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

Example 11 with VectorExtractRow

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

the class TestVectorSubStr method doVectorIfTest.

private void doVectorIfTest(TypeInfo typeInfo, TypeInfo targetTypeInfo, List<String> columns, TypeInfo[] typeInfos, DataTypePhysicalVariation[] dataTypePhysicalVariations, List<ExprNodeDesc> children, SubStrTestMode subStrTestMode, VectorRandomBatchSource batchSource, VectorizedRowBatchCtx batchContext, GenericUDF genericUdf, Object[] resultObjects) throws Exception {
    ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(targetTypeInfo, genericUdf, children);
    HiveConf hiveConf = new HiveConf();
    if (subStrTestMode == SubStrTestMode.ADAPTOR) {
        hiveConf.setBoolVar(HiveConf.ConfVars.HIVE_TEST_VECTOR_ADAPTOR_OVERRIDE, true);
    }
    VectorizationContext vectorizationContext = new VectorizationContext("name", columns, Arrays.asList(typeInfos), Arrays.asList(dataTypePhysicalVariations), hiveConf);
    VectorExpression vectorExpression = vectorizationContext.getVectorExpression(exprDesc);
    if (subStrTestMode == SubStrTestMode.VECTOR_EXPRESSION && vectorExpression instanceof VectorUDFAdaptor) {
        System.out.println("*NO NATIVE VECTOR EXPRESSION* typeInfo " + typeInfo.toString() + " subStrTestMode " + subStrTestMode + " vectorExpression " + vectorExpression.toString());
    }
    VectorizedRowBatch batch = batchContext.createVectorizedRowBatch();
    VectorExtractRow resultVectorExtractRow = new VectorExtractRow();
    resultVectorExtractRow.init(new TypeInfo[] { targetTypeInfo }, new int[] { columns.size() });
    Object[] scrqtchRow = new Object[1];
    // System.out.println("*VECTOR EXPRESSION* " + vectorExpression.getClass().getSimpleName());
    /*
    System.out.println(
        "*DEBUG* typeInfo " + typeInfo.toString() +
        " targetTypeInfo " + targetTypeInfo.toString() +
        " subStrTestMode " + subStrTestMode +
        " vectorExpression " + vectorExpression.getClass().getSimpleName());
    */
    batchSource.resetBatchIteration();
    int rowIndex = 0;
    while (true) {
        if (!batchSource.fillNextBatch(batch)) {
            break;
        }
        vectorExpression.evaluate(batch);
        extractResultObjects(batch, rowIndex, resultVectorExtractRow, scrqtchRow, targetTypeInfo, resultObjects);
        rowIndex += batch.size;
    }
}

Example 12 with VectorExtractRow

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

the class TestVectorIfStatement method doVectorIfTest.

