Examples with DoubleLiteral io.prestosql.sql.tree.DoubleLiteral used on opensource projects

Example 11 with DoubleLiteral

use of io.prestosql.sql.tree.DoubleLiteral in project hetu-core by openlookeng.

the class TestComparisonStatsCalculator method symbolToLiteralEqualStats.

@Test
public void symbolToLiteralEqualStats() {
    // Simple case
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("y"), new DoubleLiteral("2.5"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    25.0).symbolStats("y", symbolAssert -> {
        symbolAssert.averageRowSize(4.0).distinctValuesCount(1.0).lowValue(2.5).highValue(2.5).nullsFraction(0.0);
    });
    // Literal on the edge of symbol range
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("x"), new DoubleLiteral("10.0"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    18.75).symbolStats("x", symbolAssert -> {
        symbolAssert.averageRowSize(4.0).distinctValuesCount(1.0).lowValue(10.0).highValue(10.0).nullsFraction(0.0);
    });
    // Literal out of symbol range
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("y"), new DoubleLiteral("10.0"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    0.0).symbolStats("y", symbolAssert -> {
        symbolAssert.averageRowSize(0.0).distinctValuesCount(0.0).emptyRange().nullsFraction(1.0);
    });
    // Literal in left open range
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("leftOpen"), new DoubleLiteral("2.5"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    18.0).symbolStats("leftOpen", symbolAssert -> {
        symbolAssert.averageRowSize(4.0).distinctValuesCount(1.0).lowValue(2.5).highValue(2.5).nullsFraction(0.0);
    });
    // Literal in right open range
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("rightOpen"), new DoubleLiteral("-2.5"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    18.0).symbolStats("rightOpen", symbolAssert -> {
        symbolAssert.averageRowSize(4.0).distinctValuesCount(1.0).lowValue(-2.5).highValue(-2.5).nullsFraction(0.0);
    });
    // Literal in unknown range
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("unknownRange"), new DoubleLiteral("0.0"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    18.0).symbolStats("unknownRange", symbolAssert -> {
        symbolAssert.averageRowSize(4.0).distinctValuesCount(1.0).lowValue(0.0).highValue(0.0).nullsFraction(0.0);
    });
    // Literal in empty range
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("emptyRange"), new DoubleLiteral("0.0"))).outputRowsCount(0.0).symbolStats("emptyRange", equalTo(emptyRangeStats));
    // Column with values not representable as double (unknown range)
    assertCalculate(new ComparisonExpression(EQUAL, new SymbolReference("varchar"), new StringLiteral("blah"))).outputRowsCount(// all rows minus nulls divided by distinct values count
    18.0).symbolStats("varchar", symbolAssert -> {
        symbolAssert.averageRowSize(4.0).distinctValuesCount(1.0).lowValue(NEGATIVE_INFINITY).highValue(POSITIVE_INFINITY).nullsFraction(0.0);
    });
}

Example 12 with DoubleLiteral

use of io.prestosql.sql.tree.DoubleLiteral in project hetu-core by openlookeng.

the class TestStarTreeAggregationRule method testBuildSymbolMappings.

