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From fhueske <...@git.apache.org>
Subject [GitHub] flink pull request #4625: [FLINK-6233] [table] Support time-bounded stream i...
Date Tue, 05 Sep 2017 21:50:30 GMT
Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/flink/pull/4625#discussion_r137102330
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/join/TimeBoundedStreamInnerJoin.scala
---
    @@ -0,0 +1,533 @@
    +/*
    + * 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.runtime.join
    +
    +import java.text.SimpleDateFormat
    +import java.util
    +import java.util.Map.Entry
    +import java.util.{Date, List => JList}
    +
    +import org.apache.flink.api.common.functions.FlatJoinFunction
    +import org.apache.flink.api.common.state._
    +import org.apache.flink.api.common.typeinfo.{BasicTypeInfo, TypeInformation}
    +import org.apache.flink.api.java.typeutils.ListTypeInfo
    +import org.apache.flink.configuration.Configuration
    +import org.apache.flink.streaming.api.functions.co.CoProcessFunction
    +import org.apache.flink.table.codegen.Compiler
    +import org.apache.flink.table.runtime.CRowWrappingCollector
    +import org.apache.flink.table.runtime.join.JoinTimeIndicator.JoinTimeIndicator
    +import org.apache.flink.table.runtime.types.CRow
    +import org.apache.flink.table.util.Logging
    +import org.apache.flink.types.Row
    +import org.apache.flink.util.Collector
    +
    +/**
    +  * A CoProcessFunction to execute time-bounded stream inner-join.
    +  *
    +  * Sample criteria:
    +  *
    +  * L.time between R.time + X and R.time + Y
    +  * or AND R.time between L.time - Y and L.time - X
    +  *
    +  * @param leftLowerBound  X
    +  * @param leftUpperBound  Y
    +  * @param allowedLateness the lateness allowed for the two streams
    +  * @param leftType        the input type of left stream
    +  * @param rightType       the input type of right stream
    +  * @param genJoinFuncName the function code of other non-equi conditions
    +  * @param genJoinFuncCode the function name of other non-equi conditions
    +  * @param timeIndicator   indicate whether joining on proctime or rowtime
    +  *
    +  */
    +class TimeBoundedStreamInnerJoin(
    +  private val leftLowerBound: Long,
    +  private val leftUpperBound: Long,
    +  private val allowedLateness: Long,
    +  private val leftType: TypeInformation[Row],
    +  private val rightType: TypeInformation[Row],
    +  private val genJoinFuncName: String,
    +  private val genJoinFuncCode: String,
    +  private val leftTimeIdx: Int,
    +  private val rightTimeIdx: Int,
    +  private val timeIndicator: JoinTimeIndicator)
    +  extends CoProcessFunction[CRow, CRow, CRow]
    +    with Compiler[FlatJoinFunction[Row, Row, Row]]
    +    with Logging {
    +
    +  private var cRowWrapper: CRowWrappingCollector = _
    +
    +  // the join function for other conditions
    +  private var joinFunction: FlatJoinFunction[Row, Row, Row] = _
    +
    +  // cache to store the left stream records
    +  private var leftCache: MapState[Long, JList[Row]] = _
    +  // cache to store right stream records
    +  private var rightCache: MapState[Long, JList[Row]] = _
    +
    +  // state to record the timer on the left stream. 0 means no timer set
    +  private var leftTimerState: ValueState[Long] = _
    +  // state to record the timer on the right stream. 0 means no timer set
    +  private var rightTimerState: ValueState[Long] = _
    +
    +  private val leftRelativeSize: Long = -leftLowerBound
    +  private val rightRelativeSize: Long = leftUpperBound
    +
    +  private val relativeWindowSize = rightRelativeSize + leftRelativeSize
    +
    +  private var leftOperatorTime: Long = 0L
    +  private var rightOperatorTime: Long = 0L
    +
    +  private var backPressureSuggestion: Long = 0L
    +
    +  if (relativeWindowSize <= 0) {
    +    LOG.warn("The relative window size is non-positive, please check the join conditions.")
    +  }
    +
    +  if (allowedLateness < 0) {
    +    throw new IllegalArgumentException("The allowed lateness must be non-negative.")
    +  }
    +
    +
    +  /**
    +    * For holding back watermarks.
    +    *
    +    * @return the maximum delay for the outputs
    +    */
    +  def getMaxOutputDelay = Math.max(leftRelativeSize, rightRelativeSize) + allowedLateness;
    +
    +  /**
    +    * For dynamic query optimization.
    +    *
    +    * @return the suggested offset time for back-pressure
    +    */
    +  def getBackPressureSuggestion = backPressureSuggestion
    +
    +  override def open(config: Configuration) {
    +    val clazz = compile(
    +      getRuntimeContext.getUserCodeClassLoader,
    +      genJoinFuncName,
    +      genJoinFuncCode)
    +    joinFunction = clazz.newInstance()
    +
    +    cRowWrapper = new CRowWrappingCollector()