private void doVectorIfTest(TypeInfo typeInfo, IfVariation ifVariation, List<String> columns, String[] columnNames, TypeInfo[] typeInfos, DataTypePhysicalVariation[] dataTypePhysicalVariations, List<ExprNodeDesc> children, IfStmtTestMode ifStmtTestMode, ColumnScalarMode columnScalarMode, VectorRandomBatchSource batchSource, Object[] resultObjects) throws Exception {
    final boolean isFilter = ifVariation.isFilter;
    GenericUDF udf;
    switch(ifStmtTestMode) {
        case VECTOR_EXPRESSION:
            udf = new GenericUDFIf();
            break;
        case ADAPTOR_WHEN:
            udf = new GenericUDFWhen();
            break;
        default:
            throw new RuntimeException("Unexpected IF statement test mode " + ifStmtTestMode);
    }
    ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(typeInfo, udf, children);
    String ifExprMode = (ifStmtTestMode != IfStmtTestMode.VECTOR_EXPRESSION ? "adaptor" : "good");
    HiveConf hiveConf = new HiveConf();
    hiveConf.setVar(HiveConf.ConfVars.HIVE_VECTORIZED_IF_EXPR_MODE, ifExprMode);
    VectorizationContext vectorizationContext = new VectorizationContext("name", columns, Arrays.asList(typeInfos), Arrays.asList(dataTypePhysicalVariations), hiveConf);
    VectorExpression vectorExpression = vectorizationContext.getVectorExpression(exprDesc, (isFilter ? VectorExpressionDescriptor.Mode.FILTER : VectorExpressionDescriptor.Mode.PROJECTION));
    final TypeInfo outputTypeInfo;
    final ObjectInspector objectInspector;
    if (!isFilter) {
        outputTypeInfo = vectorExpression.getOutputTypeInfo();
        objectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(outputTypeInfo);
    } else {
        outputTypeInfo = null;
        objectInspector = null;
    }
    if (ifStmtTestMode == IfStmtTestMode.VECTOR_EXPRESSION && vectorExpression instanceof VectorUDFAdaptor) {
        System.out.println("*NO NATIVE VECTOR EXPRESSION* typeInfo " + typeInfo.toString() + " ifStmtTestMode " + ifStmtTestMode + " ifVariation " + ifVariation + " columnScalarMode " + columnScalarMode + " vectorExpression " + vectorExpression.toString());
    }
    String[] outputScratchTypeNames = vectorizationContext.getScratchColumnTypeNames();
    DataTypePhysicalVariation[] outputDataTypePhysicalVariations = vectorizationContext.getScratchDataTypePhysicalVariations();
    VectorizedRowBatchCtx batchContext = new VectorizedRowBatchCtx(columnNames, typeInfos, dataTypePhysicalVariations, /* dataColumnNums */
    null, /* partitionColumnCount */
    0, /* virtualColumnCount */
    0, /* neededVirtualColumns */
    null, outputScratchTypeNames, outputDataTypePhysicalVariations);
    VectorizedRowBatch batch = batchContext.createVectorizedRowBatch();
    // System.out.println("*VECTOR EXPRESSION* " + vectorExpression.getClass().getSimpleName());
    /*
    System.out.println(
        "*DEBUG* typeInfo " + typeInfo.toString() +
        " ifStmtTestMode " + ifStmtTestMode +
        " ifVariation " + ifVariation +
        " columnScalarMode " + columnScalarMode +
        " vectorExpression " + vectorExpression.toString());
    */
    VectorExtractRow resultVectorExtractRow = null;
    Object[] scrqtchRow = null;
    if (!isFilter) {
        resultVectorExtractRow = new VectorExtractRow();
        final int outputColumnNum = vectorExpression.getOutputColumnNum();
        resultVectorExtractRow.init(new TypeInfo[] { outputTypeInfo }, new int[] { outputColumnNum });
        scrqtchRow = new Object[1];
    }
    boolean copySelectedInUse = false;
    int[] copySelected = new int[VectorizedRowBatch.DEFAULT_SIZE];
    batchSource.resetBatchIteration();
    int rowIndex = 0;
    while (true) {
        if (!batchSource.fillNextBatch(batch)) {
            break;
        }
        final int originalBatchSize = batch.size;
        if (isFilter) {
            copySelectedInUse = batch.selectedInUse;
            if (batch.selectedInUse) {
                System.arraycopy(batch.selected, 0, copySelected, 0, originalBatchSize);
            }
        }
        // In filter mode, the batch size can be made smaller.
        vectorExpression.evaluate(batch);
        if (!isFilter) {
            extractResultObjects(batch, rowIndex, resultVectorExtractRow, scrqtchRow, objectInspector, resultObjects);
        } else {
            final int currentBatchSize = batch.size;
            if (copySelectedInUse && batch.selectedInUse) {
                int selectIndex = 0;
                for (int i = 0; i < originalBatchSize; i++) {
                    final int originalBatchIndex = copySelected[i];
                    final boolean booleanResult;
                    if (selectIndex < currentBatchSize && batch.selected[selectIndex] == originalBatchIndex) {
                        booleanResult = true;
                        selectIndex++;
                    } else {
                        booleanResult = false;
                    }
                    resultObjects[rowIndex + i] = new BooleanWritable(booleanResult);
                }
            } else if (batch.selectedInUse) {
                int selectIndex = 0;
                for (int i = 0; i < originalBatchSize; i++) {
                    final boolean booleanResult;
                    if (selectIndex < currentBatchSize && batch.selected[selectIndex] == i) {
                        booleanResult = true;
                        selectIndex++;
                    } else {
                        booleanResult = false;
                    }
                    resultObjects[rowIndex + i] = new BooleanWritable(booleanResult);
                }
            } else if (currentBatchSize == 0) {
                // Whole batch got zapped.
                for (int i = 0; i < originalBatchSize; i++) {
                    resultObjects[rowIndex + i] = new BooleanWritable(false);
                }
            } else {
                // Every row kept.
                for (int i = 0; i < originalBatchSize; i++) {
                    resultObjects[rowIndex + i] = new BooleanWritable(true);
                }
            }
        }
        rowIndex += originalBatchSize;
    }
}

