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From GitBox <...@apache.org>
Subject [GitHub] pnowojski commented on a change in pull request #6776: [FLINK-9715][table] Support temporal join with event time
Date Tue, 16 Oct 2018 10:03:43 GMT
pnowojski commented on a change in pull request #6776: [FLINK-9715][table] Support temporal
join with event time
URL: https://github.com/apache/flink/pull/6776#discussion_r225475981
 
 

 ##########
 File path: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/join/TemporalRowtimeJoin.scala
 ##########
 @@ -0,0 +1,339 @@
+/*
+ * 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.lang.{Long => JLong}
+import java.util
+import java.util.Comparator
+
+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.runtime.state.{VoidNamespace, VoidNamespaceSerializer}
+import org.apache.flink.streaming.api.SimpleTimerService
+import org.apache.flink.streaming.api.operators._
+import org.apache.flink.streaming.runtime.streamrecord.StreamRecord
+import org.apache.flink.table.api.StreamQueryConfig
+import org.apache.flink.table.codegen.Compiler
+import org.apache.flink.table.runtime.CRowWrappingCollector
+import org.apache.flink.table.runtime.types.CRow
+import org.apache.flink.table.typeutils.TypeCheckUtils._
+import org.apache.flink.table.util.Logging
+import org.apache.flink.types.Row
+import org.apache.flink.util.Preconditions.checkState
+
+import scala.collection.JavaConversions._
+
+/**
+  * This operator works by keeping on the state collection of probe and build records to
process
+  * on next watermark. The idea is that between watermarks we are collecting those elements
+  * and once we are sure that there will be no updates we emit the correct result and clean
up the
+  * state.
+  *
+  * Cleaning up the state drops all of the "old" values from the probe side, where "old"
is defined
+  * as older then the current watermark. Build side is also cleaned up in the similar fashion,
+  * however we always keep at least one record - the latest one - even if it's past the last
+  * watermark.
+  *
+  * One more trick is how the emitting results and cleaning up is triggered. It is achieved
+  * by registering timers for the keys. We could register a timer for every probe and build
+  * side element's event time (when watermark exceeds this timer, that's when we are emitting
and/or
+  * cleaning up the state). However this would cause huge number of registered timers. For
example
+  * with following evenTimes of probe records accumulated: {1, 2, 5, 8, 9}, if we
+  * had received Watermark(10), it would trigger 5 separate timers for the same key. To avoid
that
+  * we always keep only one single registered timer for any given key, registered for the
minimal
+  * value. Upon triggering it, we process all records with event times older then or equal
to
+  * currentWatermark.
+  */
+class TemporalRowtimeJoin(
+    leftType: TypeInformation[Row],
+    rightType: TypeInformation[Row],
+    genJoinFuncName: String,
+    genJoinFuncCode: String,
+    queryConfig: StreamQueryConfig,
+    leftTimeAttribute: Int,
+    rightTimeAttribute: Int)
+  extends AbstractStreamOperator[CRow]
+  with TwoInputStreamOperator[CRow, CRow, CRow]
+  with Triggerable[Any, VoidNamespace]
+  with Compiler[FlatJoinFunction[Row, Row, Row]]
+  with Logging {
+
+  validateEqualsHashCode("join", leftType)
+  validateEqualsHashCode("join", rightType)
+
+  private val NEXT_LEFT_INDEX_STATE_NAME = "next-index"
+  private val LEFT_STATE_NAME = "left"
+  private val RIGHT_STATE_NAME = "right"
+  private val REGISTERED_TIMER_STATE_NAME = "timer"
+  private val TIMERS_STATE_NAME = "timers"
+
+  private val rightRowtimeComparator = new RowtimeComparator(rightTimeAttribute)
+
+  /**
+    * Incremental index generator for `leftState`'s keys.
+    */
+  private var nextLeftIndex: ValueState[JLong] = _
+
+  /**
+    * Mapping from artificial row index (generated by `nextLeftIndex`) into the left side
`Row`.
