Examples with GenericUDFOPEqualOrGreaterThan org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan used on opensource projects

Example 16 with GenericUDFOPEqualOrGreaterThan

use of org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan in project hive by apache.

the class TestAccumuloRangeGenerator method testRangeDisjunction.

@Test
public void testRangeDisjunction() throws Exception {
    // rowId >= 'f'
    ExprNodeDesc column = new ExprNodeColumnDesc(TypeInfoFactory.stringTypeInfo, "rid", null, false);
    ExprNodeDesc constant = new ExprNodeConstantDesc(TypeInfoFactory.stringTypeInfo, "f");
    List<ExprNodeDesc> children = Lists.newArrayList();
    children.add(column);
    children.add(constant);
    ExprNodeDesc node = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPEqualOrGreaterThan(), children);
    assertNotNull(node);
    // rowId <= 'm'
    ExprNodeDesc column2 = new ExprNodeColumnDesc(TypeInfoFactory.stringTypeInfo, "rid", null, false);
    ExprNodeDesc constant2 = new ExprNodeConstantDesc(TypeInfoFactory.stringTypeInfo, "m");
    List<ExprNodeDesc> children2 = Lists.newArrayList();
    children2.add(column2);
    children2.add(constant2);
    ExprNodeDesc node2 = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPEqualOrLessThan(), children2);
    assertNotNull(node2);
    // Or UDF
    List<ExprNodeDesc> bothFilters = Lists.newArrayList();
    bothFilters.add(node);
    bothFilters.add(node2);
    ExprNodeGenericFuncDesc both = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPOr(), bothFilters);
    // Should generate (-inf,+inf)
    List<Range> expectedRanges = Arrays.asList(new Range());
    AccumuloRangeGenerator rangeGenerator = new AccumuloRangeGenerator(conf, handler, rowIdMapping, "rid");
    SemanticDispatcher disp = new DefaultRuleDispatcher(rangeGenerator, Collections.<SemanticRule, SemanticNodeProcessor>emptyMap(), null);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.add(both);
    HashMap<Node, Object> nodeOutput = new HashMap<Node, Object>();
    try {
        ogw.startWalking(topNodes, nodeOutput);
    } catch (SemanticException ex) {
        throw new RuntimeException(ex);
    }
    Object result = nodeOutput.get(both);
    Assert.assertNotNull(result);
    Assert.assertTrue("Result from graph walk was not a List", result instanceof List);
    @SuppressWarnings("unchecked") List<Range> actualRanges = (List<Range>) result;
    Assert.assertEquals(expectedRanges, actualRanges);
}

Example 17 with GenericUDFOPEqualOrGreaterThan

use of org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan in project hive by apache.

the class TestAccumuloRangeGenerator method testRangeOverStringIndexedField.

