Examples with FlinkLogicalWindowAggregate org.apache.flink.table.planner.plan.nodes.logical.FlinkLogicalWindowAggregate used on opensource projects

Example 6 with FlinkLogicalWindowAggregate

use of org.apache.flink.table.planner.plan.nodes.logical.FlinkLogicalWindowAggregate in project flink by apache.

the class BatchPhysicalPythonWindowAggregateRule method onMatch.

@Override
public void onMatch(RelOptRuleCall call) {
    FlinkLogicalWindowAggregate agg = call.rel(0);
    RelNode input = agg.getInput();
    LogicalWindow window = agg.getWindow();
    if (!(window instanceof TumblingGroupWindow && AggregateUtil.hasTimeIntervalType(((TumblingGroupWindow) window).size()) || window instanceof SlidingGroupWindow && AggregateUtil.hasTimeIntervalType(((SlidingGroupWindow) window).size()) || window instanceof SessionGroupWindow)) {
        // sliding & tumbling count window and session window not supported
        throw new TableException("Window " + window + " is not supported right now.");
    }
    int[] groupSet = agg.getGroupSet().toArray();
    RelTraitSet traitSet = agg.getTraitSet().replace(FlinkConventions.BATCH_PHYSICAL());
    Tuple2<int[], Seq<AggregateCall>> auxGroupSetAndCallsTuple = AggregateUtil.checkAndSplitAggCalls(agg);
    int[] auxGroupSet = auxGroupSetAndCallsTuple._1;
    Seq<AggregateCall> aggCallsWithoutAuxGroupCalls = auxGroupSetAndCallsTuple._2;
    Tuple3<int[][], DataType[][], UserDefinedFunction[]> aggBufferTypesAndFunctions = AggregateUtil.transformToBatchAggregateFunctions(FlinkTypeFactory.toLogicalRowType(input.getRowType()), aggCallsWithoutAuxGroupCalls, null);
    UserDefinedFunction[] aggFunctions = aggBufferTypesAndFunctions._3();
    int inputTimeFieldIndex = AggregateUtil.timeFieldIndex(input.getRowType(), call.builder(), window.timeAttribute());
    RelDataType inputTimeFieldType = input.getRowType().getFieldList().get(inputTimeFieldIndex).getType();
    boolean inputTimeIsDate = inputTimeFieldType.getSqlTypeName() == SqlTypeName.DATE;
    RelTraitSet requiredTraitSet = agg.getTraitSet().replace(FlinkConventions.BATCH_PHYSICAL());
    if (groupSet.length != 0) {
        FlinkRelDistribution requiredDistribution = FlinkRelDistribution.hash(groupSet, false);
        requiredTraitSet = requiredTraitSet.replace(requiredDistribution);
    } else {
        requiredTraitSet = requiredTraitSet.replace(FlinkRelDistribution.SINGLETON());
    }
    RelCollation sortCollation = createRelCollation(groupSet, inputTimeFieldIndex);
    requiredTraitSet = requiredTraitSet.replace(sortCollation);
    RelNode newInput = RelOptRule.convert(input, requiredTraitSet);
    BatchPhysicalPythonGroupWindowAggregate windowAgg = new BatchPhysicalPythonGroupWindowAggregate(agg.getCluster(), traitSet, newInput, agg.getRowType(), newInput.getRowType(), groupSet, auxGroupSet, aggCallsWithoutAuxGroupCalls, aggFunctions, window, inputTimeFieldIndex, inputTimeIsDate, agg.getNamedProperties());
    call.transformTo(windowAgg);
}