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From rtudoran <...@git.apache.org>
Subject [GitHub] flink pull request #3609: [FLINK-6073] - Support for SQL inner queries for p...
Date Sun, 26 Mar 2017 14:59:15 GMT
Github user rtudoran commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3609#discussion_r108062687
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamJoin.scala
---
    @@ -0,0 +1,241 @@
    +/*
    + * 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.{ RelOptCluster, RelTraitSet }
    +import org.apache.calcite.rel.`type`.RelDataType
    +import org.apache.calcite.rel.core.AggregateCall
    +import org.apache.calcite.rel.{ RelNode, RelWriter, BiRel }
    +import org.apache.flink.api.java.tuple.Tuple
    +import org.apache.flink.streaming.api.datastream.{ AllWindowedStream, DataStream, KeyedStream,
WindowedStream }
    +import org.apache.flink.streaming.api.windowing.assigners._
    +import org.apache.flink.streaming.api.windowing.time.Time
    +import org.apache.flink.streaming.api.windowing.windows.{ Window => DataStreamWindow
}
    +import org.apache.flink.table.api.StreamTableEnvironment
    +import org.apache.flink.table.calcite.FlinkRelBuilder.NamedWindowProperty
    +import org.apache.flink.table.calcite.FlinkTypeFactory
    +import org.apache.flink.table.expressions._
    +import org.apache.flink.table.plan.logical._
    +import org.apache.flink.table.plan.nodes.CommonAggregate
    +import org.apache.flink.table.plan.nodes.datastream.DataStreamAggregate._
    +import org.apache.flink.table.runtime.aggregate.AggregateUtil._
    +import org.apache.flink.table.runtime.aggregate._
    +import org.apache.flink.table.typeutils.TypeCheckUtils.isTimeInterval
    +import org.apache.flink.table.typeutils.{ RowIntervalTypeInfo, TimeIntervalTypeInfo }
    +import org.apache.flink.types.Row
    +import org.apache.calcite.rel.logical.LogicalJoin
    +import org.apache.calcite.rel.core.JoinRelType
    +import org.apache.flink.table.api.TableException
    +import org.apache.flink.api.java.functions.KeySelector
    +import org.apache.flink.api.java.typeutils.RowTypeInfo
    +import org.apache.flink.streaming.api.windowing.triggers.Trigger
    +import org.apache.flink.streaming.api.windowing.windows.GlobalWindow
    +import org.apache.flink.streaming.api.windowing.triggers.Trigger.TriggerContext
    +import org.apache.flink.streaming.api.windowing.triggers.TriggerResult
    +import org.apache.flink.streaming.api.datastream.CoGroupedStreams.TaggedUnion
    +import org.apache.flink.streaming.api.windowing.evictors.Evictor
    +import org.apache.flink.streaming.api.windowing.evictors.Evictor.EvictorContext
    +import java.lang.Iterable
    +import org.apache.flink.streaming.runtime.streamrecord.StreamRecord
    +import org.apache.flink.streaming.runtime.operators.windowing.TimestampedValue
    +import org.apache.flink.api.common.functions.RichFlatJoinFunction
    +import org.apache.flink.configuration.Configuration
    +import org.apache.flink.api.common.state.ValueState
    +import org.apache.flink.api.common.state.ValueStateDescriptor
    +import org.apache.flink.util.Collector
    +
    +class DataStreamJoin(
    +  calc: LogicalJoin,
    +  cluster: RelOptCluster,
    +  traitSet: RelTraitSet,
    +  inputLeft: RelNode,
    +  inputRight: RelNode,
    +  rowType: RelDataType,
    +  description: String)
    +    extends BiRel(cluster, traitSet, inputLeft, inputRight) with DataStreamRel {
    +
    +  override def deriveRowType(): RelDataType = rowType
    +
    +  override def copy(traitSet: RelTraitSet, inputs: java.util.List[RelNode]): RelNode
= {
    +    new DataStreamJoin(
    +      calc,
    +      cluster,
    +      traitSet,
    +      inputs.get(0),
    +      inputs.get(1),
    +      rowType,
    +      description + calc.getId())
    +  }
    +
    +  override def toString: String = {
    +    s"Join(${
    +      if (!calc.getCondition.isAlwaysTrue()) {
    +        s"condition: (${calc.getCondition}), "
    +      } else {
    +        ""
    +      }
    +    }left: ($inputLeft), right($inputRight))"
    +  }
    +
    +  override def explainTerms(pw: RelWriter): RelWriter = {
    +    super.explainTerms(pw)
    +      .itemIf("condition", calc.getCondition, !calc.getCondition.isAlwaysTrue())
    +      .item("join", calc)
    +      .item("left", inputLeft)
    +      .item("right", inputRight)
    +  }
    +
    +  override def translateToPlan(tableEnv: StreamTableEnvironment): DataStream[Row] = {
    +
    +    val inputDSLeft = inputLeft.asInstanceOf[DataStreamRel].translateToPlan(tableEnv)
    +    val inputDSRight = inputRight.asInstanceOf[DataStreamRel].translateToPlan(tableEnv)
    +
    +    //define the setup for various types of joins to be supported
    +    (calc.getCondition.isAlwaysTrue(), calc.getJoinType) match {
    +      case (true, JoinRelType.LEFT) =>
    +        createInnerQueryJoin(inputDSLeft, inputDSRight)
    +      case (_, _) =>
    +        throw new TableException("Table does not support this type of JOIN.")
    +    }
    +
    +    null
    +  }
    +
    +  def createInnerQueryJoin(
    +    inputDSLeft: DataStream[Row], inputDSRight: DataStream[Row]): DataStream[Row] = {
    +
    +    // get the output types
    +    val rowTypeInfo = FlinkTypeFactory.toInternalRowTypeInfo(getRowType).asInstanceOf[RowTypeInfo]
    +
    +    val result = inputDSLeft.join(inputDSRight)
    +      .where(new EmptyKeySelector()).equalTo(new EmptyKeySelector())
    +      .window(GlobalWindows.create())
    +      .trigger(new ProcTimeLeftJoinTrigger())
    +      .evictor(new FullEvictor())
    +      .apply(new JoinProcTimeForInnerQuerry(rowTypeInfo))
    +
    +    null
    --- End diff --
    
    @shijinkui  thanks for the review...it is indeed redundant as i am catching actually all
cases in the match pattern matching. I will remove it


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