Examples with VectorRandomBatchSource org.apache.hadoop.hive.ql.exec.vector.VectorRandomBatchSource used on opensource projects

Example 1 with VectorRandomBatchSource

use of org.apache.hadoop.hive.ql.exec.vector.VectorRandomBatchSource in project hive by apache.

the class AbstractMapJoin method setupMapJoin.

protected void setupMapJoin(HiveConf hiveConf, long seed, int rowCount, VectorMapJoinVariation vectorMapJoinVariation, MapJoinTestImplementation mapJoinImplementation, String[] bigTableColumnNames, TypeInfo[] bigTableTypeInfos, int[] bigTableKeyColumnNums, String[] smallTableValueColumnNames, TypeInfo[] smallTableValueTypeInfos, int[] bigTableRetainColumnNums, int[] smallTableRetainKeyColumnNums, int[] smallTableRetainValueColumnNums, SmallTableGenerationParameters smallTableGenerationParameters) throws Exception {
    this.vectorMapJoinVariation = vectorMapJoinVariation;
    this.mapJoinImplementation = mapJoinImplementation;
    testDesc = new MapJoinTestDescription(hiveConf, vectorMapJoinVariation, bigTableTypeInfos, bigTableKeyColumnNums, smallTableValueTypeInfos, smallTableRetainKeyColumnNums, smallTableGenerationParameters, MapJoinPlanVariation.DYNAMIC_PARTITION_HASH_JOIN);
    // Prepare data.  Good for ANY implementation variation.
    testData = new MapJoinTestData(rowCount, testDesc, seed);
    ObjectRegistryImpl objectRegistry = new ObjectRegistryImpl();
    ObjectCache.setupObjectRegistry(objectRegistry);
    operator = setupBenchmarkImplementation(mapJoinImplementation, testDesc, testData);
    isVectorOutput = isVectorOutput(mapJoinImplementation);
    /*
     * We don't measure data generation execution cost -- generate the big table into memory first.
     */
    if (!isVectorOutput) {
        bigTableRows = testData.getBigTableBatchSource().getRandomRows();
    } else {
        ArrayList<VectorizedRowBatch> bigTableBatchList = new ArrayList<VectorizedRowBatch>();
        VectorRandomBatchSource batchSource = testData.getBigTableBatchSource();
        batchSource.resetBatchIteration();
        while (true) {
            VectorizedRowBatch batch = testData.createBigTableBatch(testDesc);
            if (!batchSource.fillNextBatch(batch)) {
                break;
            }
            bigTableBatchList.add(batch);
        }
        bigTableBatches = bigTableBatchList.toArray(new VectorizedRowBatch[0]);
    }
}

Example 2 with VectorRandomBatchSource

use of org.apache.hadoop.hive.ql.exec.vector.VectorRandomBatchSource in project hive by apache.

the class TestVectorBetweenIn method doBetweenInVariation.