@Test
public void testRangeOverStringIndexedField() throws Exception {
    // age >= '10'
    ExprNodeDesc column = new ExprNodeColumnDesc(TypeInfoFactory.stringTypeInfo, "age", null, false);
    ExprNodeDesc constant = new ExprNodeConstantDesc(TypeInfoFactory.stringTypeInfo, "10");
    List<ExprNodeDesc> children = Lists.newArrayList();
    children.add(column);
    children.add(constant);
    ExprNodeDesc node = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPEqualOrGreaterThan(), children);
    assertNotNull(node);
    // age <= '50'
    ExprNodeDesc column2 = new ExprNodeColumnDesc(TypeInfoFactory.stringTypeInfo, "age", null, false);
    ExprNodeDesc constant2 = new ExprNodeConstantDesc(TypeInfoFactory.stringTypeInfo, "50");
    List<ExprNodeDesc> children2 = Lists.newArrayList();
    children2.add(column2);
    children2.add(constant2);
    ExprNodeDesc node2 = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPEqualOrLessThan(), children2);
    assertNotNull(node2);
    // And UDF
    List<ExprNodeDesc> bothFilters = Lists.newArrayList();
    bothFilters.add(node);
    bothFilters.add(node2);
    ExprNodeGenericFuncDesc both = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPAnd(), bothFilters);
    AccumuloRangeGenerator rangeGenerator = new AccumuloRangeGenerator(conf, handler, rowIdMapping, "rid");
    rangeGenerator.setIndexScanner(TestAccumuloDefaultIndexScanner.buildMockHandler(10));
    SemanticDispatcher disp = new DefaultRuleDispatcher(rangeGenerator, Collections.<SemanticRule, SemanticNodeProcessor>emptyMap(), null);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.add(both);
    HashMap<Node, Object> nodeOutput = new HashMap<Node, Object>();
    try {
        ogw.startWalking(topNodes, nodeOutput);
    } catch (SemanticException ex) {
        throw new RuntimeException(ex);
    }
    // Filters are using an index which should match 3 rows
    Object result = nodeOutput.get(both);
    if (result instanceof List) {
        List results = (List) result;
        Assert.assertEquals(3, results.size());
        Assert.assertTrue("does not contain row1", results.contains(new Range("row1")));
        Assert.assertTrue("does not contain row2", results.contains(new Range("row2")));
        Assert.assertTrue("does not contain row3", results.contains(new Range("row3")));
    } else {
        Assert.fail("Results not a list");
    }
}

Example 18 with GenericUDFOPEqualOrGreaterThan

use of org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan in project hive by apache.

the class TestAccumuloPredicateHandler method testMultipleRanges.

@Test
public void testMultipleRanges() throws SerDeException {
    ExprNodeDesc column = new ExprNodeColumnDesc(TypeInfoFactory.stringTypeInfo, "rid", null, false);
    ExprNodeDesc constant = new ExprNodeConstantDesc(TypeInfoFactory.stringTypeInfo, "aaa");
    List<ExprNodeDesc> children = Lists.newArrayList();
    children.add(column);
    children.add(constant);
    ExprNodeDesc node = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPEqualOrGreaterThan(), children);
    assertNotNull(node);
    ExprNodeDesc column2 = new ExprNodeColumnDesc(TypeInfoFactory.stringTypeInfo, "rid", null, false);
    ExprNodeDesc constant2 = new ExprNodeConstantDesc(TypeInfoFactory.stringTypeInfo, "bbb");
    List<ExprNodeDesc> children2 = Lists.newArrayList();
    children2.add(column2);
    children2.add(constant2);
    ExprNodeDesc node2 = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPLessThan(), children2);
    assertNotNull(node2);
    List<ExprNodeDesc> bothFilters = Lists.newArrayList();
    bothFilters.add(node);
    bothFilters.add(node2);
    ExprNodeGenericFuncDesc both = new ExprNodeGenericFuncDesc(TypeInfoFactory.stringTypeInfo, new GenericUDFOPAnd(), bothFilters);
    String filterExpr = SerializationUtilities.serializeExpression(both);
    conf.set(TableScanDesc.FILTER_EXPR_CONF_STR, filterExpr);
    List<Range> ranges = handler.getRanges(conf, columnMapper);
    assertEquals(1, ranges.size());
    Range range = ranges.get(0);
    assertEquals(new Range(new Key("aaa"), true, new Key("bbb"), false), range);
}

Example 19 with GenericUDFOPEqualOrGreaterThan

use of org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan in project hive by apache.

the class TestKuduPredicateHandler method testOrPredicates.

