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https://issues.apache.org/jira/browse/FLINK-6233?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16194692#comment-16194692
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ASF GitHub Bot commented on FLINK-6233:
---------------------------------------
Github user xccui commented on a diff in the pull request:
https://github.com/apache/flink/pull/4625#discussion_r143211000
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/join/TimeBoundedStreamInnerJoin.scala
---
@@ -0,0 +1,410 @@
+/*
+ * 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.util.{ArrayList, List => JList}
+
+import org.apache.flink.api.common.functions.FlatJoinFunction
+import org.apache.flink.api.common.state._
+import org.apache.flink.api.common.typeinfo.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.api.Types
+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.util.Logging
+import org.apache.flink.types.Row
+import org.apache.flink.util.Collector
+
+/**
+ * A CoProcessFunction to execute time-bounded stream inner-join.
+ * Two kinds of time criteria:
+ * "L.time between R.time + X and R.time + Y" or "R.time between L.time -
Y and L.time - X".
+ *
+ * @param leftLowerBound the lower bound for the left stream (X in the
criteria)
+ * @param leftUpperBound the upper bound for the left stream (Y in the
criteria)
+ * @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
+ *
+ */
+abstract 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)
+ 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 rows from the left stream
+ private var leftCache: MapState[Long, JList[Row]] = _
+ // cache to store rows from the right stream
+ 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 var leftExpirationTime: Long = 0L;
+ private var rightExpirationTime: Long = 0L;
+
+ protected var leftOperatorTime: Long = 0L
+ protected var rightOperatorTime: Long = 0L
+
+
+ // for delayed cleanup
+ private val cleanupDelay = (leftRelativeSize + rightRelativeSize) / 2
+
+ if (allowedLateness < 0) {
+ throw new IllegalArgumentException("The allowed lateness must be
non-negative.")
+ }
+
+ /**
+ * Get the maximum interval between receiving a row and emitting it (as
part of a joined result).
+ * Only reasonable for row time join.
+ *
+ * @return the maximum delay for the outputs
+ */
+ def getMaxOutputDelay: Long = Math.max(leftRelativeSize,
rightRelativeSize) + allowedLateness
+
+ override def open(config: Configuration) {
+ LOG.debug(s"Compiling JoinFunction: $genJoinFuncName \n\n " +
+ s"Code:\n$genJoinFuncCode")
+ val clazz = compile(
+ getRuntimeContext.getUserCodeClassLoader,
+ genJoinFuncName,
+ genJoinFuncCode)
+ LOG.debug("Instantiating JoinFunction.")
+ 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]](
+ "InnerJoinLeftCache",
+ Types.LONG.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]](
+ "InnerJoinRightCache",
+ Types.LONG.asInstanceOf[TypeInformation[Long]],
+ rightListTypeInfo)
+ rightCache = getRuntimeContext.getMapState(rightStateDescriptor)
+
+ // Initialize the timer states.
+ val leftTimerStateDesc: ValueStateDescriptor[Long] =
+ new ValueStateDescriptor[Long]("InnerJoinLeftTimerState",
classOf[Long])
+ leftTimerState = getRuntimeContext.getState(leftTimerStateDesc)
+
+ val rightTimerStateDesc: ValueStateDescriptor[Long] =
+ new ValueStateDescriptor[Long]("InnerJoinRightTimerState",
classOf[Long])
+ rightTimerState = getRuntimeContext.getState(rightTimerStateDesc)
+ }
+
+ /**
+ * Process rows from the left stream.
+ */
+ override def processElement1(
+ cRowValue: CRow,
+ ctx: CoProcessFunction[CRow, CRow, CRow]#Context,
+ out: Collector[CRow]): Unit = {
+ updateOperatorTime(ctx)
+ val leftRow = cRowValue.row
+ val timeForLeftRow: Long = getTimeForLeftStream(ctx, leftRow)
+ val rightQualifiedLowerBound: Long = timeForLeftRow - rightRelativeSize
+ val rightQualifiedUpperBound: Long = timeForLeftRow + leftRelativeSize
+ cRowWrapper.out = out
+
+ if (rightOperatorTime < rightQualifiedUpperBound) {
+ // Put the leftRow into the cache for later use.
