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From fhueske <...@git.apache.org>
Subject [GitHub] flink pull request #3386: [FLINK-5658][table] support unbounded eventtime ov...
Date Thu, 23 Mar 2017 16:41:58 GMT
Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3386#discussion_r107712202
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/UnboundedEventTimeOverProcessFunction.scala
---
    @@ -0,0 +1,200 @@
    +/*
    + * 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.aggregate
    +
    +import java.util.{ArrayList, LinkedList, List => JList}
    +
    +import org.apache.flink.api.common.typeinfo.{BasicTypeInfo, TypeInformation}
    +import org.apache.flink.configuration.Configuration
    +import org.apache.flink.types.Row
    +import org.apache.flink.streaming.api.functions.ProcessFunction
    +import org.apache.flink.util.{Collector, Preconditions}
    +import org.apache.flink.api.common.state._
    +import org.apache.flink.api.java.typeutils.{ListTypeInfo}
    +import org.apache.flink.streaming.api.operators.TimestampedCollector
    +import org.apache.flink.table.functions.{Accumulator, AggregateFunction}
    +
    +
    +/**
    +  * A ProcessFunction to support unbounded event-time over-window
    +  *
    +  * @param aggregates the aggregate functions
    +  * @param aggFields  the filed index which the aggregate functions use
    +  * @param forwardedFieldCount the input fields count
    +  * @param intermediateType the intermediate row tye which the state saved
    +  * @param inputType the input row tye which the state saved
    +  *
    +  */
    +class UnboundedEventTimeOverProcessFunction(
    +    private val aggregates: Array[AggregateFunction[_]],
    +    private val aggFields: Array[Int],
    +    private val forwardedFieldCount: Int,
    +    private val intermediateType: TypeInformation[Row],
    +    private val inputType: TypeInformation[Row])
    +  extends ProcessFunction[Row, Row]{
    +
    +  Preconditions.checkNotNull(aggregates)
    +  Preconditions.checkNotNull(aggFields)
    +  Preconditions.checkArgument(aggregates.length == aggFields.length)
    +
    +  private var output: Row = _
    +  private var accumulatorState: ValueState[Row] = _
    +  private var rowMapState: MapState[Long, JList[Row]] = _
    +  private var sortList: LinkedList[Long] = _
    +
    +
    +  override def open(config: Configuration) {
    +    output = new Row(forwardedFieldCount + aggregates.length)
    +    sortList = new LinkedList[Long]()
    +
    +    val stateDescriptor: ValueStateDescriptor[Row] =
    +      new ValueStateDescriptor[Row]("accumulatorstate", intermediateType)
    +    accumulatorState = getRuntimeContext.getState[Row](stateDescriptor)
    +
    +    val rowListTypeInfo: TypeInformation[JList[Row]] =
    +      new ListTypeInfo[Row](inputType).asInstanceOf[TypeInformation[JList[Row]]]
    +    val mapStateDescriptor: MapStateDescriptor[Long, JList[Row]] =
    +      new MapStateDescriptor[Long, JList[Row]]("rowmapstate",
    +        BasicTypeInfo.LONG_TYPE_INFO.asInstanceOf[TypeInformation[Long]], rowListTypeInfo)
    +    rowMapState = getRuntimeContext.getMapState(mapStateDescriptor)
    +  }
    +
    +  /**
    +    * Process one element from the input stream, not emit the output
    +    *
    +    * @param input The input value.
    +    * @param ctx   The ctx to register timer or get current time
    +    * @param out   The collector for returning result values.
    +    *
    +    */
    +  override def processElement(
    +     input: Row,
    +     ctx:  ProcessFunction[Row, Row]#Context,
    +     out: Collector[Row]): Unit = {
    +
    +    // discard later record
    +    if (ctx.timestamp() >= ctx.timerService().currentWatermark()) {
    +      // ensure every key just register on timer
    +      ctx.timerService.registerEventTimeTimer(ctx.timerService.currentWatermark + 1)
    +
    +      val rowList =
    +        if (rowMapState.contains(ctx.timestamp)) rowMapState.get(ctx.timestamp)
    --- End diff --
    
    we can directly call `get()` and check for `null`. This will save one call to the state
backend.


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