private boolean doBetweenInVariation(Random random, String typeName, boolean tryDecimal64, BetweenInVariation betweenInVariation, int subVariation) throws Exception {
    TypeInfo typeInfo = TypeInfoUtils.getTypeInfoFromTypeString(typeName);
    boolean isDecimal64 = checkDecimal64(tryDecimal64, typeInfo);
    DataTypePhysicalVariation dataTypePhysicalVariation = (isDecimal64 ? DataTypePhysicalVariation.DECIMAL_64 : DataTypePhysicalVariation.NONE);
    final int decimal64Scale = (isDecimal64 ? ((DecimalTypeInfo) typeInfo).getScale() : 0);
    // ----------------------------------------------------------------------------------------------
    ObjectInspector objectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(typeInfo);
    final int valueCount = 10 + random.nextInt(10);
    List<Object> valueList = new ArrayList<Object>(valueCount);
    for (int i = 0; i < valueCount; i++) {
        valueList.add(VectorRandomRowSource.randomWritable(random, typeInfo, objectInspector, dataTypePhysicalVariation, /* allowNull */
        false));
    }
    final boolean isBetween = (betweenInVariation == BetweenInVariation.FILTER_BETWEEN || betweenInVariation == BetweenInVariation.FILTER_NOT_BETWEEN || betweenInVariation == BetweenInVariation.PROJECTION_BETWEEN || betweenInVariation == BetweenInVariation.PROJECTION_NOT_BETWEEN);
    List<Object> compareList = new ArrayList<Object>();
    List<Object> sortedList = new ArrayList<Object>(valueCount);
    sortedList.addAll(valueList);
    Object exampleObject = valueList.get(0);
    WritableComparator writableComparator = WritableComparator.get((Class<? extends WritableComparable>) exampleObject.getClass());
    sortedList.sort(writableComparator);
    final boolean isInvert;
    if (isBetween) {
        // FILTER_BETWEEN
        // FILTER_NOT_BETWEEN
        // PROJECTION_BETWEEN
        // PROJECTION_NOT_BETWEEN
        isInvert = (betweenInVariation == BetweenInVariation.FILTER_NOT_BETWEEN || betweenInVariation == BetweenInVariation.PROJECTION_NOT_BETWEEN);
        switch(subVariation) {
            case 0:
                // Range covers all values exactly.
                compareList.add(sortedList.get(0));
                compareList.add(sortedList.get(valueCount - 1));
                break;
            case 1:
                // Exclude the first and last sorted.
                compareList.add(sortedList.get(1));
                compareList.add(sortedList.get(valueCount - 2));
                break;
            case 2:
                // Only last 2 sorted.
                compareList.add(sortedList.get(valueCount - 2));
                compareList.add(sortedList.get(valueCount - 1));
                break;
            case 3:
            case 4:
            case 5:
            case 6:
                {
                    // Choose 2 adjacent in the middle.
                    Object min = sortedList.get(5);
                    Object max = sortedList.get(6);
                    compareList.add(min);
                    compareList.add(max);
                    if (subVariation == 4) {
                        removeValue(valueList, min);
                    } else if (subVariation == 5) {
                        removeValue(valueList, max);
                    } else if (subVariation == 6) {
                        removeValue(valueList, min);
                        removeValue(valueList, max);
                    }
                }
                break;
            default:
                return false;
        }
    } else {
        // FILTER_IN.
        // PROJECTION_IN.
        isInvert = false;
        switch(subVariation) {
            case 0:
                // All values.
                compareList.addAll(valueList);
                break;
            case 1:
                // Don't include the first and last sorted.
                for (int i = 1; i < valueCount - 1; i++) {
