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From: fhueske <git@git.apache.org>
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References: <git-pr-4625-flink@git.apache.org>
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Subject: [GitHub] flink pull request #4625: [FLINK-6233] [table] Support time-bounded stream i...
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Message-Id: <20170905215018.78E72F568C@git1-us-west.apache.org>
Date: Tue,  5 Sep 2017 21:50:18 +0000 (UTC)
archived-at: Tue, 05 Sep 2017 21:50:28 -0000

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

    https://github.com/apache/flink/pull/4625#discussion_r137100457
  
    --- 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) {
    +        val oppositeLowerBound: Long =
    +          if (leftRecord) timeForRecord - rightRelativeSize else timeForRecord - leftRelativeSize
    +
    +        val oppositeUpperBound: Long =
    +          if (leftRecord) timeForRecord + leftRelativeSize else timeForRecord + rightRelativeSize
    +
    +        // Put the record into the cache for later use.
    +        val recordList = if (recordListCache.contains(timeForRecord)) {
    --- End diff --
    
    we should directly call `get()` and check for a `null` return value. `contains()` and `get()` would result in two RocksDB accesses of which one can be avoided.


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