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

Example 1 with StringGenerationOption

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

the class TestVectorSubStr method doTests.

private void doTests(Random random, boolean useLength) throws Exception {
    String typeName = "string";
    TypeInfo typeInfo = TypeInfoFactory.stringTypeInfo;
    TypeInfo targetTypeInfo = typeInfo;
    String functionName = "substr";
    List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    List<String> columns = new ArrayList<String>();
    int columnNum = 1;
    ExprNodeDesc col1Expr;
    StringGenerationOption stringGenerationOption = new StringGenerationOption(true, true);
    generationSpecList.add(GenerationSpec.createStringFamily(typeInfo, stringGenerationOption));
    explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
    String columnName = "col" + (columnNum++);
    col1Expr = new ExprNodeColumnDesc(typeInfo, columnName, "table", false);
    columns.add(columnName);
    VectorRandomRowSource rowSource = new VectorRandomRowSource();
    rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
    children.add(col1Expr);
    final int position = 10 - random.nextInt(21);
    Object scalar2Object = Integer.valueOf(position);
    ExprNodeDesc col2Expr = new ExprNodeConstantDesc(TypeInfoFactory.intTypeInfo, scalar2Object);
    children.add(col2Expr);
    if (useLength) {
        Object scalar3Object = random.nextInt(12);
        ExprNodeDesc col3Expr = new ExprNodeConstantDesc(TypeInfoFactory.intTypeInfo, scalar3Object);
        children.add(col3Expr);
    }
    // ----------------------------------------------------------------------------------------------
    String[] columnNames = columns.toArray(new String[0]);
    String[] outputScratchTypeNames = new String[] { targetTypeInfo.getTypeName() };
    DataTypePhysicalVariation[] outputDataTypePhysicalVariations = new DataTypePhysicalVariation[] { DataTypePhysicalVariation.NONE };
    VectorizedRowBatchCtx batchContext = new VectorizedRowBatchCtx(columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), /* dataColumnNums */
    null, /* partitionColumnCount */
    0, /* virtualColumnCount */
    0, /* neededVirtualColumns */
    null, outputScratchTypeNames, outputDataTypePhysicalVariations);
    Object[][] randomRows = rowSource.randomRows(100000);
    VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
    GenericUDF genericUdf;
    FunctionInfo funcInfo = null;
    try {
        funcInfo = FunctionRegistry.getFunctionInfo(functionName);
    } catch (SemanticException e) {
        Assert.fail("Failed to load " + functionName + " " + e);
    }
    genericUdf = funcInfo.getGenericUDF();
    final int rowCount = randomRows.length;
    Object[][] resultObjectsArray = new Object[SubStrTestMode.count][];
    for (int i = 0; i < SubStrTestMode.count; i++) {
        Object[] resultObjects = new Object[rowCount];
        resultObjectsArray[i] = resultObjects;
        SubStrTestMode subStrTestMode = SubStrTestMode.values()[i];
        switch(subStrTestMode) {
            case ROW_MODE:
                doRowIfTest(typeInfo, targetTypeInfo, columns, children, randomRows, rowSource.rowStructObjectInspector(), genericUdf, resultObjects);
                break;
            case ADAPTOR:
            case VECTOR_EXPRESSION:
                doVectorIfTest(typeInfo, targetTypeInfo, columns, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), children, subStrTestMode, batchSource, batchContext, genericUdf, resultObjects);
                break;
            default:
                throw new RuntimeException("Unexpected STRING Unary test mode " + subStrTestMode);
        }
    }
    for (int i = 0; i < rowCount; i++) {
        // Row-mode is the expected value.
        Object expectedResult = resultObjectsArray[0][i];
        for (int v = 1; v < SubStrTestMode.count; v++) {
            Object vectorResult = resultObjectsArray[v][i];
            if (expectedResult == null || vectorResult == null) {
                if (expectedResult != null || vectorResult != null) {
                    Assert.fail("Row " + i + " " + SubStrTestMode.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 (!expectedResult.equals(vectorResult)) {
                    Assert.fail("Row " + i + " " + SubStrTestMode.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 2 with StringGenerationOption

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

the class TestVectorStringUnary method doTests.