@Test
public void testBuildSymbolMappings() {
    RowExpression rowExpression = planBuilder.variable(columnTotalprice.getName(), totalpriceHandle.getType());
    FilterNode filterNode = new FilterNode(newId(), baseTableScan, rowExpression);
    Assignments projectionAssignments = Assignments.builder().put(columnCustkey, planBuilder.variable(columnCustkey.getName(), custkeyHandle.getType())).build();
    ProjectNode projectNode1 = new ProjectNode(newId(), filterNode, projectionAssignments);
    List<ProjectNode> projectNodes = ImmutableList.of(projectNode1);
    AggregationNode countAggNode = new AggregationNode(newId(), projectNode1, ImmutableMap.of(columnCustkey, new AggregationNode.Aggregation(Expressions.call("count", COUNT, DOUBLE, ImmutableList.of(planBuilder.variable(columnOrderkey.getName(), orderkeyHandle.getType()))), ImmutableList.of(planBuilder.variable(columnCustkey.getName(), custkeyHandle.getType())), true, Optional.empty(), Optional.empty(), Optional.empty())), singleGroupingSet(ImmutableList.of(columnOrderkey, columnOrderDate)), ImmutableList.of(), SINGLE, Optional.empty(), Optional.empty(), AggregationNode.AggregationType.HASH, Optional.empty());
    Map<String, Object> columnMapping = CubeOptimizerUtil.buildSymbolMappings(countAggNode, projectNodes, Optional.of(filterNode), baseTableScan, baseTableMetadata);
    assertEquals(columnMapping.size(), 4);
    assertEquals(new ArrayList<>(columnMapping.keySet()).toString(), "[orderkey, custkey, totalprice, orderdate]");
    assertTrue(columnMapping.values().containsAll(assignments.values()) && assignments.values().containsAll(columnMapping.values()));
    // expression Literal
    DoubleLiteral testDouble = new DoubleLiteral("1.0");
    Assignments assignment2 = Assignments.builder().put(columnCustkey, OriginalExpressionUtils.castToRowExpression(testDouble)).build();
    ProjectNode projectNode2 = new ProjectNode(newId(), filterNode, assignment2);
    List<ProjectNode> projections2 = ImmutableList.of(projectNode2);
    columnMapping = CubeOptimizerUtil.buildSymbolMappings(countAggNode, projections2, Optional.of(filterNode), baseTableScan, baseTableMetadata);
    assertEquals(new ArrayList(columnMapping.values()).get(1), testDouble);
    // expression Cast/SymbolReference
    Cast testCast = new Cast(SymbolUtils.toSymbolReference(columnCustkey), StandardTypes.INTEGER);
    Assignments assignment3 = Assignments.builder().put(columnCustkey, OriginalExpressionUtils.castToRowExpression(testCast)).build();
    ProjectNode planNode3 = new ProjectNode(newId(), baseTableScan, assignment3);
    List<ProjectNode> projections3 = ImmutableList.of(planNode3);
    columnMapping = CubeOptimizerUtil.buildSymbolMappings(countAggNode, projections3, Optional.of(filterNode), baseTableScan, baseTableMetadata);
    assertEquals(new ArrayList(columnMapping.values()).get(1), custkeyHandle);
    // expression Cast/Literal
    Cast testCast2 = new Cast(testDouble, StandardTypes.DOUBLE);
    Assignments assignment4 = Assignments.builder().put(columnCustkey, OriginalExpressionUtils.castToRowExpression(testCast2)).build();
    ProjectNode planNode4 = new ProjectNode(newId(), baseTableScan, assignment4);
    List<ProjectNode> projections4 = ImmutableList.of(planNode4);
    columnMapping = CubeOptimizerUtil.buildSymbolMappings(countAggNode, projections4, Optional.of(filterNode), baseTableScan, baseTableMetadata);
    assertEquals(new ArrayList(columnMapping.values()).get(1), testDouble);
}

Example 13 with DoubleLiteral

use of io.prestosql.sql.tree.DoubleLiteral in project hetu-core by openlookeng.

the class CubeConsole method isSupportedExpression.

/**
 * Gets whether the expression is supported for processing the create cube query
 *
 * @param createCube createCube
 * @return void
 */
private boolean isSupportedExpression(CreateCube createCube, QueryRunner queryRunner, ClientOptions.OutputFormat outputFormat, Runnable schemaChanged, boolean usePager, boolean showProgress, Terminal terminal, PrintStream out, PrintStream errorChannel) {
    boolean supportedExpression = false;
    boolean success = true;
    Optional<Expression> expression = createCube.getWhere();
    if (expression.isPresent()) {
        ImmutableSet.Builder<Identifier> identifierBuilder = new ImmutableSet.Builder<>();
        new DefaultExpressionTraversalVisitor<Void, ImmutableSet.Builder<Identifier>>() {