                    compareList.add(valueList.get(i));
                }
                break;
            case 2:
                // The even ones.
                for (int i = 2; i < valueCount; i += 2) {
                    compareList.add(valueList.get(i));
                }
                break;
            case 3:
                {
                    // Choose 2 adjacent in the middle.
                    Object min = sortedList.get(5);
                    Object max = sortedList.get(6);
                    compareList.add(min);
                    compareList.add(max);
                    if (subVariation == 4) {
                        removeValue(valueList, min);
                    } else if (subVariation == 5) {
                        removeValue(valueList, max);
                    } else if (subVariation == 6) {
                        removeValue(valueList, min);
                        removeValue(valueList, max);
                    }
                }
                break;
            default:
                return false;
        }
    }
    // ----------------------------------------------------------------------------------------------
    GenerationSpec generationSpec = GenerationSpec.createValueList(typeInfo, valueList);
    List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    generationSpecList.add(generationSpec);
    explicitDataTypePhysicalVariationList.add(dataTypePhysicalVariation);
    VectorRandomRowSource rowSource = new VectorRandomRowSource();
    rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    List<String> columns = new ArrayList<String>();
    String col1Name = rowSource.columnNames().get(0);
    columns.add(col1Name);
    final ExprNodeDesc col1Expr = new ExprNodeColumnDesc(typeInfo, col1Name, "table", false);
    List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
    if (isBetween) {
        children.add(new ExprNodeConstantDesc(Boolean.valueOf(isInvert)));
    }
    children.add(col1Expr);
    for (Object compareObject : compareList) {
        ExprNodeConstantDesc constDesc = new ExprNodeConstantDesc(typeInfo, VectorRandomRowSource.getNonWritableObject(compareObject, typeInfo, objectInspector));
        children.add(constDesc);
    }
    String[] columnNames = columns.toArray(new String[0]);
    Object[][] randomRows = rowSource.randomRows(100000);
    VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
    final GenericUDF udf;
    final ObjectInspector outputObjectInspector;
    if (isBetween) {
        udf = new GenericUDFBetween();
        // First argument is boolean invert. Arguments 1..3 are inspectors for range limits...
        ObjectInspector[] argumentOIs = new ObjectInspector[4];
        argumentOIs[0] = PrimitiveObjectInspectorFactory.writableBooleanObjectInspector;
        argumentOIs[1] = objectInspector;
        argumentOIs[2] = objectInspector;
        argumentOIs[3] = objectInspector;
        outputObjectInspector = udf.initialize(argumentOIs);
    } else {
        final int compareCount = compareList.size();
        udf = new GenericUDFIn();
        ObjectInspector[] argumentOIs = new ObjectInspector[compareCount];
        ConstantObjectInspector constantObjectInspector = (ConstantObjectInspector) children.get(1).getWritableObjectInspector();
        for (int i = 0; i < compareCount; i++) {
            argumentOIs[i] = constantObjectInspector;
        }
        outputObjectInspector = udf.initialize(argumentOIs);
    }
    TypeInfo outputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(outputObjectInspector);
    ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(TypeInfoFactory.booleanTypeInfo, udf, children);
    return executeTestModesAndVerify(typeInfo, betweenInVariation, compareList, columns, columnNames, children, udf, exprDesc, randomRows, rowSource, batchSource, outputTypeInfo, /* skipAdaptor */
    false);
}

