Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/flink/pull/4471#discussion_r132213679
  
    --- Diff: 
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamJoin.scala
 ---
    @@ -0,0 +1,212 @@
    +/*
    + * 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.plan.nodes.datastream
    +
    +import org.apache.calcite.plan._
    +import org.apache.calcite.rel.`type`.RelDataType
    +import org.apache.calcite.rel.core.{JoinInfo, JoinRelType}
    +import org.apache.calcite.rel.{BiRel, RelNode, RelWriter}
    +import org.apache.calcite.rex.RexNode
    +import org.apache.flink.api.common.functions.FlatJoinFunction
    +import org.apache.flink.streaming.api.datastream.DataStream
    +import org.apache.flink.table.api.{StreamQueryConfig, 
StreamTableEnvironment, TableException}
    +import org.apache.flink.table.codegen.FunctionCodeGenerator
    +import org.apache.flink.table.plan.nodes.CommonJoin
    +import org.apache.flink.table.plan.schema.RowSchema
    +import org.apache.flink.table.runtime.FlatJoinRunner
    +import org.apache.flink.table.runtime.join.ProcTimeNonWindowInnerJoin
    +import org.apache.flink.table.runtime.types.{CRow, CRowTypeInfo}
    +import org.apache.flink.types.Row
    +
    +import scala.collection.JavaConversions._
    +import scala.collection.mutable.ArrayBuffer
    +
    +/**
    +  * RelNode for a non-windowed stream join.
    +  */
    +class DataStreamJoin(
    +    cluster: RelOptCluster,
    +    traitSet: RelTraitSet,
    +    leftNode: RelNode,
    +    rightNode: RelNode,
    +    joinCondition: RexNode,
    +    joinInfo: JoinInfo,
    +    joinType: JoinRelType,
    +    leftSchema: RowSchema,
    +    rightSchema: RowSchema,
    +    schema: RowSchema,
    +    ruleDescription: String)
    +  extends BiRel(cluster, traitSet, leftNode, rightNode)
    +          with CommonJoin
    +          with DataStreamRel {
    +
    +  override def deriveRowType(): RelDataType = schema.logicalType
    +
    +  override def needsUpdatesAsRetraction: Boolean = true
    +
    +  override def copy(traitSet: RelTraitSet, inputs: 
java.util.List[RelNode]): RelNode = {
    +    new DataStreamJoin(
    +      cluster,
    +      traitSet,
    +      inputs.get(0),
    +      inputs.get(1),
    +      joinCondition,
    +      joinInfo,
    +      joinType,
    +      leftSchema,
    +      rightSchema,
    +      schema,
    +      ruleDescription)
    +  }
    +
    +  def getJoinInfo: JoinInfo = joinInfo
    +
    +  override def toString: String = {
    +    joinToString(
    +      schema.logicalType,
    +      joinCondition,
    +      joinType,
    +      getExpressionString)
    +  }
    +
    +  override def explainTerms(pw: RelWriter): RelWriter = {
    +    joinExplainTerms(
    +      super.explainTerms(pw),
    +      schema.logicalType,
    +      joinCondition,
    +      joinType,
    +      getExpressionString)
    +  }
    +
    +  override def translateToPlan(
    +      tableEnv: StreamTableEnvironment,
    +      queryConfig: StreamQueryConfig): DataStream[CRow] = {
    +
    +    val config = tableEnv.getConfig
    +    val returnType = schema.physicalTypeInfo
    +    val keyPairs = joinInfo.pairs().toList
    +
    +    // get the equality keys
    +    val leftKeys = ArrayBuffer.empty[Int]
    +    val rightKeys = ArrayBuffer.empty[Int]
    +    if (keyPairs.isEmpty) {
    +      // if no equality keys => not supported
    +      throw TableException(
    +        "Joins should have at least one equality condition.\n" +
    +          s"\tLeft: ${left.toString},\n" +
    +          s"\tRight: ${right.toString},\n" +
    +          s"\tCondition: (${joinConditionToString(schema.logicalType,
    +             joinCondition, getExpressionString)})"
    +      )
    +    }
    +    else {
    +      // at least one equality expression
    +      val leftFields = left.getRowType.getFieldList
    +      val rightFields = right.getRowType.getFieldList
    +
    +      keyPairs.foreach(pair => {
    +        val leftKeyType = 
leftFields.get(pair.source).getType.getSqlTypeName
    +        val rightKeyType = 
rightFields.get(pair.target).getType.getSqlTypeName
    +
    +        // check if keys are compatible
    +        if (leftKeyType == rightKeyType) {
    +          // add key pair
    +          leftKeys.add(pair.source)
    +          rightKeys.add(pair.target)
    +        } else {
    +          throw TableException(
    +            "Equality join predicate on incompatible types.\n" +
    +              s"\tLeft: ${left.toString},\n" +
    +              s"\tRight: ${right.toString},\n" +
    +              s"\tCondition: (${joinConditionToString(schema.logicalType,
    +                joinCondition, getExpressionString)})"
    +          )
    +        }
    +      })
    +    }
    +
    +    val leftDataStream =
    +      left.asInstanceOf[DataStreamRel].translateToPlan(tableEnv, 
queryConfig)
    +    val rightDataStream =
    +      right.asInstanceOf[DataStreamRel].translateToPlan(tableEnv, 
queryConfig)
    +
    +    val (connectOperator, nullCheck) = joinType match {
    +      case JoinRelType.INNER => (leftDataStream.connect(rightDataStream), 
false)
    +      case _ => throw new UnsupportedOperationException(s"An Unsupported 
JoinType [ $joinType ]")
    +    }
    +
    +    if (nullCheck && !config.getNullCheck) {
    +      throw TableException("Null check in TableConfig must be enabled for 
outer joins.")
    +    }
    +
    +
    +    val generator = new FunctionCodeGenerator(
    +      config,
    +      nullCheck,
    +      leftSchema.physicalTypeInfo,
    +      Some(rightSchema.physicalTypeInfo))
    +    val conversion = generator.generateConverterResultExpression(
    +      schema.physicalTypeInfo,
    +      schema.physicalType.getFieldNames)
    +
    +
    +    var body = ""
    +
    +    if (joinInfo.isEqui) {
    +      // only equality condition
    +      body = s"""
    +                |${conversion.code}
    +                
|${generator.collectorTerm}.collect(${conversion.resultTerm});
    +                |""".stripMargin
    +    } else {
    +      val condition = generator.generateExpression(joinCondition)
    +      body = s"""
    +                |${condition.code}
    +                |if (${condition.resultTerm}) {
    +                |  ${conversion.code}
    +                |  
${generator.collectorTerm}.collect(${conversion.resultTerm});
    +                |}
    +                |""".stripMargin
    +    }
    +
    +    val genFunction = generator.generateFunction(
    +      ruleDescription,
    +      classOf[FlatJoinFunction[Row, Row, Row]],
    +      body,
    +      returnType)
    +
    +    val joinFun = new FlatJoinRunner[Row, Row, Row](
    --- End diff --
    
    Do we need to wrap the generated function in a `FlatJoinRunner`? 
    Can't we use the code-gen'd function directly in the 
`ProcTimeNonWindowInnerJoin`?


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