Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/2811#discussion_r89482516
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/plan/nodes/dataset/DataSetSingleRowCross.scala
---
@@ -0,0 +1,180 @@
+/*
+ * 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.api.table.plan.nodes.dataset
+
+import org.apache.calcite.plan._
+import org.apache.calcite.rel.`type`.RelDataType
+import org.apache.calcite.rel.metadata.RelMetadataQuery
+import org.apache.calcite.rel.{BiRel, RelNode, RelWriter}
+import org.apache.flink.api.common.functions.{MapFunction, RichMapFunction}
+import org.apache.flink.api.common.typeinfo.TypeInformation
+import org.apache.flink.api.java.DataSet
+import org.apache.flink.api.table.codegen.CodeGenerator
+import org.apache.flink.api.table.runtime.RichMapRunner
+import
org.apache.flink.api.table.typeutils.TypeConverter.determineReturnType
+import org.apache.flink.api.table.{BatchTableEnvironment, TableConfig}
+
+import scala.collection.JavaConversions._
+import scala.collection.JavaConverters._
+
+/**
+ * Flink RelNode which matches along with CrossOperator.
+ */
+class DataSetSingleRowCross(
+ cluster: RelOptCluster,
+ traitSet: RelTraitSet,
+ leftNode: RelNode,
+ rightNode: RelNode,
+ leftIsSingle: Boolean,
+ rowRelDataType: RelDataType,
+ joinRowType: RelDataType,
+ ruleDescription: String)
+ extends BiRel(cluster, traitSet, leftNode, rightNode)
+ with DataSetRel {
+
+ override def deriveRowType() = rowRelDataType
+
+ override def copy(traitSet: RelTraitSet, inputs:
java.util.List[RelNode]): RelNode = {
+ new DataSetSingleRowCross(
+ cluster,
+ traitSet,
+ inputs.get(0),
+ inputs.get(1),
+ leftIsSingle,
+ getRowType,
+ joinRowType,
+ ruleDescription)
+ }
+
+ override def toString: String = {
+ s"$joinTypeToString(where: ($joinConditionToString), join:
($joinSelectionToString))"
+ }
+
+ override def explainTerms(pw: RelWriter): RelWriter = {
+ super.explainTerms(pw)
+ .item("where", joinConditionToString)
+ .item("join", joinSelectionToString)
+ .item("joinType", joinTypeToString)
+ }
+
+ override def computeSelfCost (planner: RelOptPlanner, metadata:
RelMetadataQuery): RelOptCost = {
+ val children = this.getInputs
+ children.foldLeft(planner.getCostFactory.makeZeroCost()) { (cost,
child) =>
+ val rowCnt = metadata.getRowCount(child)
+ val rowSize = this.estimateRowSize(child.getRowType)
+ cost.plus(planner.getCostFactory.makeCost(rowCnt, rowCnt, rowCnt *
rowSize))
+ }
+ }
+
+ override def translateToPlan(
+ tableEnv: BatchTableEnvironment,
+ expectedType: Option[TypeInformation[Any]]): DataSet[Any] = {
+
+ val leftDataSet =
left.asInstanceOf[DataSetRel].translateToPlan(tableEnv)
+ val rightDataSet =
right.asInstanceOf[DataSetRel].translateToPlan(tableEnv)
+ val broadcastSetName = "joinSet"
+ val mapSideJoin = generateMapFunction(
+ tableEnv.getConfig,
+ leftDataSet.getType,
+ rightDataSet.getType,
+ leftIsSingle,
+ broadcastSetName,
+ expectedType)
+
+ val (multiRowDataSet, singleRowDataSet) =
+ if (leftIsSingle) {
+ (rightDataSet, leftDataSet)
+ } else {
+ (leftDataSet, rightDataSet)
+ }
+
+ multiRowDataSet
+ .map(mapSideJoin)
+ .withBroadcastSet(singleRowDataSet, broadcastSetName)
+ .name(getMapOperatorName)
+ .asInstanceOf[DataSet[Any]]
+ }
+
+ private def generateMapFunction(
--- End diff --
Actually, I think it is easier and requires less additional code to
generate a regular `JoinFunction` as done in the `DataSetJoin` and call it from
the wrapping `RichMapFunction` with the input value from `map()` and the
broadcasted value.
With this we can move the broadcast and `RichFunction` logic completely to
the wrapper and do not need any changes to the code generation.
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