+ var leftRowList = leftCache.get(timeForLeftRow)
+ if (null == leftRowList) {
+ leftRowList = new ArrayList[Row](1)
+ }
+ leftRowList.add(leftRow)
+ leftCache.put(timeForLeftRow, leftRowList)
+ if (rightTimerState.value == 0) {
+ // Register a timer on the RIGHT stream to remove rows.
+ registerCleanUpTimer(ctx, timeForLeftRow, rightTimerState, leftRow
= true)
+ }
+ }
+ // We'd like to produce as many results as possible.
+ if (rightExpirationTime < rightQualifiedUpperBound) {
+ rightExpirationTime = calExpirationTime(leftOperatorTime,
rightRelativeSize)
+ // Join the leftRow with rows from the right cache.
+ val rightIterator = rightCache.iterator()
+ while (rightIterator.hasNext) {
+ val rightEntry = rightIterator.next
+ val rightTime = rightEntry.getKey
+ if (rightTime >= rightQualifiedLowerBound && rightTime <=
rightQualifiedUpperBound) {
+ val rightRows = rightEntry.getValue
+ var i = 0
+ while (i < rightRows.size) {
+ joinFunction.join(leftRow, rightRows.get(i), cRowWrapper)
+ i += 1
+ }
+ }
+
+ if (rightTime <= rightExpirationTime) {
+ // eager remove
+ rightIterator.remove()
+ }// We could do the short-cutting optimization here once we get a
state with ordered keys.
+ }
+ }
+ }
+
+ /**
+ * Process rows from the right stream.
+ */
+ override def processElement2(
+ cRowValue: CRow,
+ ctx: CoProcessFunction[CRow, CRow, CRow]#Context,
+ out: Collector[CRow]): Unit = {
+ updateOperatorTime(ctx)
+ val rightRow = cRowValue.row
+ val timeForRightRow: Long = getTimeForRightStream(ctx, rightRow)
+ val leftQualifiedLowerBound: Long = timeForRightRow - leftRelativeSize
+ val leftQualifiedUpperBound: Long = timeForRightRow +
rightRelativeSize
+ cRowWrapper.out = out
+
+ if (leftOperatorTime < leftQualifiedUpperBound) {
+ // Put the rightRow into the cache for later use.
+ var rightRowList = rightCache.get(timeForRightRow)
+ if (null == rightRowList) {
+ rightRowList = new ArrayList[Row](1)
+ }
+ rightRowList.add(rightRow)
+ rightCache.put(timeForRightRow, rightRowList)
+ if (leftTimerState.value == 0) {
+ // Register a timer on the LEFT stream to remove rows.
+ registerCleanUpTimer(ctx, timeForRightRow, leftTimerState, leftRow
= false)
+ }
+ }
+ // We'd like to produce as many results as possible.
+ if (leftExpirationTime < leftQualifiedUpperBound) {
+ leftExpirationTime = calExpirationTime(rightOperatorTime,
leftRelativeSize)
+ // Join the rightRow with rows from the left cache.
+ val leftIterator = leftCache.iterator()
+ while (leftIterator.hasNext) {
+ val leftEntry = leftIterator.next
+ val leftTime = leftEntry.getKey
+ if (leftTime >= leftQualifiedLowerBound && leftTime <=
leftQualifiedUpperBound) {
+ val leftRows = leftEntry.getValue
+ var i = 0
+ while (i < leftRows.size) {
+ joinFunction.join(leftRows.get(i), rightRow, cRowWrapper)
+ i += 1
+ }
+ }
+ if (leftTime <= leftExpirationTime) {
+ // eager remove
+ leftIterator.remove()
+ } // We could do the short-cutting optimization here once we get a
state with ordered keys.