Example 3 with VectorRandomBatchSource

use of org.apache.hadoop.hive.ql.exec.vector.VectorRandomBatchSource in project hive by apache.

the class TestVectorBetweenIn method doBetweenStructInVariation.

private boolean doBetweenStructInVariation(Random random, String structTypeName, BetweenInVariation betweenInVariation) throws Exception {
    StructTypeInfo structTypeInfo = (StructTypeInfo) TypeInfoUtils.getTypeInfoFromTypeString(structTypeName);
    ObjectInspector structObjectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(structTypeInfo);
    final int valueCount = 10 + random.nextInt(10);
    List<Object> valueList = new ArrayList<Object>(valueCount);
    for (int i = 0; i < valueCount; i++) {
        valueList.add(VectorRandomRowSource.randomWritable(random, structTypeInfo, structObjectInspector, DataTypePhysicalVariation.NONE, /* allowNull */
        false));
    }
    final boolean isInvert = false;
    // No convenient WritableComparator / WritableComparable available for STRUCT.
    List<Object> compareList = new ArrayList<Object>();
    Set<Integer> includedSet = new HashSet<Integer>();
    final int chooseLimit = 4 + random.nextInt(valueCount / 2);
    int chooseCount = 0;
    while (chooseCount < chooseLimit) {
        final int index = random.nextInt(valueCount);
        if (includedSet.contains(index)) {
            continue;
        }
        includedSet.add(index);
        compareList.add(valueList.get(index));
        chooseCount++;
    }
    // ----------------------------------------------------------------------------------------------
    GenerationSpec structGenerationSpec = GenerationSpec.createValueList(structTypeInfo, valueList);
    List<GenerationSpec> structGenerationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> structExplicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    structGenerationSpecList.add(structGenerationSpec);
    structExplicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
    VectorRandomRowSource structRowSource = new VectorRandomRowSource();
    structRowSource.initGenerationSpecSchema(random, structGenerationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, structExplicitDataTypePhysicalVariationList);
    Object[][] structRandomRows = structRowSource.randomRows(100000);
    // ---------------------------------------------------------------------------------------------
    List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    List<TypeInfo> fieldTypeInfoList = structTypeInfo.getAllStructFieldTypeInfos();
    final int fieldCount = fieldTypeInfoList.size();
    for (int i = 0; i < fieldCount; i++) {
        GenerationSpec generationSpec = GenerationSpec.createOmitGeneration(fieldTypeInfoList.get(i));
        generationSpecList.add(generationSpec);
        explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
    }
    VectorRandomRowSource rowSource = new VectorRandomRowSource();
    rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    Object[][] randomRows = rowSource.randomRows(100000);
    final int rowCount = randomRows.length;
    for (int r = 0; r < rowCount; r++) {
        List<Object> fieldValueList = (ArrayList) structRandomRows[r][0];
        for (int f = 0; f < fieldCount; f++) {
