HuangXingBo commented on a change in pull request #13388: URL: https://github.com/apache/flink/pull/13388#discussion_r490665353
########## File path: flink-table/flink-table-planner-blink/src/main/java/org/apache/flink/table/planner/plan/rules/physical/batch/BatchExecPythonAggregateRule.java ########## @@ -0,0 +1,153 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.flink.table.planner.plan.rules.physical.batch; + +import org.apache.flink.table.api.TableException; +import org.apache.flink.table.functions.ImperativeAggregateFunction; +import org.apache.flink.table.functions.UserDefinedFunction; +import org.apache.flink.table.functions.python.PythonFunction; +import org.apache.flink.table.functions.python.PythonFunctionKind; +import org.apache.flink.table.planner.functions.utils.AggSqlFunction; +import org.apache.flink.table.planner.plan.nodes.FlinkConventions; +import org.apache.flink.table.planner.plan.nodes.logical.FlinkLogicalAggregate; +import org.apache.flink.table.planner.plan.nodes.physical.batch.BatchExecPythonGroupAggregate; +import org.apache.flink.table.planner.plan.trait.FlinkRelDistribution; +import org.apache.flink.table.planner.plan.utils.AggregateUtil; +import org.apache.flink.table.planner.plan.utils.FlinkRelOptUtil; +import org.apache.flink.table.types.DataType; + +import org.apache.calcite.plan.RelOptRule; +import org.apache.calcite.plan.RelOptRuleCall; +import org.apache.calcite.plan.RelTraitSet; +import org.apache.calcite.rel.RelCollation; +import org.apache.calcite.rel.RelCollations; +import org.apache.calcite.rel.RelFieldCollation; +import org.apache.calcite.rel.RelNode; +import org.apache.calcite.rel.convert.ConverterRule; +import org.apache.calcite.rel.core.AggregateCall; +import org.apache.calcite.sql.SqlAggFunction; + +import java.util.LinkedList; +import java.util.List; + +import scala.Tuple2; +import scala.Tuple3; +import scala.collection.Seq; + +/** + * The physical rule is responsible for convert {@link FlinkLogicalAggregate} to + * {@link BatchExecPythonGroupAggregate}. + */ +public class BatchExecPythonAggregateRule extends ConverterRule { + + public static final RelOptRule INSTANCE = new BatchExecPythonAggregateRule(); + + private BatchExecPythonAggregateRule() { + super(FlinkLogicalAggregate.class, FlinkConventions.LOGICAL(), FlinkConventions.BATCH_PHYSICAL(), + "BatchExecPythonAggregateRule"); + } + + @Override + public boolean matches(RelOptRuleCall call) { + FlinkLogicalAggregate agg = call.rel(0); + List<AggregateCall> aggCalls = agg.getAggCallList(); + boolean existPandasFunction = false; + boolean existGeneralPythonFunction = false; + boolean existJavaFunction = false; + for (AggregateCall aggCall : aggCalls) { + SqlAggFunction aggregation = aggCall.getAggregation(); + if (aggregation instanceof AggSqlFunction) { + ImperativeAggregateFunction<?, ?> func = + ((AggSqlFunction) aggregation).aggregateFunction(); + if (func instanceof PythonFunction) { + PythonFunction pythonFunction = (PythonFunction) func; + if (pythonFunction.getPythonFunctionKind() == PythonFunctionKind.PANDAS) { + existPandasFunction = true; + } else { + existGeneralPythonFunction = true; + } + } else { + existJavaFunction = true; + } + } + } + if (existPandasFunction) { + if (existGeneralPythonFunction) { + throw new TableException("Pandas UDAF cannot be computed with General Python UDAF currently"); + } + if (existJavaFunction) { + throw new TableException("Pandas UDAF cannot be computed with Java/Scala UDAF currently"); + } + } + + return existPandasFunction || existGeneralPythonFunction; + } + + @Override + public RelNode convert(RelNode relNode) { + FlinkLogicalAggregate agg = (FlinkLogicalAggregate) relNode; + RelNode input = agg.getInput(); + + int[] groupSet = agg.getGroupSet().toArray(); + RelTraitSet traitSet = relNode.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( + aggCallsWithoutAuxGroupCalls, input.getRowType(), null); Review comment: `transformToBatchAggregateFunctions` is a scala function, we can't take use of default parameter ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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