RECORDS / 2; i++) {
+ filterExpectedVariance.increment(_intValues[i]);
+ }
+ assertTrue(Precision.equalsWithRelativeTolerance((double) results[0], filterExpectedVariance.getResult(),
+ RELATIVE_EPSILON));
+ }
+
+ @Test
+ public void testVarianceAggregationGroupBy() {
+ // Compute expected group results
+ Variance[] expectedGroupByResult = new Variance[NUM_GROUPS];
+ double[] expectedSum = new double[NUM_GROUPS];
+
+ for (int i = 0; i < NUM_GROUPS; i++) {
+ expectedGroupByResult[i] = new Variance(false);
+ }
+ for (int j = 0; j < NUM_RECORDS; j++) {
+ int pos = j / (NUM_RECORDS / NUM_GROUPS);
+ expectedGroupByResult[pos].increment(_intValues[j]);
+ expectedSum[pos] += _intValues[j];
+ }
+
+ String query = "SELECT VAR_POP(intColumn) FROM testTable GROUP BY groupByColumn ORDER BY groupByColumn";
+ GroupByOperator groupByOperator = getOperator(query);
+ GroupByResultsBlock resultsBlock = groupByOperator.nextBlock();
+ QueriesTestUtils.testInnerSegmentExecutionStatistics(groupByOperator.getExecutionStatistics(), NUM_RECORDS, 0,
+ NUM_RECORDS * 2, NUM_RECORDS);
+ AggregationGroupByResult aggregationGroupByResult = resultsBlock.getAggregationGroupByResult();
+ assertNotNull(aggregationGroupByResult);
+ for (int i = 0; i < NUM_GROUPS; i++) {
+
+ VarianceTuple actualVarianceTuple = (VarianceTuple) aggregationGroupByResult.getResultForGroupId(0, i);
+ checkWithPrecisionForVariance(actualVarianceTuple, NUM_RECORDS / NUM_GROUPS, expectedSum[i],
+ expectedGroupByResult[i].getResult(), false);
+ }
+ }
+
+ @Test
+ public void testStandardDeviationAggregationOnly() {
+ // Compute the expected values
+ StandardDeviation[] expectedStdDevs = new StandardDeviation[8];
+ for (int i = 0; i < 8; i++) {
+ if (i < 4) {
+ expectedStdDevs[i] = new StandardDeviation(false);
+ } else {
+ expectedStdDevs[i] = new StandardDeviation(true);
+ }
+ }
+ for (int i = 0; i < NUM_RECORDS; i++) {
+ expectedStdDevs[0].increment(_intValues[i]);
+ expectedStdDevs[1].increment(_longValues[i]);
+ expectedStdDevs[2].increment(_floatValues[i]);
+ expectedStdDevs[3].increment(_doubleValues[i]);
+ expectedStdDevs[4].increment(_intValues[i]);
+ expectedStdDevs[5].increment(_longValues[i]);
+ expectedStdDevs[6].increment(_floatValues[i]);
+ expectedStdDevs[7].increment(_doubleValues[i]);
+ }
+
+ double expectedIntSum = Arrays.stream(_intValues).asDoubleStream().sum();
+ double expectedLongSum = Arrays.stream(_longValues).asDoubleStream().sum();
+ double expectedFloatSum = 0.0;
+ for (int i = 0; i < _floatValues.length; i++) {
+ expectedFloatSum += _floatValues[i];
+ }
+ double expectedDoubleSum = Arrays.stream(_doubleValues).sum();
+
+ // Compute the query
+ String query =
+ "SELECT STDDEV_POP(intColumn), STDDEV_POP(longColumn), STDDEV_POP(floatColumn), STDDEV_POP(doubleColumn),"
+ + "STDDEV_SAMP(intColumn), STDDEV_SAMP(longColumn), STDDEV_SAMP(floatColumn), STDDEV_SAMP(doubleColumn) "
+ + "FROM testTable";
+ AggregationOperator aggregationOperator = getOperator(query);
+ AggregationResultsBlock resultsBlock = aggregationOperator.nextBlock();
+ QueriesTestUtils.testInnerSegmentExecutionStatistics(aggregationOperator.getExecutionStatistics(), NUM_RECORDS, 0,
+ NUM_RECORDS * 4, NUM_RECORDS);
+ List<Object> aggregationResult = resultsBlock.getResults();
+
+ // Validate the aggregation results
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(0), NUM_RECORDS, expectedIntSum,
+ expectedStdDevs[0].getResult(), false);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(1), NUM_RECORDS, expectedLongSum,
+ expectedStdDevs[1].getResult(), false);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(2), NUM_RECORDS, expectedFloatSum,
+ expectedStdDevs[2].getResult(), false);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(3), NUM_RECORDS, expectedDoubleSum,
+ expectedStdDevs[3].getResult(), false);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(4), NUM_RECORDS, expectedIntSum,
+ expectedStdDevs[4].getResult(), true);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(5), NUM_RECORDS, expectedLongSum,
+ expectedStdDevs[5].getResult(), true);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(6), NUM_RECORDS, expectedFloatSum,
+ expectedStdDevs[6].getResult(), true);
+ checkWithPrecisionForStandardDeviation((VarianceTuple) aggregationResult.get(7), NUM_RECORDS, expectedDoubleSum,
+ expectedStdDevs[7].getResult(), true);
+
+ // Update the expected result by 3 more times (broker query will compute 4 identical segments)
Review Comment:
The variance on 4 identical segments is the same as variance on one of these segments. Should probably to consider using `getDistinctInstances` in `BaseQueriesTest`
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