            @Override
            protected Void visitIdentifier(Identifier node, ImmutableSet.Builder<Identifier> builder) {
                builder.add(node);
                return null;
            }
        }.process(expression.get(), identifierBuilder);
        int sizeIdentifiers = identifierBuilder.build().asList().size();
        if (sizeIdentifiers == SUPPORTED_INDENTIFIER_SIZE) {
            String whereClause = createCube.getWhere().get().toString();
            QualifiedName sourceTableName = createCube.getSourceTableName();
            if (expression.get() instanceof BetweenPredicate) {
                BetweenPredicate betweenPredicate = (BetweenPredicate) (expression.get());
                String columnName = betweenPredicate.getValue().toString();
                String columnDataTypeQuery;
                String catalogName;
                String tableName = sourceTableName.getSuffix();
                checkArgument(tableName.matches("[\\p{Alnum}_]+"), "Invalid table name");
                if (hasInvalidSymbol(columnName)) {
                    return false;
                }
                if (sourceTableName.getPrefix().isPresent() && sourceTableName.getPrefix().get().getPrefix().isPresent()) {
                    catalogName = sourceTableName.getPrefix().get().getPrefix().get().toString();
                    checkArgument(catalogName.matches("[\\p{Alnum}_]+"), "Invalid catalog name");
                    columnDataTypeQuery = String.format(SELECT_DATA_TYPE_STRING, catalogName, tableName, columnName);
                } else if (queryRunner.getSession().getCatalog() != null) {
                    catalogName = queryRunner.getSession().getCatalog();
                    checkArgument(catalogName.matches("[\\p{Alnum}_]+"), "Invalid catalog name");
                    columnDataTypeQuery = String.format(SELECT_DATA_TYPE_STRING, catalogName, tableName, columnName);
                } else {
                    return false;
                }
                if (!processCubeInitialQuery(queryRunner, columnDataTypeQuery, outputFormat, schemaChanged, usePager, showProgress, terminal, out, errorChannel)) {
                    return false;
                }
                String resInitCubeQuery;
                resInitCubeQuery = getResultInitCubeQuery();
                if (resInitCubeQuery != null) {
                    cubeColumnDataType = resInitCubeQuery;
                }
                if (cubeColumnDataType.contains(DATATYPE_DECIMAL)) {
                    cubeColumnDataType = DATATYPE_DECIMAL;
                }
                if (cubeColumnDataType.contains(DATATYPE_VARCHAR)) {
                    cubeColumnDataType = DATATYPE_VARCHAR;
                }
                if (!isSupportedDatatype(cubeColumnDataType)) {
                    return false;
                }
                if (betweenPredicate.getMin() instanceof LongLiteral || betweenPredicate.getMin() instanceof LongLiteral || betweenPredicate.getMin() instanceof TimestampLiteral || betweenPredicate.getMin() instanceof TimestampLiteral || betweenPredicate.getMin() instanceof GenericLiteral || betweenPredicate.getMin() instanceof StringLiteral || betweenPredicate.getMin() instanceof DoubleLiteral) {
                    if (betweenPredicate.getMax() instanceof LongLiteral || betweenPredicate.getMax() instanceof LongLiteral || betweenPredicate.getMax() instanceof TimestampLiteral || betweenPredicate.getMax() instanceof TimestampLiteral || betweenPredicate.getMax() instanceof GenericLiteral || betweenPredicate.getMax() instanceof StringLiteral || betweenPredicate.getMax() instanceof DoubleLiteral) {
                        // initial query to get the total number of distinct column values in the table
                        String countDistinctQuery = String.format(SELECT_COUNT_DISTINCT_FROM_STRING, columnName, sourceTableName.toString(), whereClause);
                        if (!processCubeInitialQuery(queryRunner, countDistinctQuery, outputFormat, schemaChanged, usePager, showProgress, terminal, out, errorChannel)) {
                            return false;
                        }
                        Long valueCountDistinctQuery = INITIAL_QUERY_RESULT_VALUE;
                        resInitCubeQuery = getResultInitCubeQuery();
                        if (resInitCubeQuery != null) {
                            valueCountDistinctQuery = Long.parseLong(resInitCubeQuery);
                        }
                        if (valueCountDistinctQuery < MAX_BUFFERED_ROWS && valueCountDistinctQuery * rowBufferTempMultiplier < Integer.MAX_VALUE) {
                            supportedExpression = true;