            randomRows[r][f] = fieldValueList.get(f);
        }
    }
    // ---------------------------------------------------------------------------------------------
    // Currently, STRUCT IN vectorization assumes a GenericUDFStruct.
    List<ObjectInspector> structUdfObjectInspectorList = new ArrayList<ObjectInspector>();
    List<ExprNodeDesc> structUdfChildren = new ArrayList<ExprNodeDesc>(fieldCount);
    List<String> rowColumnNameList = rowSource.columnNames();
    for (int i = 0; i < fieldCount; i++) {
        TypeInfo fieldTypeInfo = fieldTypeInfoList.get(i);
        ExprNodeColumnDesc fieldExpr = new ExprNodeColumnDesc(fieldTypeInfo, rowColumnNameList.get(i), "table", false);
        structUdfChildren.add(fieldExpr);
        ObjectInspector fieldObjectInspector = VectorRandomRowSource.getObjectInspector(fieldTypeInfo, DataTypePhysicalVariation.NONE);
        structUdfObjectInspectorList.add(fieldObjectInspector);
    }
    StandardStructObjectInspector structUdfObjectInspector = ObjectInspectorFactory.getStandardStructObjectInspector(rowColumnNameList, structUdfObjectInspectorList);
    String structUdfTypeName = structUdfObjectInspector.getTypeName();
    TypeInfo structUdfTypeInfo = TypeInfoUtils.getTypeInfoFromTypeString(structUdfTypeName);
    String structFuncText = "struct";
    FunctionInfo fi = FunctionRegistry.getFunctionInfo(structFuncText);
    GenericUDF genericUDF = fi.getGenericUDF();
    ExprNodeDesc col1Expr = new ExprNodeGenericFuncDesc(structUdfObjectInspector, genericUDF, structFuncText, structUdfChildren);
    // ---------------------------------------------------------------------------------------------
    List<String> columns = new ArrayList<String>();
    List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
    children.add(col1Expr);
    for (int i = 0; i < compareList.size(); i++) {
        Object compareObject = compareList.get(i);
        ExprNodeConstantDesc constDesc = new ExprNodeConstantDesc(structUdfTypeInfo, VectorRandomRowSource.getNonWritableObject(compareObject, structUdfTypeInfo, structUdfObjectInspector));
        children.add(constDesc);
    }
    for (int i = 0; i < fieldCount; i++) {
        columns.add(rowColumnNameList.get(i));
    }
    String[] columnNames = columns.toArray(new String[0]);
    VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
    // ---------------------------------------------------------------------------------------------
    final GenericUDF udf = new GenericUDFIn();
    final int compareCount = compareList.size();
    ObjectInspector[] argumentOIs = new ObjectInspector[compareCount];
    for (int i = 0; i < compareCount; i++) {
        argumentOIs[i] = structUdfObjectInspector;
    }
    final ObjectInspector outputObjectInspector = udf.initialize(argumentOIs);
    TypeInfo outputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(outputObjectInspector);
    ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(TypeInfoFactory.booleanTypeInfo, udf, children);
    return executeTestModesAndVerify(structUdfTypeInfo, betweenInVariation, compareList, columns, columnNames, children, udf, exprDesc, randomRows, rowSource, batchSource, outputTypeInfo, /* skipAdaptor */
    true);
}

