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https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15947268#comment-15947268
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ASF GitHub Bot commented on FLINK-5653:
---------------------------------------

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

    https://github.com/apache/flink/pull/3574#discussion_r108686885
  
    --- Diff: 
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/BoundedProcessingOverRowProcessFunction.scala
 ---
    @@ -0,0 +1,182 @@
    +/*
    + * 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 org.apache.flink.configuration.Configuration
    +import org.apache.flink.streaming.api.functions.ProcessFunction
    +import org.apache.flink.types.Row
    +import org.apache.flink.util.{ Collector, Preconditions }
    +import org.apache.flink.api.common.state.ValueStateDescriptor
    +import org.apache.flink.api.java.typeutils.RowTypeInfo
    +import org.apache.flink.api.common.state.ValueState
    +import org.apache.flink.table.functions.{ Accumulator, AggregateFunction }
    +import org.apache.flink.api.common.state.MapState
    +import org.apache.flink.api.common.state.MapStateDescriptor
    +import org.apache.flink.api.common.typeinfo.TypeInformation
    +import org.apache.flink.api.java.typeutils.ListTypeInfo
    +import java.util.{ ArrayList, LinkedList, List => JList }
    +import org.apache.flink.api.common.typeinfo.BasicTypeInfo
    +
    +class BoundedProcessingOverRowProcessFunction(
    +  private val aggregates: Array[AggregateFunction[_]],
    +  private val aggFields: Array[Int],
    +  private val precedingOffset: Int,
    +  private val forwardedFieldCount: Int,
    +  private val aggregatesTypeInfo: RowTypeInfo,
    +  private val inputType: TypeInformation[Row])
    +    extends ProcessFunction[Row, Row] {
    +
    +  Preconditions.checkNotNull(aggregates)
    +  Preconditions.checkNotNull(aggFields)
    +  Preconditions.checkArgument(aggregates.length == aggFields.length)
    +  Preconditions.checkArgument(precedingOffset > 0)
    +
    +  private var accumulators: Row = _
    +  private var accumulatorState: ValueState[Row] = _
    +  private var rowMapState: MapState[Long, JList[Row]] = _
    +  private var output: Row = _
    +  private var counterState: ValueState[Long] = _
    +  private var counter : Long = _
    +  private var smallestTsState: ValueState[Long] = _
    +  private var smallestTs : Long = _
    +  
    +  override def open(config: Configuration) {
    +    
    +    output = new Row(forwardedFieldCount + aggregates.length)
    +    // We keep the elements received in a list state 
    --- End diff --
    
    Update comment. We use a `MapState` keyed by the ingestion time.


> Add processing time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> --------------------------------------------------------------------
>
>                 Key: FLINK-5653
>                 URL: https://issues.apache.org/jira/browse/FLINK-5653
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: Fabian Hueske
>            Assignee: Stefano Bortoli
>
> The goal of this issue is to add support for OVER ROWS aggregations on 
> processing time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT 
>   a, 
>   SUM(b) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2 PRECEDING 
> AND CURRENT ROW) AS sumB,
>   MIN(b) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2 PRECEDING 
> AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The PARTITION BY clause is optional (no partitioning results in single 
> threaded execution).
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a 
> parameterless scalar function that just indicates processing time mode.
> - UNBOUNDED PRECEDING is not supported (see FLINK-5656)
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some 
> of the restrictions are trivial to address, we can add the functionality in 
> this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with 
> RexOver expression).



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