                            rowBufferListSize = (int) ((valueCountDistinctQuery).intValue() * rowBufferTempMultiplier);
                        }
                    }
                }
            }
            if (expression.get() instanceof ComparisonExpression) {
                ComparisonExpression comparisonExpression = (ComparisonExpression) (createCube.getWhere().get());
                ComparisonExpression.Operator operator = comparisonExpression.getOperator();
                Expression left = comparisonExpression.getLeft();
                Expression right = comparisonExpression.getRight();
                if (!(left instanceof SymbolReference) && right instanceof SymbolReference) {
                    comparisonExpression = new ComparisonExpression(operator.flip(), right, left);
                }
                if (left instanceof Literal && !(right instanceof Literal)) {
                    comparisonExpression = new ComparisonExpression(operator.flip(), right, left);
                }
                if (comparisonExpression.getRight() instanceof LongLiteral) {
                    supportedExpression = true;
                }
                String catalogName;
                String tableName = sourceTableName.getSuffix();
                String columnName = comparisonExpression.getLeft().toString();
                String columnDataTypeQuery;
                checkArgument(tableName.matches("[\\p{Alnum}_]+"), "Invalid table name");
                if (hasInvalidSymbol(columnName)) {
                    return false;
                }
                if (sourceTableName.getPrefix().isPresent() && sourceTableName.getPrefix().get().getPrefix().isPresent()) {
                    catalogName = sourceTableName.getPrefix().get().getPrefix().get().toString();
                    checkArgument(catalogName.matches("[\\p{Alnum}_]+"), "Invalid catalog name");
                    columnDataTypeQuery = String.format(SELECT_DATA_TYPE_STRING, catalogName, tableName, columnName);
                } else if (queryRunner.getSession().getCatalog() != null) {
                    catalogName = queryRunner.getSession().getCatalog();
                    checkArgument(catalogName.matches("[\\p{Alnum}_]+"), "Invalid catalog name");
                    columnDataTypeQuery = String.format(SELECT_DATA_TYPE_STRING, catalogName, tableName, columnName);
                } else {
                    return false;
                }
                if (!processCubeInitialQuery(queryRunner, columnDataTypeQuery, outputFormat, schemaChanged, usePager, showProgress, terminal, out, errorChannel)) {
                    return false;
                }
                String resInitCubeQuery;
                resInitCubeQuery = getResultInitCubeQuery();
                if (resInitCubeQuery != null) {
                    cubeColumnDataType = resInitCubeQuery.toLowerCase(Locale.ENGLISH);
                }
                if (cubeColumnDataType.contains(DATATYPE_DECIMAL)) {
                    cubeColumnDataType = DATATYPE_DECIMAL;
                }
                if (cubeColumnDataType.contains(DATATYPE_VARCHAR)) {
                    cubeColumnDataType = DATATYPE_VARCHAR;
                }
                if (!isSupportedDatatype(cubeColumnDataType)) {
                    return false;
                }
                if (comparisonExpression.getRight() instanceof GenericLiteral || comparisonExpression.getRight() instanceof StringLiteral || comparisonExpression.getRight() instanceof DoubleLiteral || comparisonExpression.getRight() instanceof LongLiteral || comparisonExpression.getRight() instanceof TimestampLiteral) {
                    // initial query to get the total number of distinct column values in the table
                    String countDistinctQuery = String.format(SELECT_COUNT_DISTINCT_FROM_STRING, columnName, sourceTableName.toString(), whereClause);
                    if (!processCubeInitialQuery(queryRunner, countDistinctQuery, outputFormat, schemaChanged, usePager, showProgress, terminal, out, errorChannel)) {
                        return false;
                    }
                    Long valueCountDistinctQuery = INITIAL_QUERY_RESULT_VALUE;
                    resInitCubeQuery = getResultInitCubeQuery();
                    if (resInitCubeQuery != null) {
                        valueCountDistinctQuery = Long.parseLong(resInitCubeQuery);
                    }
                    if (valueCountDistinctQuery < MAX_BUFFERED_ROWS) {
                        supportedExpression = true;
                    }
                }
            }
        }
    }
    return supportedExpression;
}