@Test
public void testOrPredicates() throws Exception {
    for (ColumnSchema col : SCHEMA.getColumns()) {
        // Skip binary columns because binary predicates are not supported. (HIVE-11370)
        if (col.getName().equals("null") || col.getName().equals("default") || col.getName().equals("binary")) {
            continue;
        }
        PrimitiveTypeInfo typeInfo = toHiveType(col.getType(), col.getTypeAttributes());
        ExprNodeDesc colExpr = new ExprNodeColumnDesc(typeInfo, col.getName(), null, false);
        ExprNodeDesc constExpr = new ExprNodeConstantDesc(typeInfo, ROW.getObject(col.getName()));
        List<ExprNodeDesc> children = Lists.newArrayList();
        children.add(colExpr);
        children.add(constExpr);
        ExprNodeGenericFuncDesc gePredicateExpr = new ExprNodeGenericFuncDesc(typeInfo, new GenericUDFOPEqualOrGreaterThan(), children);
        ExprNodeGenericFuncDesc lePredicateExpr = new ExprNodeGenericFuncDesc(typeInfo, new GenericUDFOPEqualOrLessThan(), children);
        List<ExprNodeDesc> orChildren = Lists.newArrayList();
        orChildren.add(gePredicateExpr);
        orChildren.add(lePredicateExpr);
        ExprNodeGenericFuncDesc predicateExpr = new ExprNodeGenericFuncDesc(typeInfo, new GenericUDFOPOr(), orChildren);
        // Verify KuduPredicateHandler.decompose
        HiveStoragePredicateHandler.DecomposedPredicate decompose = KuduPredicateHandler.decompose(predicateExpr, SCHEMA);
        // OR predicates are currently not supported.
        assertNull(decompose);
        List<KuduPredicate> predicates = expressionToPredicates(predicateExpr);
        assertEquals(0, predicates.size());
        // Also test NOT OR.
        List<ExprNodeDesc> notChildren = Lists.newArrayList();
        notChildren.add(predicateExpr);
        ExprNodeGenericFuncDesc notPredicateExpr = new ExprNodeGenericFuncDesc(typeInfo, new GenericUDFOPNot(), notChildren);
        // Verify KuduPredicateHandler.decompose
        HiveStoragePredicateHandler.DecomposedPredicate decomposeNot = KuduPredicateHandler.decompose(notPredicateExpr, SCHEMA);
        // See note in KuduPredicateHandler.newAnalyzer.
        assertNull(decomposeNot);
        List<KuduPredicate> notPredicates = expressionToPredicates(notPredicateExpr);
        assertEquals(2, notPredicates.size());
    }
}

Example 20 with GenericUDFOPEqualOrGreaterThan

use of org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqualOrGreaterThan in project hive by apache.

the class TestVectorFilterCompare method doTestsWithDiffColumnScalar.

