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https://issues.apache.org/jira/browse/FLINK-3474?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15173638#comment-15173638
 ] 

ASF GitHub Bot commented on FLINK-3474:
---------------------------------------

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

    https://github.com/apache/flink/pull/1746#discussion_r54554936
  
    --- Diff: 
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/runtime/aggregate/AggregateUtil.scala
 ---
    @@ -0,0 +1,309 @@
    +/*
    + * 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.api.table.runtime.aggregate
    +
    +import java.util
    +
    +import org.apache.calcite.rel.`type`._
    +import org.apache.calcite.rel.core.AggregateCall
    +import org.apache.calcite.sql.SqlAggFunction
    +import org.apache.calcite.sql.`type`.SqlTypeName._
    +import org.apache.calcite.sql.`type`.{SqlTypeFactoryImpl, SqlTypeName}
    +import org.apache.calcite.sql.fun._
    +import org.apache.flink.api.common.functions.{GroupReduceFunction, 
MapFunction}
    +import org.apache.flink.api.table.Row
    +import org.apache.flink.api.table.plan.PlanGenException
    +import org.apache.flink.api.table.plan.nodes.logical.FlinkAggregate
    +
    +import scala.collection.JavaConversions._
    +import scala.collection.mutable.ArrayBuffer
    +
    +object AggregateUtil {
    +
    +  /**
    +   * Create Flink operator functions for aggregates. It includes 2 
implementations of Flink 
    +   * operator functions:
    +   * [[org.apache.flink.api.common.functions.MapFunction]] and 
    +   * [[org.apache.flink.api.common.functions.GroupReduceFunction]](if it's 
partial aggregate,
    +   * should also implement 
[[org.apache.flink.api.common.functions.CombineFunction]] as well). 
    +   * The output of [[org.apache.flink.api.common.functions.MapFunction]] 
contains the 
    +   * intermediate aggregate values of all aggregate function, it's stored 
in Row by the following
    +   * format:
    +   *
    +   * {{{
    +   *                   avg(x) aggOffsetInRow = 2          count(z) 
aggOffsetInRow = 5
    +   *                             |                          |
    +   *                             v                          v
    +   *        +---------+---------+--------+--------+--------+--------+
    +   *        |groupKey1|groupKey2|  sum1  | count1 |  sum2  | count2 |
    +   *        +---------+---------+--------+--------+--------+--------+
    +   *                                              ^
    +   *                                              |
    +   *                               sum(y) aggOffsetInRow = 4
    +   * }}}
    +   *
    +   */
    +  def createOperatorFunctionsForAggregates(aggregate: FlinkAggregate,
    +      inputType: RelDataType, outputType: RelDataType,
    +      groupings: Array[Int]): AggregateResult = {
    +
    +    val aggregateCalls: Seq[AggregateCall] = aggregate.getAggCallList
    +    // store the aggregate fields of each aggregate function, by the same 
order of aggregates.
    +    val aggFieldIndexes = new Array[Int](aggregateCalls.size)
    +    val aggregates = new Array[Aggregate[_ <: Any]](aggregateCalls.size)
    +
    +    transformToAggregateFunctions(aggregateCalls, aggFieldIndexes,
    +      aggregates, inputType, groupings.length)
    +
    +    val mapFunction = new AggregateMapFunction(aggregates, 
aggFieldIndexes, groupings)
    +
    +    val bufferDataType: RelRecordType =
    +      createAggregateBufferDataType(groupings, aggregates, inputType)
    +
    +    // the mapping relation between field index of intermediate aggregate 
Row and output Row.
    +    var groupingOffsetMapping = ArrayBuffer[(Int, Int)]()
    +
    +    // the mapping relation between aggregate function index in list and 
its corresponding
    +    // field index in output Row.
    +    var aggOffsetMapping = ArrayBuffer[(Int, Int)]()
    +
    +
    +    outputType.getFieldList.zipWithIndex.foreach {
    --- End diff --
    
    I find this part not easy to understand, partially because it mixes the 
initialization of `groupingOffsetMapping` and `aggOffsetMapping`. How about we 
extend `getMatchedAggregateIndex` and `getMatchedFieldIndex` to completely 
handle the intialization of `aggOffsetMapping` and `groupingOffsetMapping`, 
respectively? 


> Partial aggregate interface design and sort-based implementation
> ----------------------------------------------------------------
>
>                 Key: FLINK-3474
>                 URL: https://issues.apache.org/jira/browse/FLINK-3474
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API
>            Reporter: Chengxiang Li
>            Assignee: Chengxiang Li
>
> The scope of this sub task includes:
> # Partial aggregate interface.
> # Simple aggregate function implementation, such as SUM/AVG/COUNT/MIN/MAX.
> # DataSetAggregateRule which translate logical calcite aggregate node to 
> Flink user functions. As hash-based combiner is not available yet(see PR 
> #1517), we would use sort-based combine as default.



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