Example 13 with VectorExtractRow

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

the class FakeCaptureVectorToRowOutputOperator method initializeOp.

@Override
public void initializeOp(Configuration conf) throws HiveException {
    super.initializeOp(conf);
    VectorizationContextRegion vectorizationContextRegion = (VectorizationContextRegion) op;
    VectorizationContext outputVectorizationContext = vectorizationContextRegion.getOutputVectorizationContext();
    outputTypeInfos = outputVectorizationContext.getInitialTypeInfos();
    final int outputLength = outputTypeInfos.length;
    outputObjectInspectors = new ObjectInspector[outputLength];
    for (int i = 0; i < outputLength; i++) {
        TypeInfo typeInfo = outputTypeInfos[i];
        outputObjectInspectors[i] = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(typeInfo);
    }
    vectorExtractRow = new VectorExtractRow();
    vectorExtractRow.init(outputTypeInfos);
}

Example 14 with VectorExtractRow

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

the class TestVectorFilterCompare method doVectorFilterCompareTest.

private void doVectorFilterCompareTest(TypeInfo typeInfo1, TypeInfo typeInfo2, List<String> columns, String[] columnNames, TypeInfo[] typeInfos, DataTypePhysicalVariation[] dataTypePhysicalVariations, List<ExprNodeDesc> children, ExprNodeGenericFuncDesc exprDesc, Comparison comparison, FilterCompareTestMode filterCompareTestMode, ColumnScalarMode columnScalarMode, VectorRandomBatchSource batchSource, ObjectInspector objectInspector, TypeInfo outputTypeInfo, Object[] resultObjects) throws Exception {
    HiveConf hiveConf = new HiveConf();
    if (filterCompareTestMode == FilterCompareTestMode.ADAPTOR) {
        hiveConf.setBoolVar(HiveConf.ConfVars.HIVE_TEST_VECTOR_ADAPTOR_OVERRIDE, true);
        // Don't use DECIMAL_64 with the VectorUDFAdaptor.
        dataTypePhysicalVariations = null;
    }
    VectorizationContext vectorizationContext = new VectorizationContext("name", columns, Arrays.asList(typeInfos), dataTypePhysicalVariations == null ? null : Arrays.asList(dataTypePhysicalVariations), hiveConf);
    final VectorExpressionDescriptor.Mode mode;
    switch(filterCompareTestMode) {
        case ADAPTOR:
        case COMPARE_VECTOR_EXPRESSION:
            mode = VectorExpressionDescriptor.Mode.PROJECTION;
            break;
        case FILTER_VECTOR_EXPRESSION:
            mode = VectorExpressionDescriptor.Mode.FILTER;
            break;
        default:
            throw new RuntimeException("Unexpected filter compare mode " + filterCompareTestMode);
    }
    VectorExpression vectorExpression = vectorizationContext.getVectorExpression(exprDesc, mode);
    vectorExpression.transientInit(hiveConf);
    if (filterCompareTestMode == FilterCompareTestMode.COMPARE_VECTOR_EXPRESSION && vectorExpression instanceof VectorUDFAdaptor) {
        System.out.println("*NO NATIVE VECTOR EXPRESSION* typeInfo1 " + typeInfo1.toString() + " typeInfo2 " + typeInfo2.toString() + " " + comparison + " " + " filterCompareTestMode " + filterCompareTestMode + " columnScalarMode " + columnScalarMode + " vectorExpression " + vectorExpression.toString());
    }
    String[] outputScratchTypeNames = vectorizationContext.getScratchColumnTypeNames();
    DataTypePhysicalVariation[] outputDataTypePhysicalVariations = vectorizationContext.getScratchDataTypePhysicalVariations();
    VectorizedRowBatchCtx batchContext = new VectorizedRowBatchCtx(columnNames, typeInfos, dataTypePhysicalVariations, /* dataColumnNums */
    null, /* partitionColumnCount */
    0, /* virtualColumnCount */