    +    cRowWrapper.setChange(true)
    +
    +    // Initialize the data caches.
    +    val leftListTypeInfo: TypeInformation[JList[Row]] = new ListTypeInfo[Row](leftType)
    +    val leftStateDescriptor: MapStateDescriptor[Long, JList[Row]] =
    +      new MapStateDescriptor[Long, JList[Row]](timeIndicator + "InnerJoinLeftCache",
    +        BasicTypeInfo.LONG_TYPE_INFO.asInstanceOf[TypeInformation[Long]], leftListTypeInfo)
    +    leftCache = getRuntimeContext.getMapState(leftStateDescriptor)
    +
    +    val rightListTypeInfo: TypeInformation[JList[Row]] = new ListTypeInfo[Row](rightType)
    +    val rightStateDescriptor: MapStateDescriptor[Long, JList[Row]] =
    +      new MapStateDescriptor[Long, JList[Row]](timeIndicator + "InnerJoinRightCache",
    +        BasicTypeInfo.LONG_TYPE_INFO.asInstanceOf[TypeInformation[Long]], rightListTypeInfo)
    +    rightCache = getRuntimeContext.getMapState(rightStateDescriptor)
    +
    +    // Initialize the timer states.
    +    val leftTimerStateDesc: ValueStateDescriptor[Long] =
    +      new ValueStateDescriptor[Long](timeIndicator + "InnerJoinLeftTimerState",
    +        classOf[Long])
    +    leftTimerState = getRuntimeContext.getState(leftTimerStateDesc)
    +
    +    val rightTimerStateDesc: ValueStateDescriptor[Long] =
    +      new ValueStateDescriptor[Long](timeIndicator + "InnerJoinRightTimerState",
    +        classOf[Long])
    +    rightTimerState = getRuntimeContext.getState(rightTimerStateDesc)
    +  }
    +
    +  /**
    +    * Process records from the left stream.
    +    *
    +    * @param cRowValue the input record
    +    * @param ctx       the context to register timer or get current time
    +    * @param out       the collector for outputting results
    +    *
    +    */
    +  override def processElement1(
    +    cRowValue: CRow,
    +    ctx: CoProcessFunction[CRow, CRow, CRow]#Context,
    +    out: Collector[CRow]): Unit = {
    +    val timeForRecord: Long = getTimeForRecord(ctx, cRowValue, true)
    +    getCurrentOperatorTime(ctx)
    +    processElement(
    +      cRowValue,
    +      timeForRecord,
    +      ctx,
    +      out,
    +      leftOperatorTime,
    +      rightOperatorTime,
    +      rightTimerState,
    +      leftCache,
    +      rightCache,
    +      true
    +    )
    +  }
    +
    +  /**
    +    * Process records from the right stream.
    +    *
    +    * @param cRowValue the input record
    +    * @param ctx       the context to get current time
    +    * @param out       the collector for outputting results
    +    *
    +    */
    +  override def processElement2(
    +    cRowValue: CRow,
    +    ctx: CoProcessFunction[CRow, CRow, CRow]#Context,
    +    out: Collector[CRow]): Unit = {
    +    val timeForRecord: Long = getTimeForRecord(ctx, cRowValue, false)
    +    getCurrentOperatorTime(ctx)
    +    processElement(
    +      cRowValue,
    +      timeForRecord,
    +      ctx,
    +      out,
    +      rightOperatorTime,
    +      leftOperatorTime,
    +      leftTimerState,
    +      rightCache,
    +      leftCache,
    +      false
    +    )
    +  }
    +
    +  /**
    +    * Put a record from the input stream into the cache and iterate the opposite cache
to
    +    * output records meeting the join conditions. If there is no timer set for the OPPOSITE
    +    * STREAM, register one.
    +    */
    +  private def processElement(
    +    cRowValue: CRow,
    +    timeForRecord: Long,
    +    ctx: CoProcessFunction[CRow, CRow, CRow]#Context,
    +    out: Collector[CRow],
    +    myWatermark: Long,
    +    oppositeWatermark: Long,
    +    oppositeTimeState: ValueState[Long],
    +    recordListCache: MapState[Long, JList[Row]],
    +    oppositeCache: MapState[Long, JList[Row]],
    +    leftRecord: Boolean): Unit = {
    +    if (relativeWindowSize > 0) {
    +      //TODO Shall we consider adding a method for initialization with the context and
collector?
    +      cRowWrapper.out = out
    +
    +      val record = cRowValue.row
    +
    +      //TODO Only if the time of the record is greater than the watermark, can we continue.
    +      if (timeForRecord >= myWatermark - allowedLateness) {
    --- End diff --
    
    don't we need to check against the other watermark, i.e., whether the other stream has
progressed so much that this record cannot be joined with any record from the other side any
more? 
    
    I think it is not important whether the record is late with respect to other records of
this stream but rather whether there are (or may be) record to be joined with.
    
    If all records to join with are already evicted and none are expected in the future, we
can dismiss this record. Otherwise, we should check the other cache and put it in our cache.


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