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Subject [GitHub] pnowojski commented on a change in pull request #6776: [FLINK-9715][table] Support temporal join with event time
Date Tue, 02 Oct 2018 15:41:03 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_r221638717
 
 

 ##########
 File path: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/join/TemporalRowtimeJoin.scala
 ##########
 @@ -0,0 +1,307 @@
+/*
+ * 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, TableException}
+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 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 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 netLeftIndexStateName = "next-index"
+  private val leftStateName = "left"
+  private val rightStateName = "right"
+  private val registeredTimerStateName = "timer"
+  private val probteTimersStateName = "probe-timers"
+
+  private val rightRowtimeComparator = new RowtimeComparator(rightTimeAttribute)
+
+  /**
+    * Incremental index generator for `leftState`'s keys.
+    */
+  private var nextLeftIndex: ValueState[JLong] = _
+
+  /**
+    * This could have been a MultiMap indexed by rowtime, but we have to handle rows with
+    * duplicated rowtimes. We can not use List, 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] = _
+
+  /**
+    * 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](netLeftIndexStateName, BasicTypeInfo.LONG_TYPE_INFO))
+    leftState = getRuntimeContext.getMapState(
+      new MapStateDescriptor[JLong, Row](leftStateName, BasicTypeInfo.LONG_TYPE_INFO, leftType))
+    rightState = getRuntimeContext.getMapState(
+      new MapStateDescriptor[JLong, Row](rightStateName, BasicTypeInfo.LONG_TYPE_INFO, rightType))
+    registeredTimer = getRuntimeContext.getState(
+      new ValueStateDescriptor[JLong](registeredTimerStateName, BasicTypeInfo.LONG_TYPE_INFO))
+
+    collector = new TimestampedCollector[CRow](output)
+    cRowWrapper = new CRowWrappingCollector()
+    cRowWrapper.out = collector
+
+    val internalTimerService = getInternalTimerService(
+      probteTimersStateName,
+      VoidNamespaceSerializer.INSTANCE,
+      this)
+
+    timerService = new SimpleTimerService(internalTimerService)
+  }
+
+  override def processElement1(element: StreamRecord[CRow]): Unit = {
+    if (!element.getValue.change) {
+      throw new TableException(
+        s"${classOf[TemporalRowtimeJoin].getSimpleName} does not support retractions on the
" +
+          s"left side.")
+    }
+
+    leftState.put(getNextLeftIndex, element.getValue.row)
+    maybeRegisterTimer(getLeftTime(element.getValue.row)) // Timer to emit and clean up the
state
+  }
+
+  override def processElement2(element: StreamRecord[CRow]): Unit = {
+    if (!element.getValue.change) {
+      throw new TableException(
+        s"${classOf[TemporalRowtimeJoin].getSimpleName} does not support retractions on the"
+
+          s"right side.")
+    }
+
+    val rowTime = getRightTime(element.getValue.row)
+    rightState.put(rowTime, element.getValue.row)
+    maybeRegisterTimer(rowTime) // Timer to clean up the state
+  }
+
+  private def maybeRegisterTimer(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())
+    lastUnprocessedTime.foreach(registerTimer)
 
 Review comment:
   Dropped as you suggest in favour of `Long.MAX_VALUE`.

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