Example 4 with VectorRandomBatchSource

use of org.apache.hadoop.hive.ql.exec.vector.VectorRandomBatchSource in project hive by apache.

the class TestVectorCastStatement method doIfTestOneCast.

private void doIfTestOneCast(Random random, String typeName, DataTypePhysicalVariation dataTypePhysicalVariation, PrimitiveCategory targetPrimitiveCategory) throws Exception {
    TypeInfo typeInfo = TypeInfoUtils.getTypeInfoFromTypeString(typeName);
    PrimitiveCategory primitiveCategory = ((PrimitiveTypeInfo) typeInfo).getPrimitiveCategory();
    boolean isDecimal64 = (dataTypePhysicalVariation == DataTypePhysicalVariation.DECIMAL_64);
    final int decimal64Scale = (isDecimal64 ? ((DecimalTypeInfo) typeInfo).getScale() : 0);
    // ----------------------------------------------------------------------------------------------
    String targetTypeName;
    if (targetPrimitiveCategory == PrimitiveCategory.BYTE) {
        targetTypeName = "tinyint";
    } else if (targetPrimitiveCategory == PrimitiveCategory.SHORT) {
        targetTypeName = "smallint";
    } else if (targetPrimitiveCategory == PrimitiveCategory.LONG) {
        targetTypeName = "bigint";
    } else {
        targetTypeName = targetPrimitiveCategory.name().toLowerCase();
    }
    targetTypeName = VectorRandomRowSource.getDecoratedTypeName(random, targetTypeName);
    TypeInfo targetTypeInfo = TypeInfoUtils.getTypeInfoFromTypeString(targetTypeName);
    // ----------------------------------------------------------------------------------------------
    GenerationSpec generationSpec;
    if (needsValidDataTypeData(targetTypeInfo) && (primitiveCategory == PrimitiveCategory.STRING || primitiveCategory == PrimitiveCategory.CHAR || primitiveCategory == PrimitiveCategory.VARCHAR)) {
        generationSpec = GenerationSpec.createStringFamilyOtherTypeValue(typeInfo, targetTypeInfo);
    } else {
        generationSpec = GenerationSpec.createSameType(typeInfo);
    }
    List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    generationSpecList.add(generationSpec);
    explicitDataTypePhysicalVariationList.add(dataTypePhysicalVariation);
    VectorRandomRowSource rowSource = new VectorRandomRowSource();
    rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    List<String> columns = new ArrayList<String>();
    columns.add("col1");
    ExprNodeColumnDesc col1Expr = new ExprNodeColumnDesc(typeInfo, "col1", "table", false);
    List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
    children.add(col1Expr);
    String[] columnNames = columns.toArray(new String[0]);
    Object[][] randomRows = rowSource.randomRows(100000);
    VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
    final int rowCount = randomRows.length;
    Object[][] resultObjectsArray = new Object[CastStmtTestMode.count][];
    for (int i = 0; i < CastStmtTestMode.count; i++) {
        Object[] resultObjects = new Object[rowCount];
        resultObjectsArray[i] = resultObjects;
        CastStmtTestMode ifStmtTestMode = CastStmtTestMode.values()[i];
        switch(ifStmtTestMode) {
            case ROW_MODE:
                if (!doRowCastTest(typeInfo, targetTypeInfo, columns, children, randomRows, rowSource.rowStructObjectInspector(), resultObjects)) {
                    return;
                }
                break;
            case ADAPTOR:
            case VECTOR_EXPRESSION:
                if (!doVectorCastTest(typeInfo, targetTypeInfo, columns, columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), children, ifStmtTestMode, batchSource, resultObjects)) {
                    return;
                }
                break;
            default:
                throw new RuntimeException("Unexpected IF statement test mode " + ifStmtTestMode);
        }
    }
    for (int i = 0; i < rowCount; i++) {
        // Row-mode is the expected value.
        Object expectedResult = resultObjectsArray[0][i];
        for (int v = 1; v < CastStmtTestMode.count; v++) {
            Object vectorResult = resultObjectsArray[v][i];
            if (expectedResult == null || vectorResult == null) {
                if (expectedResult != null || vectorResult != null) {
                    Assert.fail("Row " + i + " sourceTypeName " + typeName + " targetTypeName " + targetTypeName + " " + CastStmtTestMode.values()[v] + " result is NULL " + (vectorResult == null ? "YES" : "NO result " + vectorResult.toString()) + " does not match row-mode expected result is NULL " + (expectedResult == null ? "YES" : "NO result " + expectedResult.toString()) + " row values " + Arrays.toString(randomRows[i]));
                }
            } else {
                if (isDecimal64 && expectedResult instanceof LongWritable) {
                    HiveDecimalWritable expectedHiveDecimalWritable = new HiveDecimalWritable(0);
                    expectedHiveDecimalWritable.deserialize64(((LongWritable) expectedResult).get(), decimal64Scale);
                    expectedResult = expectedHiveDecimalWritable;
                }
                if (!expectedResult.equals(vectorResult)) {
                    Assert.fail("Row " + i + " sourceTypeName " + typeName + " targetTypeName " + targetTypeName + " " + CastStmtTestMode.values()[v] + " result " + vectorResult.toString() + " (" + vectorResult.getClass().getSimpleName() + ")" + " does not match row-mode expected result " + expectedResult.toString() + " (" + expectedResult.getClass().getSimpleName() + ")" + " row values " + Arrays.toString(randomRows[i]));
                }
            }
        }
    }
}

