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

Example 21 with VectorExtractRow

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

the class MapJoinTestData method driveBigTableData.

public static void driveBigTableData(MapJoinTestDescription testDesc, MapJoinTestData testData, MapJoinOperator operator) throws HiveException {
    VectorExtractRow vectorExtractRow = new VectorExtractRow();
    vectorExtractRow.init(testDesc.bigTableTypeInfos);
    Object[][] bigTableRandomRows = testData.bigTableRandomRows;
    final int rowCount = bigTableRandomRows.length;
    for (int i = 0; i < rowCount; i++) {
        Object[] row = bigTableRandomRows[i];
        operator.process(row, 0);
    }
    // Close the operator tree.
    operator.close(false);
}

Example 22 with VectorExtractRow

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

the class TestVectorNegative method doVectorArithmeticTest.

private void doVectorArithmeticTest(TypeInfo typeInfo, List<String> columns, String[] columnNames, TypeInfo[] typeInfos, DataTypePhysicalVariation[] dataTypePhysicalVariations, List<ExprNodeDesc> children, ExprNodeGenericFuncDesc exprDesc, NegativeTestMode negativeTestMode, VectorRandomBatchSource batchSource, ObjectInspector objectInspector, TypeInfo outputTypeInfo, Object[] resultObjects) throws Exception {
    HiveConf hiveConf = new HiveConf();
    if (negativeTestMode == NegativeTestMode.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);
    vectorExpression.transientInit(hiveConf);
    if (negativeTestMode == NegativeTestMode.VECTOR_EXPRESSION && vectorExpression instanceof VectorUDFAdaptor) {
        System.out.println("*NO NATIVE VECTOR EXPRESSION* typeInfo " + typeInfo.toString() + " negativeTestMode " + negativeTestMode + " vectorExpression " + vectorExpression.toString());
    }
    String[] outputScratchTypeNames = vectorizationContext.getScratchColumnTypeNames();
    VectorizedRowBatchCtx batchContext = new VectorizedRowBatchCtx(columnNames, typeInfos, dataTypePhysicalVariations, /* dataColumnNums */
    null, /* partitionColumnCount */
    0, /* virtualColumnCount */
    0, /* neededVirtualColumns */
    null, outputScratchTypeNames, null);
    VectorizedRowBatch batch = batchContext.createVectorizedRowBatch();
    VectorExtractRow resultVectorExtractRow = new VectorExtractRow();
    resultVectorExtractRow.init(new TypeInfo[] { outputTypeInfo }, new int[] { vectorExpression.getOutputColumnNum() });
    Object[] scrqtchRow = new Object[1];
    // System.out.println("*VECTOR EXPRESSION* " + vectorExpression.getClass().getSimpleName());
    /*
    System.out.println(
        "*DEBUG* typeInfo " + typeInfo.toString() +
        " negativeTestMode " + negativeTestMode +
        " vectorExpression " + vectorExpression.toString());
    */
    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;
    }
}

Example 23 with VectorExtractRow

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

the class VectorBatchGenerateUtil method generateRowObjectArray.

public static Object[][] generateRowObjectArray(TypeInfo[] typeInfos, VectorBatchGenerateStream batchStream, VectorizedRowBatch batch, ObjectInspector[] objectInspectors) throws HiveException {
    VectorExtractRow vectorExtractRow = new VectorExtractRow();
    vectorExtractRow.init(typeInfos);
    final int rowCount = batchStream.getRowCount();
    final int columnCount = typeInfos.length;
    Object[][] rowObjectArray = new Object[rowCount][];
    Object[] row = new Object[columnCount];
    int index = 0;
    batchStream.reset();
    while (batchStream.isNext()) {
        batch.reset();
        batchStream.fillNext(batch);
        // Extract rows and call process per row
        final int size = batch.size;
        for (int r = 0; r < size; r++) {
            vectorExtractRow.extractRow(batch, r, row);
            Object[] resultObjectArray = new Object[columnCount];
            for (int c = 0; c < columnCount; c++) {
                resultObjectArray[c] = ((PrimitiveObjectInspector) objectInspectors[c]).copyObject(row[c]);
            }
            rowObjectArray[index++] = resultObjectArray;
        }
    }
    return rowObjectArray;
}