Examples with RelOptCluster org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelOptCluster used on opensource projects

Example 41 with RelOptCluster

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelOptCluster in project flink by apache.

the class LogicalDistribution method create.

public static LogicalDistribution create(RelNode input, RelCollation collation, List<Integer> distKeys) {
    RelOptCluster cluster = input.getCluster();
    collation = RelCollationTraitDef.INSTANCE.canonize(collation);
    RelTraitSet traitSet = input.getTraitSet().replace(Convention.NONE).replace(collation);
    return new LogicalDistribution(cluster, traitSet, input, collation, distKeys);
}

Example 42 with RelOptCluster

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelOptCluster in project flink by apache.

the class SubQueryDecorrelator method decorrelateQuery.

/**
 * Decorrelates a subquery.
 *
 * <p>This is the main entry point to {@code SubQueryDecorrelator}.
 *
 * @param rootRel The node which has SubQuery.
 * @return Decorrelate result.
 */
public static Result decorrelateQuery(RelNode rootRel) {
    int maxCnfNodeCount = FlinkRelOptUtil.getMaxCnfNodeCount(rootRel);
    final CorelMapBuilder builder = new CorelMapBuilder(maxCnfNodeCount);
    final CorelMap corelMap = builder.build(rootRel);
    if (builder.hasNestedCorScope || builder.hasUnsupportedCorCondition) {
        return null;
    }
    if (!corelMap.hasCorrelation()) {
        return Result.EMPTY;
    }
    RelOptCluster cluster = rootRel.getCluster();
    RelBuilder relBuilder = new FlinkRelBuilder(cluster.getPlanner().getContext(), cluster, null);
    RexBuilder rexBuilder = cluster.getRexBuilder();
    final SubQueryDecorrelator decorrelator = new SubQueryDecorrelator(new SubQueryRelDecorrelator(corelMap, relBuilder, rexBuilder, maxCnfNodeCount), relBuilder);
    rootRel.accept(decorrelator);
    return new Result(decorrelator.subQueryMap);
}

Example 43 with RelOptCluster

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelOptCluster in project flink by apache.

the class StreamPhysicalPythonGroupWindowAggregateRule method convert.

@Override
public RelNode convert(RelNode rel) {
    FlinkLogicalWindowAggregate agg = (FlinkLogicalWindowAggregate) rel;
    LogicalWindow window = agg.getWindow();
    List<AggregateCall> aggCalls = agg.getAggCallList();
    boolean isPandasPythonUDAF = aggCalls.stream().anyMatch(x -> PythonUtil.isPythonAggregate(x, PythonFunctionKind.PANDAS));
    if (isPandasPythonUDAF && window instanceof SessionGroupWindow) {
        throw new TableException("Session Group Window is currently not supported for Pandas UDAF.");
    }
    RelNode input = agg.getInput();
    RelOptCluster cluster = rel.getCluster();
    FlinkRelDistribution requiredDistribution;
    if (agg.getGroupCount() != 0) {
        requiredDistribution = FlinkRelDistribution.hash(agg.getGroupSet().asList(), true);
    } else {
        requiredDistribution = FlinkRelDistribution.SINGLETON();
    }
    RelTraitSet requiredTraitSet = input.getTraitSet().replace(FlinkConventions.STREAM_PHYSICAL()).replace(requiredDistribution);
    RelTraitSet providedTraitSet = rel.getTraitSet().replace(FlinkConventions.STREAM_PHYSICAL());
    RelNode newInput = RelOptRule.convert(input, requiredTraitSet);
    ReadableConfig config = ShortcutUtils.unwrapTableConfig(rel);
    WindowEmitStrategy emitStrategy = WindowEmitStrategy.apply(config, agg.getWindow());
    if (emitStrategy.produceUpdates()) {
        throw new TableException("Python Group Window Aggregate Function is currently not supported for early fired or lately fired.");
    }
    return new StreamPhysicalPythonGroupWindowAggregate(cluster, providedTraitSet, newInput, rel.getRowType(), agg.getGroupSet().toArray(), JavaScalaConversionUtil.toScala(aggCalls), agg.getWindow(), agg.getNamedProperties(), emitStrategy);
}

Example 44 with RelOptCluster

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelOptCluster in project flink by apache.

the class ProjectWindowTableFunctionTransposeRule method createNewTableFunctionScan.

private LogicalTableFunctionScan createNewTableFunctionScan(RelBuilder relBuilder, LogicalTableFunctionScan oldScan, LogicalType timeAttributeType, RelNode newInput, Map<Integer, Integer> mapping) {
    relBuilder.push(newInput);
    RexNode newCall = rewriteWindowCall((RexCall) oldScan.getCall(), mapping, relBuilder);
    RelOptCluster cluster = oldScan.getCluster();
    FlinkTypeFactory typeFactory = (FlinkTypeFactory) cluster.getTypeFactory();
    RelDataType newScanOutputType = SqlWindowTableFunction.inferRowType(typeFactory, newInput.getRowType(), typeFactory.createFieldTypeFromLogicalType(timeAttributeType));
    return LogicalTableFunctionScan.create(cluster, new ArrayList<>(Collections.singleton(newInput)), newCall, oldScan.getElementType(), newScanOutputType, oldScan.getColumnMappings());
}

Example 45 with RelOptCluster

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelOptCluster in project beam by apache.

the class RelConverter method createOneRow.

// This function creates a single dummy input row for queries that don't read from a table.
// For example: SELECT "hello"
// The code is copy-pasted from Calcite's LogicalValues.createOneRow() with a single line
// change: SqlTypeName.INTEGER replaced by SqlTypeName.BIGINT.
// Would like to call LogicalValues.createOneRow() directly, but it uses type SqlTypeName.INTEGER
// which corresponds to TypeKind.TYPE_INT32 in ZetaSQL, a type not supported in ZetaSQL
// PRODUCT_EXTERNAL mode. See
// https://github.com/google/zetasql/blob/c610a21ffdc110293c1c7bd255a2674ebc7ec7a8/java/com/google/zetasql/TypeFactory.java#L61
static LogicalValues createOneRow(RelOptCluster cluster) {
    final RelDataType rowType = cluster.getTypeFactory().builder().add("ZERO", SqlTypeName.BIGINT).nullable(false).build();
    final ImmutableList<ImmutableList<RexLiteral>> tuples = ImmutableList.of(ImmutableList.of(cluster.getRexBuilder().makeExactLiteral(BigDecimal.ZERO, rowType.getFieldList().get(0).getType())));
    return LogicalValues.create(cluster, rowType, tuples);
}