Example 5 with VectorRandomBatchSource

use of org.apache.hadoop.hive.ql.exec.vector.VectorRandomBatchSource in project hive by apache.

the class TestVectorAggregation method doTests.

private void doTests(Random random, String aggregationName, TypeInfo typeInfo, boolean isCountStar, boolean tryDecimal64) throws Exception {
    List<GenerationSpec> dataAggrGenerationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    TypeInfo keyTypeInfo = TypeInfoFactory.shortTypeInfo;
    GenerationSpec keyGenerationSpec = GenerationSpec.createOmitGeneration(keyTypeInfo);
    dataAggrGenerationSpecList.add(keyGenerationSpec);
    explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
    final boolean decimal64Enable = checkDecimal64(tryDecimal64, typeInfo);
    GenerationSpec generationSpec = GenerationSpec.createSameType(typeInfo);
    dataAggrGenerationSpecList.add(generationSpec);
    explicitDataTypePhysicalVariationList.add(decimal64Enable ? DataTypePhysicalVariation.DECIMAL_64 : DataTypePhysicalVariation.NONE);
    List<String> columns = new ArrayList<String>();
    columns.add("col0");
    columns.add("col1");
    ExprNodeColumnDesc dataAggrCol1Expr = new ExprNodeColumnDesc(typeInfo, "col1", "table", false);
    List<ExprNodeDesc> dataAggrParameters = new ArrayList<ExprNodeDesc>();
    if (!isCountStar) {
        dataAggrParameters.add(dataAggrCol1Expr);
    }
    final int dataAggrParameterCount = dataAggrParameters.size();
    ObjectInspector[] dataAggrParameterObjectInspectors = new ObjectInspector[dataAggrParameterCount];
    for (int i = 0; i < dataAggrParameterCount; i++) {
        TypeInfo paramTypeInfo = dataAggrParameters.get(i).getTypeInfo();
        dataAggrParameterObjectInspectors[i] = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(paramTypeInfo);
    }
    String[] columnNames = columns.toArray(new String[0]);
    final int dataAggrMaxKeyCount = 20000;
    final int reductionFactor = 16;
    ObjectInspector keyObjectInspector = VectorRandomRowSource.getObjectInspector(keyTypeInfo);
    /*
     * PARTIAL1.
     */
    VectorRandomRowSource partial1RowSource = new VectorRandomRowSource();
    boolean allowNull = !aggregationName.equals("bloom_filter");
    partial1RowSource.initGenerationSpecSchema(random, dataAggrGenerationSpecList, /* maxComplexDepth */
    0, allowNull, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    Object[][] partial1RandomRows = partial1RowSource.randomRows(TEST_ROW_COUNT);
    final int partial1RowCount = partial1RandomRows.length;
    for (int i = 0; i < partial1RowCount; i++) {
        final short shortKey = (short) getLinearRandomNumber(random, dataAggrMaxKeyCount);
        partial1RandomRows[i][0] = ((WritableShortObjectInspector) keyObjectInspector).create((short) shortKey);
    }
    VectorRandomBatchSource partial1BatchSource = VectorRandomBatchSource.createInterestingBatches(random, partial1RowSource, partial1RandomRows, null);
    GenericUDAFEvaluator partial1Evaluator = getEvaluator(aggregationName, typeInfo);
    if (isCountStar) {
        Assert.assertTrue(partial1Evaluator instanceof GenericUDAFCountEvaluator);
        GenericUDAFCountEvaluator countEvaluator = (GenericUDAFCountEvaluator) partial1Evaluator;
        countEvaluator.setCountAllColumns(true);
    }
    /*
    System.out.println(
        "*DEBUG* GenericUDAFEvaluator for " + aggregationName + ", " + typeInfo.getTypeName() + ": " +
            partial1Evaluator.getClass().getSimpleName());
    */
    // The only way to get the return object inspector (and its return type) is to
    // initialize it...
    final GenericUDAFEvaluator.Mode partial1UdafEvaluatorMode = GenericUDAFEvaluator.Mode.PARTIAL1;
    ObjectInspector partial1ReturnOI = partial1Evaluator.init(partial1UdafEvaluatorMode, dataAggrParameterObjectInspectors);
    TypeInfo partial1OutputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(partial1ReturnOI);
    Object[] partial1ResultsArray = new Object[AggregationTestMode.count];
    executeAggregationTests(aggregationName, typeInfo, partial1Evaluator, partial1OutputTypeInfo, partial1UdafEvaluatorMode, dataAggrMaxKeyCount, columns, columnNames, dataAggrParameters, partial1RandomRows, partial1RowSource, partial1BatchSource, tryDecimal64, partial1ResultsArray);
    verifyAggregationResults(typeInfo, partial1OutputTypeInfo, dataAggrMaxKeyCount, partial1UdafEvaluatorMode, partial1ResultsArray);
    final boolean hasDifferentCompleteExpr;
    if (varianceNames.contains(aggregationName)) {
        hasDifferentCompleteExpr = true;
    } else {
        switch(aggregationName) {
            case "avg":
                hasDifferentCompleteExpr = true;
