use of org.apache.flink.table.planner.plan.nodes.physical.stream.StreamPhysicalPythonGroupWindowAggregate 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);
}
Aggregations