    0, /* neededVirtualColumns */
    null, outputScratchTypeNames, outputDataTypePhysicalVariations);
    VectorizedRowBatch batch = batchContext.createVectorizedRowBatch();
    VectorExtractRow resultVectorExtractRow = new VectorExtractRow();
    final int outputColumnNum = vectorExpression.getOutputColumnNum();
    resultVectorExtractRow.init(new TypeInfo[] { outputTypeInfo }, new int[] { outputColumnNum });
    Object[] scrqtchRow = new Object[1];
    // System.out.println("*VECTOR EXPRESSION* " + vectorExpression.getClass().getSimpleName());
    /*
    System.out.println(
        "*DEBUG* typeInfo1 " + typeInfo1.toString() +
        " typeInfo2 " + typeInfo2.toString() +
        " " + comparison + " " +
        " filterCompareTestMode " + filterCompareTestMode +
        " columnScalarMode " + columnScalarMode +
        " vectorExpression " + vectorExpression.toString());
    */
    final boolean isFilter = (mode == VectorExpressionDescriptor.Mode.FILTER);
    boolean copySelectedInUse = false;
    int[] copySelected = new int[VectorizedRowBatch.DEFAULT_SIZE];
    batchSource.resetBatchIteration();
    int rowIndex = 0;
    while (true) {
        if (!batchSource.fillNextBatch(batch)) {
            break;
        }
        final int originalBatchSize = batch.size;
        if (isFilter) {
            copySelectedInUse = batch.selectedInUse;
            if (batch.selectedInUse) {
                System.arraycopy(batch.selected, 0, copySelected, 0, originalBatchSize);
            }
        }
        // In filter mode, the batch size can be made smaller.
        vectorExpression.evaluate(batch);
        if (!isFilter) {
            extractResultObjects(batch, rowIndex, resultVectorExtractRow, scrqtchRow, objectInspector, resultObjects);
        } else {
            final int currentBatchSize = batch.size;
            if (copySelectedInUse && batch.selectedInUse) {
                int selectIndex = 0;
                for (int i = 0; i < originalBatchSize; i++) {
                    final int originalBatchIndex = copySelected[i];
                    final boolean booleanResult;
                    if (selectIndex < currentBatchSize && batch.selected[selectIndex] == originalBatchIndex) {
                        booleanResult = true;
                        selectIndex++;
                    } else {
                        booleanResult = false;
                    }
                    resultObjects[rowIndex + i] = new BooleanWritable(booleanResult);
                }
            } else if (batch.selectedInUse) {
                int selectIndex = 0;
                for (int i = 0; i < originalBatchSize; i++) {
                    final boolean booleanResult;
                    if (selectIndex < currentBatchSize && batch.selected[selectIndex] == i) {
                        booleanResult = true;
                        selectIndex++;
                    } else {
                        booleanResult = false;
                    }
                    resultObjects[rowIndex + i] = new BooleanWritable(booleanResult);
                }
            } else if (currentBatchSize == 0) {
                // Whole batch got zapped.
                for (int i = 0; i < originalBatchSize; i++) {
                    resultObjects[rowIndex + i] = new BooleanWritable(false);
                }
            } else {
                // Every row kept.
                for (int i = 0; i < originalBatchSize; i++) {
                    resultObjects[rowIndex + i] = new BooleanWritable(true);
                }
            }
        }
        rowIndex += originalBatchSize;
    }
}