                break;
            case "bloom_filter":
            case "count":
            case "max":
            case "min":
            case "sum":
                hasDifferentCompleteExpr = false;
                break;
            default:
                throw new RuntimeException("Unexpected aggregation name " + aggregationName);
        }
    }
    if (hasDifferentCompleteExpr) {
        /*
       * COMPLETE.
       */
        VectorRandomRowSource completeRowSource = new VectorRandomRowSource();
        completeRowSource.initGenerationSpecSchema(random, dataAggrGenerationSpecList, /* maxComplexDepth */
        0, /* allowNull */
        true, /* isUnicodeOk */
        true, explicitDataTypePhysicalVariationList);
        Object[][] completeRandomRows = completeRowSource.randomRows(TEST_ROW_COUNT);
        final int completeRowCount = completeRandomRows.length;
        for (int i = 0; i < completeRowCount; i++) {
            final short shortKey = (short) getLinearRandomNumber(random, dataAggrMaxKeyCount);
            completeRandomRows[i][0] = ((WritableShortObjectInspector) keyObjectInspector).create((short) shortKey);
        }
        VectorRandomBatchSource completeBatchSource = VectorRandomBatchSource.createInterestingBatches(random, completeRowSource, completeRandomRows, null);
        GenericUDAFEvaluator completeEvaluator = getEvaluator(aggregationName, typeInfo);
        /*
      System.out.println(
          "*DEBUG* GenericUDAFEvaluator for " + aggregationName + ", " + typeInfo.getTypeName() + ": " +
              completeEvaluator.getClass().getSimpleName());
      */
        // The only way to get the return object inspector (and its return type) is to
        // initialize it...
        final GenericUDAFEvaluator.Mode completeUdafEvaluatorMode = GenericUDAFEvaluator.Mode.COMPLETE;
        ObjectInspector completeReturnOI = completeEvaluator.init(completeUdafEvaluatorMode, dataAggrParameterObjectInspectors);
        TypeInfo completeOutputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(completeReturnOI);
        Object[] completeResultsArray = new Object[AggregationTestMode.count];
        executeAggregationTests(aggregationName, typeInfo, completeEvaluator, completeOutputTypeInfo, completeUdafEvaluatorMode, dataAggrMaxKeyCount, columns, columnNames, dataAggrParameters, completeRandomRows, completeRowSource, completeBatchSource, tryDecimal64, completeResultsArray);
        verifyAggregationResults(typeInfo, completeOutputTypeInfo, dataAggrMaxKeyCount, completeUdafEvaluatorMode, completeResultsArray);
    }
    final boolean hasDifferentPartial2Expr;
    if (varianceNames.contains(aggregationName)) {
        hasDifferentPartial2Expr = true;
    } else {
        switch(aggregationName) {
            case "avg":
                hasDifferentPartial2Expr = true;
                break;
            case "bloom_filter":
            case "count":
            case "max":
            case "min":
            case "sum":
                hasDifferentPartial2Expr = false;
                break;
            default:
                throw new RuntimeException("Unexpected aggregation name " + aggregationName);
        }
    }
    if (hasDifferentPartial2Expr) {
        /*
       * PARTIAL2.
       */
        final GenericUDAFEvaluator.Mode mergeUdafEvaluatorMode = GenericUDAFEvaluator.Mode.PARTIAL2;
        doMerge(mergeUdafEvaluatorMode, random, aggregationName, typeInfo, keyGenerationSpec, columns, columnNames, dataAggrMaxKeyCount, reductionFactor, partial1OutputTypeInfo, partial1ResultsArray);
    }
    final boolean hasDifferentFinalExpr;
    if (varianceNames.contains(aggregationName)) {
        hasDifferentFinalExpr = true;
    } else {
        switch(aggregationName) {
            case "avg":
                hasDifferentFinalExpr = true;
                break;
            case "bloom_filter":
            case "count":
                hasDifferentFinalExpr = true;
                break;
            case "max":
            case "min":
            case "sum":
                hasDifferentFinalExpr = false;
                break;
            default:
                throw new RuntimeException("Unexpected aggregation name " + aggregationName);
        }
    }
    if (hasDifferentFinalExpr) {
        /*
       * FINAL.
       */
        final GenericUDAFEvaluator.Mode mergeUdafEvaluatorMode = GenericUDAFEvaluator.Mode.FINAL;
        doMerge(mergeUdafEvaluatorMode, random, aggregationName, typeInfo, keyGenerationSpec, columns, columnNames, dataAggrMaxKeyCount, reductionFactor, partial1OutputTypeInfo, partial1ResultsArray);
    }
}