private void doTestsWithDiffColumnScalar(Random random, TypeInfo typeInfo1, TypeInfo typeInfo2, ColumnScalarMode columnScalarMode, Comparison comparison, boolean tryDecimal64) throws Exception {
    String typeName1 = typeInfo1.getTypeName();
    PrimitiveCategory primitiveCategory1 = ((PrimitiveTypeInfo) typeInfo1).getPrimitiveCategory();
    String typeName2 = typeInfo2.getTypeName();
    PrimitiveCategory primitiveCategory2 = ((PrimitiveTypeInfo) typeInfo2).getPrimitiveCategory();
    List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
    List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
    List<String> columns = new ArrayList<String>();
    int columnNum = 1;
    ExprNodeDesc col1Expr;
    Object scalar1Object = null;
    final boolean decimal64Enable1 = checkDecimal64(tryDecimal64, typeInfo1);
    if (columnScalarMode == ColumnScalarMode.COLUMN_COLUMN || columnScalarMode == ColumnScalarMode.COLUMN_SCALAR) {
        generationSpecList.add(GenerationSpec.createSameType(typeInfo1));
        explicitDataTypePhysicalVariationList.add(decimal64Enable1 ? DataTypePhysicalVariation.DECIMAL_64 : DataTypePhysicalVariation.NONE);
        String columnName = "col" + (columnNum++);
        col1Expr = new ExprNodeColumnDesc(typeInfo1, columnName, "table", false);
        columns.add(columnName);
    } else {
        scalar1Object = VectorRandomRowSource.randomPrimitiveObject(random, (PrimitiveTypeInfo) typeInfo1);
        // Adjust the decimal type to the scalar's type...
        if (typeInfo1 instanceof DecimalTypeInfo) {
            typeInfo1 = getDecimalScalarTypeInfo(scalar1Object);
        }
        col1Expr = new ExprNodeConstantDesc(typeInfo1, scalar1Object);
    }
    ExprNodeDesc col2Expr;
    Object scalar2Object = null;
    final boolean decimal64Enable2 = checkDecimal64(tryDecimal64, typeInfo2);
    if (columnScalarMode == ColumnScalarMode.COLUMN_COLUMN || columnScalarMode == ColumnScalarMode.SCALAR_COLUMN) {
        generationSpecList.add(GenerationSpec.createSameType(typeInfo2));
        explicitDataTypePhysicalVariationList.add(decimal64Enable2 ? DataTypePhysicalVariation.DECIMAL_64 : DataTypePhysicalVariation.NONE);
        String columnName = "col" + (columnNum++);
        col2Expr = new ExprNodeColumnDesc(typeInfo2, columnName, "table", false);
        columns.add(columnName);
    } else {
        scalar2Object = VectorRandomRowSource.randomPrimitiveObject(random, (PrimitiveTypeInfo) typeInfo2);
        // Adjust the decimal type to the scalar's type...
        if (typeInfo2 instanceof DecimalTypeInfo) {
            typeInfo2 = getDecimalScalarTypeInfo(scalar2Object);
        }
        col2Expr = new ExprNodeConstantDesc(typeInfo2, scalar2Object);
    }
    List<ObjectInspector> objectInspectorList = new ArrayList<ObjectInspector>();
    objectInspectorList.add(VectorRandomRowSource.getObjectInspector(typeInfo1));
    objectInspectorList.add(VectorRandomRowSource.getObjectInspector(typeInfo2));
    List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
    children.add(col1Expr);
    children.add(col2Expr);
    // ----------------------------------------------------------------------------------------------
    String[] columnNames = columns.toArray(new String[0]);
    VectorRandomRowSource rowSource = new VectorRandomRowSource();
    rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
    0, /* allowNull */
    true, /* isUnicodeOk */
    true, explicitDataTypePhysicalVariationList);
    Object[][] randomRows = rowSource.randomRows(100000);
    VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
    GenericUDF genericUdf;
    switch(comparison) {
        case EQUALS:
            genericUdf = new GenericUDFOPEqual();
            break;
        case LESS_THAN:
            genericUdf = new GenericUDFOPLessThan();
            break;
        case LESS_THAN_EQUAL:
            genericUdf = new GenericUDFOPEqualOrLessThan();
            break;
        case GREATER_THAN:
            genericUdf = new GenericUDFOPGreaterThan();
            break;
        case GREATER_THAN_EQUAL:
            genericUdf = new GenericUDFOPEqualOrGreaterThan();
            break;
        case NOT_EQUALS:
            genericUdf = new GenericUDFOPNotEqual();
            break;
        default:
            throw new RuntimeException("Unexpected arithmetic " + comparison);
    }
    ObjectInspector[] objectInspectors = objectInspectorList.toArray(new ObjectInspector[objectInspectorList.size()]);