+ }
+ }
+ }
+
+ /**
+ * Called when a registered timer is fired.
+ * Remove rows whose timestamps are earlier than the expiration time,
+ * and register a new timer for the remaining rows.
+ *
+ * @param timestamp the timestamp of the timer
+ * @param ctx the context to register timer or get current time
+ * @param out the collector for returning result values
+ */
+ override def onTimer(
+ timestamp: Long,
+ ctx: CoProcessFunction[CRow, CRow, CRow]#OnTimerContext,
+ out: Collector[CRow]): Unit = {
+ updateOperatorTime(ctx)
+ // In the future, we should separate the left and right watermarks.
Otherwise, the
+ // registered timer of the faster stream will be delayed, even if the
watermarks have
+ // already been emitted by the source.
+ if (leftTimerState.value == timestamp) {
+ rightExpirationTime = calExpirationTime(leftOperatorTime,
rightRelativeSize)
+ removeExpiredRows(
+ rightExpirationTime,
+ rightCache,
+ leftTimerState,
+ ctx,
+ removeLeft = false
+ )
+ }
+
+ if (rightTimerState.value == timestamp) {
+ leftExpirationTime = calExpirationTime(rightOperatorTime,
leftRelativeSize)
+ removeExpiredRows(
+ leftExpirationTime,
+ leftCache,
+ rightTimerState,
+ ctx,
+ removeLeft = true
+ )
+ }
+ }
+
+ /**
+ * Calculate the expiration time with the given operator time and
relative window size.
+ *
+ * @param operatorTime the operator time
+ * @param relativeSize the relative window size
+ * @return the expiration time for cached rows
+ */
+ private def calExpirationTime(operatorTime: Long, relativeSize: Long):
Long = {
+ if (operatorTime < Long.MaxValue) {
--- End diff --
Since `relativeSize` may be negative, the expression `operatorTime -
relativeSize - allowedLateness - 1` will overflow when `operatorTime =
Long.MaxValue` and `relativeSize < 0`. When encountered this, there will be
endless timers with negative expiration times (which should have been
`Long.MaxValue`) being recursively registered and the job will never stop.
> Support rowtime inner equi-join between two streams in the SQL API
> ------------------------------------------------------------------
>
> Key: FLINK-6233
> URL: https://issues.apache.org/jira/browse/FLINK-6233
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: hongyuhong
> Assignee: Xingcan Cui
>
> The goal of this issue is to add support for inner equi-join on proc time
> streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT o.rowtime , o.productId, o.orderId, s.rowtime AS shipTime
> FROM Orders AS o
> JOIN Shipments AS s
> ON o.orderId = s.orderId
> AND o.rowtime BETWEEN s.rowtime AND s.rowtime + INTERVAL '1' HOUR;
> {code}
> The following restrictions should initially apply:
> * The join hint only support inner join
> * The ON clause should include equi-join condition
> * The time-condition {{o.rowtime BETWEEN s.rowtime AND s.rowtime + INTERVAL
> '1' HOUR}} only can use rowtime that is a system attribute, the time
> condition only support bounded time range like {{o.rowtime BETWEEN s.rowtime
> - INTERVAL '1' HOUR AND s.rowtime + INTERVAL '1' HOUR}}, not support
> unbounded like {{o.rowtime < s.rowtime}} , and should include both two
> stream's rowtime attribute, {{o.rowtime between rowtime () and rowtime () +
> 1}} should also not be supported.
> An row-time streams join will not be able to handle late data, because this
> would mean in insert a row into a sorted order shift all other computations.
> This would be too expensive to maintain. Therefore, we will throw an error if
> a user tries to use an row-time stream join with late data handling.
> This issue includes:
> * Design of the DataStream operator to deal with stream join
> * Translation from Calcite's RelNode representation (LogicalJoin).
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