private void doTests(Random random, String typeName, String functionName) throws Exception {
    TypeInfo typeInfo = TypeInfoUtils.getTypeInfoFromTypeString(typeName);
    TypeInfo targetTypeInfo;
    if (functionName.equals("char_length") || functionName.equals("length") || functionName.equals("octet_length")) {
        targetTypeInfo = TypeInfoFactory.intTypeInfo;
    } else {
        targetTypeInfo = typeInfo;
    }
    List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    List<String> columns = new ArrayList<String>();
    int columnNum = 1;
    ExprNodeDesc col1Expr;
    StringGenerationOption stringGenerationOption = new StringGenerationOption(true, true);
    generationSpecList.add(GenerationSpec.createStringFamily(typeInfo, stringGenerationOption));
    explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
    String columnName = "col" + (columnNum++);
    col1Expr = new ExprNodeColumnDesc(typeInfo, columnName, "table", false);
    columns.add(columnName);
    VectorRandomRowSource rowSource = new VectorRandomRowSource();
    rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
    children.add(col1Expr);
    // ----------------------------------------------------------------------------------------------
    String[] columnNames = columns.toArray(new String[0]);
    String[] outputScratchTypeNames = new String[] { targetTypeInfo.getTypeName() };
    DataTypePhysicalVariation[] outputDataTypePhysicalVariations = new DataTypePhysicalVariation[] { DataTypePhysicalVariation.NONE };
    VectorizedRowBatchCtx batchContext = new VectorizedRowBatchCtx(columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), /* dataColumnNums */
    null, /* partitionColumnCount */
    0, /* virtualColumnCount */
    0, /* neededVirtualColumns */
    null, outputScratchTypeNames, outputDataTypePhysicalVariations);
    Object[][] randomRows = rowSource.randomRows(100000);
    VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
    GenericUDF genericUdf;
    FunctionInfo funcInfo = null;
    try {
        funcInfo = FunctionRegistry.getFunctionInfo(functionName);
    } catch (SemanticException e) {
        Assert.fail("Failed to load " + functionName + " " + e);
    }
    genericUdf = funcInfo.getGenericUDF();
    final int rowCount = randomRows.length;
    Object[][] resultObjectsArray = new Object[StringUnaryTestMode.count][];
    for (int i = 0; i < StringUnaryTestMode.count; i++) {
        Object[] resultObjects = new Object[rowCount];
        resultObjectsArray[i] = resultObjects;
        StringUnaryTestMode stringUnaryTestMode = StringUnaryTestMode.values()[i];
        switch(stringUnaryTestMode) {
            case ROW_MODE:
                doRowIfTest(typeInfo, targetTypeInfo, columns, children, randomRows, rowSource.rowStructObjectInspector(), genericUdf, resultObjects);
                break;
            case ADAPTOR:
            case VECTOR_EXPRESSION:
                doVectorIfTest(typeInfo, targetTypeInfo, columns, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), children, stringUnaryTestMode, batchSource, batchContext, genericUdf, resultObjects);
                break;
            default:
                throw new RuntimeException("Unexpected STRING Unary test mode " + stringUnaryTestMode);
        }
    }
    for (int i = 0; i < rowCount; i++) {
        // Row-mode is the expected value.
        Object expectedResult = resultObjectsArray[0][i];
        for (int v = 1; v < StringUnaryTestMode.count; v++) {
            Object vectorResult = resultObjectsArray[v][i];
            if (expectedResult == null || vectorResult == null) {
                if (expectedResult != null || vectorResult != null) {
                    Assert.fail("Row " + i + " " + StringUnaryTestMode.values()[v] + " typeName " + typeName + " result is NULL " + (vectorResult == null) + " does not match row-mode expected result is NULL " + (expectedResult == null) + " functionName " + functionName + " genericUdf " + genericUdf.getClass().getSimpleName());
                }
            } else {
                if (!expectedResult.equals(vectorResult)) {
                    Assert.fail("Row " + i + " " + StringUnaryTestMode.values()[v] + " typeName " + typeName + " result \"" + vectorResult.toString() + "\"" + " (" + vectorResult.getClass().getSimpleName() + ")" + " does not match row-mode expected result \"" + expectedResult.toString() + "\"" + " (" + expectedResult.getClass().getSimpleName() + ")" + " functionName " + functionName + " genericUdf " + genericUdf.getClass().getSimpleName());
                }
            }
        }
    }
}