Example 15 with VectorExtractRow

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

the class TestVectorCoalesceElt method doVectorCastTest.

private boolean doVectorCastTest(TypeInfo typeInfo, int iteration, List<String> columns, String[] columnNames, TypeInfo[] typeInfos, DataTypePhysicalVariation[] dataTypePhysicalVariations, List<ExprNodeDesc> children, GenericUDF udf, ExprNodeGenericFuncDesc exprDesc, CoalesceEltTestMode coalesceEltTestMode, VectorRandomBatchSource batchSource, ObjectInspector objectInspector, TypeInfo outputTypeInfo, Object[] resultObjects) throws Exception {
    HiveConf hiveConf = new HiveConf();
    if (coalesceEltTestMode == CoalesceEltTestMode.ADAPTOR) {
        hiveConf.setBoolVar(HiveConf.ConfVars.HIVE_TEST_VECTOR_ADAPTOR_OVERRIDE, true);
    }
    VectorizationContext vectorizationContext = new VectorizationContext("name", columns, Arrays.asList(typeInfos), Arrays.asList(dataTypePhysicalVariations), hiveConf);
    VectorExpression vectorExpression = vectorizationContext.getVectorExpression(exprDesc, VectorExpressionDescriptor.Mode.PROJECTION);
    vectorExpression.transientInit(hiveConf);
    if (coalesceEltTestMode == CoalesceEltTestMode.VECTOR_EXPRESSION && vectorExpression instanceof VectorUDFAdaptor) {
        System.out.println("*NO NATIVE VECTOR EXPRESSION* typeInfo " + typeInfo.toString() + " coalesceEltTestMode " + coalesceEltTestMode + " vectorExpression " + vectorExpression.toString());
    }
    // System.out.println("*VECTOR EXPRESSION* " + vectorExpression.getClass().getSimpleName());
    /*
    System.out.println(
        "*DEBUG* typeInfo " + typeInfo.toString() +
        " coalesceEltTestMode " + coalesceEltTestMode +
        " vectorExpression " + vectorExpression.toString());
    */
    VectorRandomRowSource rowSource = batchSource.getRowSource();
    VectorizedRowBatchCtx batchContext = new VectorizedRowBatchCtx(columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), /* dataColumnNums */
    null, /* partitionColumnCount */
    0, /* virtualColumnCount */
    0, /* neededVirtualColumns */
    null, vectorizationContext.getScratchColumnTypeNames(), vectorizationContext.getScratchDataTypePhysicalVariations());
    VectorizedRowBatch batch = batchContext.createVectorizedRowBatch();
    VectorExtractRow resultVectorExtractRow = new VectorExtractRow();
    resultVectorExtractRow.init(new TypeInfo[] { outputTypeInfo }, new int[] { vectorExpression.getOutputColumnNum() });
    Object[] scrqtchRow = new Object[1];
    batchSource.resetBatchIteration();
    int rowIndex = 0;
    while (true) {
        if (!batchSource.fillNextBatch(batch)) {
            break;
        }
        vectorExpression.evaluate(batch);
        extractResultObjects(batch, rowIndex, resultVectorExtractRow, scrqtchRow, objectInspector, resultObjects);
        rowIndex += batch.size;
    }
    return true;
}