+    * We can not use List to accumulate Rows, because we need efficient deletes of the oldest
rows.
+    *
+    * TODO: this could be OrderedMultiMap[Jlong, Row] indexed by row's timestamp, to avoid
+    * full map traversals (if we have lots of rows on the state that exceed `currentWatermark`).
+    */
+  private var leftState: MapState[JLong, Row] = _
+
+  /**
+    * Mapping from timestamp to right side `Row`.
+    *
+    * TODO: having `rightState` as an OrderedMapState would allow us to avoid sorting cost
+    * once per watermark
+    */
+  private var rightState: MapState[JLong, Row] = _
+
+  private var registeredTimer: ValueState[JLong] = _ // JLong for correct handling of default
null
+
+  private var cRowWrapper: CRowWrappingCollector = _
+  private var collector: TimestampedCollector[CRow] = _
+  private var timerService: SimpleTimerService = _
+
+  private var joinFunction: FlatJoinFunction[Row, Row, Row] = _
+
+  override def open(): Unit = {
+    val clazz = compile(
+      getRuntimeContext.getUserCodeClassLoader,
+      genJoinFuncName,
+      genJoinFuncCode)
+
+    joinFunction = clazz.newInstance()
+
+    nextLeftIndex = getRuntimeContext.getState(
+      new ValueStateDescriptor[JLong](NEXT_LEFT_INDEX_STATE_NAME, BasicTypeInfo.LONG_TYPE_INFO))
+    leftState = getRuntimeContext.getMapState(
+      new MapStateDescriptor[JLong, Row](LEFT_STATE_NAME, BasicTypeInfo.LONG_TYPE_INFO, leftType))
+    rightState = getRuntimeContext.getMapState(
+      new MapStateDescriptor[JLong, Row](RIGHT_STATE_NAME, BasicTypeInfo.LONG_TYPE_INFO,
rightType))
+    registeredTimer = getRuntimeContext.getState(
+      new ValueStateDescriptor[JLong](REGISTERED_TIMER_STATE_NAME, BasicTypeInfo.LONG_TYPE_INFO))
+
+    collector = new TimestampedCollector[CRow](output)
+    cRowWrapper = new CRowWrappingCollector()
+    cRowWrapper.out = collector
+    cRowWrapper.setChange(true)
+
+    val internalTimerService = getInternalTimerService(
+      TIMERS_STATE_NAME,
+      VoidNamespaceSerializer.INSTANCE,
+      this)
+
+    timerService = new SimpleTimerService(internalTimerService)
+  }
+
+  override def processElement1(element: StreamRecord[CRow]): Unit = {
+    checkState(
+      element.getValue.change,
+      "Retractions are not supported by [{}]. " +
+        "If this can happen it should be validated during planning!",
+      classOf[TemporalRowtimeJoin].getSimpleName)
+
+    leftState.put(getNextLeftIndex, element.getValue.row)
+    registerSmallestTimer(getLeftTime(element.getValue.row)) // Timer to emit and clean up
the state
+  }
+
+  override def processElement2(element: StreamRecord[CRow]): Unit = {
+    checkState(
+      element.getValue.change,
+      "Retractions are not supported by [{}]. " +
+        "If this can happen it should be validated during planning!",
+      classOf[TemporalRowtimeJoin].getSimpleName)
+
+    val rowTime = getRightTime(element.getValue.row)
+    rightState.put(rowTime, element.getValue.row)
+    registerSmallestTimer(rowTime) // Timer to clean up the state
+  }
+
+  private def registerSmallestTimer(timestamp: Long): Unit = {
+    val currentRegisteredTimer = registeredTimer.value()
+    if (currentRegisteredTimer == null) {
+      registerTimer(timestamp)
+    }
+    else if (currentRegisteredTimer != null && currentRegisteredTimer > timestamp)
{
+      timerService.deleteEventTimeTimer(currentRegisteredTimer)
+      registerTimer(timestamp)
+    }
+  }
+
+  private def registerTimer(timestamp: Long): Unit = {
+    registeredTimer.update(timestamp)
+    timerService.registerEventTimeTimer(timestamp)
+  }
+
+  override def onProcessingTime(timer: InternalTimer[Any, VoidNamespace]): Unit = {
+    throw new IllegalStateException("This should never happen")
+  }
+
+  override def onEventTime(timer: InternalTimer[Any, VoidNamespace]): Unit = {
+    registeredTimer.clear()
+    val lastUnprocessedTime = emitResultAndCleanUpState(timerService.currentWatermark())
+    if (lastUnprocessedTime < Long.MaxValue) {
+      registerTimer(lastUnprocessedTime)
+    }
+  }
+
+  /**
+    * @return a row time of the oldest unprocessed probe record or Long.MaxValue, if all
records
+    *         have been processed.
