use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelTraitSet in project flink by apache.
the class StreamPhysicalPythonOverAggregateRule method convert.
@Override
public RelNode convert(RelNode rel) {
FlinkLogicalOverAggregate logicWindow = (FlinkLogicalOverAggregate) rel;
if (logicWindow.groups.size() > 1) {
throw new TableException("Over Agg: Unsupported use of OVER windows. " + "All aggregates must be computed on the same window. " + "please re-check the over window statement.");
}
ImmutableBitSet keys = logicWindow.groups.get(0).keys;
FlinkRelDistribution requiredDistribution;
if (!keys.isEmpty()) {
requiredDistribution = FlinkRelDistribution.hash(keys.asList(), true);
} else {
requiredDistribution = FlinkRelDistribution.SINGLETON();
}
RelNode input = logicWindow.getInput();
RelTraitSet requiredTraitSet = input.getTraitSet().replace(FlinkConventions.STREAM_PHYSICAL()).replace(requiredDistribution);
RelTraitSet providedTraitSet = rel.getTraitSet().replace(FlinkConventions.STREAM_PHYSICAL());
RelNode newInput = RelOptRule.convert(input, requiredTraitSet);
return new StreamPhysicalPythonOverAggregate(rel.getCluster(), providedTraitSet, newInput, rel.getRowType(), logicWindow);
}
use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelTraitSet in project flink by apache.
the class StreamPhysicalPythonGroupAggregateRule method convert.
@Override
public RelNode convert(RelNode rel) {
FlinkLogicalAggregate agg = (FlinkLogicalAggregate) rel;
FlinkRelDistribution requiredDistribution;
if (agg.getGroupCount() != 0) {
requiredDistribution = FlinkRelDistribution.hash(agg.getGroupSet().asList(), true);
} else {
requiredDistribution = FlinkRelDistribution.SINGLETON();
}
RelTraitSet requiredTraitSet = rel.getCluster().getPlanner().emptyTraitSet().replace(requiredDistribution).replace(FlinkConventions.STREAM_PHYSICAL());
RelTraitSet providedTraitSet = rel.getTraitSet().replace(FlinkConventions.STREAM_PHYSICAL());
RelNode newInput = RelOptRule.convert(agg.getInput(), requiredTraitSet);
return new StreamPhysicalPythonGroupAggregate(rel.getCluster(), providedTraitSet, newInput, rel.getRowType(), agg.getGroupSet().toArray(), JavaScalaConversionUtil.toScala(agg.getAggCallList()));
}
use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelTraitSet 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);
}
use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelTraitSet in project flink by apache.
the class TwoStageOptimizedWindowAggregateRule method onMatch.
@Override
public void onMatch(RelOptRuleCall call) {
final StreamPhysicalWindowAggregate windowAgg = call.rel(0);
final RelNode realInput = call.rel(2);
final WindowingStrategy windowing = windowAgg.windowing();
RelTraitSet localTraitSet = realInput.getTraitSet().plus(ModifyKindSetTrait.INSERT_ONLY()).plus(UpdateKindTrait.NONE());
StreamPhysicalLocalWindowAggregate localAgg = new StreamPhysicalLocalWindowAggregate(windowAgg.getCluster(), localTraitSet, realInput, windowAgg.grouping(), windowAgg.aggCalls(), windowing);
// grouping keys is forwarded by local agg, use indices instead of groupings
int[] globalGrouping = IntStream.range(0, windowAgg.grouping().length).toArray();
FlinkRelDistribution globalDistribution = createDistribution(globalGrouping);
// create exchange if needed
RelNode newInput = FlinkExpandConversionRule.satisfyDistribution(FlinkConventions.STREAM_PHYSICAL(), localAgg, globalDistribution);
RelTraitSet globalAggProvidedTraitSet = windowAgg.getTraitSet();
// we put sliceEnd/windowEnd at the end of local output fields
int endIndex = localAgg.getRowType().getFieldCount() - 1;
final WindowingStrategy globalWindowing;
if (windowing instanceof TimeAttributeWindowingStrategy) {
globalWindowing = new SliceAttachedWindowingStrategy(windowing.getWindow(), windowing.getTimeAttributeType(), endIndex);
} else {
globalWindowing = new WindowAttachedWindowingStrategy(windowing.getWindow(), windowing.getTimeAttributeType(), endIndex);
}
StreamPhysicalGlobalWindowAggregate globalAgg = new StreamPhysicalGlobalWindowAggregate(windowAgg.getCluster(), globalAggProvidedTraitSet, newInput, realInput.getRowType(), globalGrouping, windowAgg.aggCalls(), globalWindowing, windowAgg.namedWindowProperties());
call.transformTo(globalAgg);
}
use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.plan.RelTraitSet in project beam by apache.
the class ZetaSQLQueryPlanner method convertToBeamRelInternal.
private BeamRelNode convertToBeamRelInternal(String sql, QueryParameters queryParams) {
RelRoot root = plannerImpl.rel(sql, queryParams);
RelTraitSet desiredTraits = root.rel.getTraitSet().replace(BeamLogicalConvention.INSTANCE).replace(root.collation).simplify();
// beam physical plan
root.rel.getCluster().setMetadataProvider(ChainedRelMetadataProvider.of(org.apache.beam.vendor.calcite.v1_28_0.com.google.common.collect.ImmutableList.of(NonCumulativeCostImpl.SOURCE, RelMdNodeStats.SOURCE, root.rel.getCluster().getMetadataProvider())));
root.rel.getCluster().setMetadataQuerySupplier(BeamRelMetadataQuery::instance);
RelMetadataQuery.THREAD_PROVIDERS.set(JaninoRelMetadataProvider.of(root.rel.getCluster().getMetadataProvider()));
root.rel.getCluster().invalidateMetadataQuery();
try {
BeamRelNode beamRelNode = (BeamRelNode) plannerImpl.transform(0, desiredTraits, root.rel);
LOG.info("BEAMPlan>\n" + RelOptUtil.toString(beamRelNode));
return beamRelNode;
} catch (RelOptPlanner.CannotPlanException e) {
throw new SqlConversionException("Failed to produce plan for query " + sql, e);
}
}
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