    ObjectInspector outputObjectInspector = null;
    try {
        outputObjectInspector = genericUdf.initialize(objectInspectors);
    } catch (Exception e) {
        Assert.fail(e.toString());
    }
    TypeInfo outputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(outputObjectInspector);
    ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(outputTypeInfo, genericUdf, children);
    final int rowCount = randomRows.length;
    Object[][] resultObjectsArray = new Object[FilterCompareTestMode.count][];
    for (int i = 0; i < FilterCompareTestMode.count; i++) {
        Object[] resultObjects = new Object[rowCount];
        resultObjectsArray[i] = resultObjects;
        FilterCompareTestMode filterCompareTestMode = FilterCompareTestMode.values()[i];
        switch(filterCompareTestMode) {
            case ROW_MODE:
                doRowFilterCompareTest(typeInfo1, typeInfo2, columns, children, exprDesc, comparison, randomRows, columnScalarMode, rowSource.rowStructObjectInspector(), outputTypeInfo, resultObjects);
                break;
            case ADAPTOR:
            case FILTER_VECTOR_EXPRESSION:
            case COMPARE_VECTOR_EXPRESSION:
                doVectorFilterCompareTest(typeInfo1, typeInfo2, columns, columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), children, exprDesc, comparison, filterCompareTestMode, columnScalarMode, batchSource, exprDesc.getWritableObjectInspector(), outputTypeInfo, resultObjects);
                break;
            default:
                throw new RuntimeException("Unexpected IF statement test mode " + filterCompareTestMode);
        }
    }
    for (int i = 0; i < rowCount; i++) {
        // Row-mode is the expected value.
        Object expectedResult = resultObjectsArray[0][i];
        for (int v = 1; v < FilterCompareTestMode.count; v++) {
            FilterCompareTestMode filterCompareTestMode = FilterCompareTestMode.values()[v];
            Object vectorResult = resultObjectsArray[v][i];
            if (filterCompareTestMode == FilterCompareTestMode.FILTER_VECTOR_EXPRESSION && expectedResult == null && vectorResult != null) {
                // This is OK.
                boolean vectorBoolean = ((BooleanWritable) vectorResult).get();
                if (vectorBoolean) {
                    Assert.fail("Row " + i + " typeName1 " + typeName1 + " typeName2 " + typeName2 + " outputTypeName " + outputTypeInfo.getTypeName() + " " + comparison + " " + filterCompareTestMode + " " + columnScalarMode + " result is NOT NULL and true" + " does not match row-mode expected result is NULL which means false here" + (columnScalarMode == ColumnScalarMode.SCALAR_COLUMN ? " scalar1 " + scalar1Object.toString() : "") + " row values " + Arrays.toString(randomRows[i]) + (columnScalarMode == ColumnScalarMode.COLUMN_SCALAR ? " scalar2 " + scalar2Object.toString() : ""));
                }
            } else if (expectedResult == null || vectorResult == null) {
                if (expectedResult != null || vectorResult != null) {
                    Assert.fail("Row " + i + " typeName1 " + typeName1 + " typeName2 " + typeName2 + " outputTypeName " + outputTypeInfo.getTypeName() + " " + comparison + " " + filterCompareTestMode + " " + columnScalarMode + " result is NULL " + (vectorResult == null) + " does not match row-mode expected result is NULL " + (expectedResult == null) + (columnScalarMode == ColumnScalarMode.SCALAR_COLUMN ? " scalar1 " + scalar1Object.toString() : "") + " row values " + Arrays.toString(randomRows[i]) + (columnScalarMode == ColumnScalarMode.COLUMN_SCALAR ? " scalar2 " + scalar2Object.toString() : ""));
                }
            } else {
                if (!expectedResult.equals(vectorResult)) {
                    Assert.fail("Row " + i + " typeName1 " + typeName1 + " typeName2 " + typeName2 + " outputTypeName " + outputTypeInfo.getTypeName() + " " + comparison + " " + filterCompareTestMode + " " + columnScalarMode + " result " + vectorResult.toString() + " (" + vectorResult.getClass().getSimpleName() + ")" + " does not match row-mode expected result " + expectedResult.toString() + " (" + expectedResult.getClass().getSimpleName() + ")" + (columnScalarMode == ColumnScalarMode.SCALAR_COLUMN ? " scalar1 " + scalar1Object.toString() : "") + " row values " + Arrays.toString(randomRows[i]) + (columnScalarMode == ColumnScalarMode.COLUMN_SCALAR ? " scalar2 " + scalar2Object.toString() : ""));
                }
            }
        }
    }
}