+    */
+  private def emitResultAndCleanUpState(timerTimestamp: Long): Long = {
+    val rightRowsSorted = getRightRowsSorted(rightRowtimeComparator)
+    var lastUnprocessedTime = Long.MaxValue
+
+    val leftIterator = leftState.entries().iterator()
+    while (leftIterator.hasNext) {
+      val leftEntry = leftIterator.next()
+      val leftRow = leftEntry.getValue
+      val leftTime = getLeftTime(leftRow)
+
+      if (leftTime <= timerTimestamp) {
+        val rightRowIndex = latestRightRowToJoin(rightRowsSorted, leftTime)
+
+        if (rightRowIndex >= 0) {
+          val rightRow = rightRowsSorted.get(rightRowIndex)
+
+          joinFunction.join(leftRow, rightRow, cRowWrapper)
+        }
+        leftIterator.remove()
+      }
+      else {
+        lastUnprocessedTime = Math.min(lastUnprocessedTime, leftTime)
+      }
+    }
+
+    cleanUpState(timerTimestamp, rightRowsSorted)
+    lastUnprocessedTime
+  }
+
+  /**
+    * Removes all right entries older then the watermark, except the latest one. For example
with:
+    * rightState = [1, 5, 9]
+    * and
+    * watermark = 6
+    * we can not remove "5" from rightState, because left elements with rowtime of 7 or 8
could
+    * be joined with it later
+    */
+  private def cleanUpState(timerTimestamp: Long, rightRowsSorted: util.List[Row]) = {
+    var i = 0
+    while (i < firstIndexToKeep(timerTimestamp, rightRowsSorted)) {
+      val rightTime = getRightTime(rightRowsSorted.get(i))
+      rightState.remove(rightTime)
+      i += 1
+    }
+  }
+
+  private def firstIndexToKeep(timerTimestamp: Long, rightRowsSorted: util.List[Row]): Int
= {
+    val firstIndexNewerThenTimer =
+      indexOf[Row](rightRowsSorted, row => getRightTime(row) > timerTimestamp)
+
+    if (firstIndexNewerThenTimer < 0) {
+      rightRowsSorted.size() - 1
+    }
+    else {
+      firstIndexNewerThenTimer - 1
+    }
+  }
+
+  private def indexOf[T](list: util.List[T], predicate: T => Boolean): Int = {
+    val iter = list.listIterator
+    while (iter.hasNext) {
+      if (predicate(iter.next)) {
+        return iter.previousIndex
+      }
+    }
+    -1
+  }
+
+  /**
+    * Binary search `rightRowsSorted` to find the latest right row to join with `leftTime`.
+    * Latest means a right row with largest time that is still smaller or equal to `leftTime`.
+    *
+    * @return index of such element. If such row was not found (either `rightRowsSorted`
is empty
+    *         or all `rightRowsSorted` are are newer) return -1.
+    */
+  private def latestRightRowToJoin(rightRowsSorted: util.List[Row], leftTime: Long): Int
= {
+    latestRightRowToJoin(rightRowsSorted, 0, rightRowsSorted.size - 1, leftTime)
+  }
+
+  private def latestRightRowToJoin(
 
 Review comment:
   Yes, good point I will change it.

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