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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-3226) Translate optimized logical Table API plans into physical plans representing DataSet programs
Date Mon, 08 Feb 2016 16:50:39 GMT

    [ https://issues.apache.org/jira/browse/FLINK-3226?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15137210#comment-15137210
] 

ASF GitHub Bot commented on FLINK-3226:
---------------------------------------

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

    https://github.com/apache/flink/pull/1600#discussion_r52192844
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/plan/functions/AggregateFunction.scala
---
    @@ -0,0 +1,76 @@
    +/*
    + * 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.plan.functions
    +
    +import java.lang.Iterable
    +import com.google.common.base.Preconditions
    +import org.apache.flink.api.common.functions.RichGroupReduceFunction
    +import org.apache.flink.api.table.plan.functions.aggregate.Aggregate
    +import org.apache.flink.configuration.Configuration
    +import org.apache.flink.util.Collector
    +import scala.collection.JavaConversions._
    +import org.apache.flink.api.table.Row
    +
    +/**
    + * A wrapper Flink GroupReduceOperator UDF of aggregates. It takes the grouped data as
input,
    + * feed to the aggregates, and collect the record with aggregated value.
    + *
    + * @param aggregates SQL aggregate functions.
    + * @param fields The grouped keys' indices in the input.
    + * @param groupingKeys The grouping keys' positions.
    + */
    +class AggregateFunction(
    +    private val aggregates: Array[Aggregate[_ <: Any]],
    +    private val fields: Array[Int],
    +    private val groupingKeys: Array[Int]) extends RichGroupReduceFunction[Row, Row] {
    --- End diff --
    
    Sounds reasonable. Together with the expression functions or separately, e.g. in `org.apache.flink.table.runtime.functions`?


> Translate optimized logical Table API plans into physical plans representing DataSet
programs
> ---------------------------------------------------------------------------------------------
>
>                 Key: FLINK-3226
>                 URL: https://issues.apache.org/jira/browse/FLINK-3226
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API
>            Reporter: Fabian Hueske
>            Assignee: Chengxiang Li
>
> This issue is about translating an (optimized) logical Table API (see FLINK-3225) query
plan into a physical plan. The physical plan is a 1-to-1 representation of the DataSet program
that will be executed. This means:
> - Each Flink RelNode refers to exactly one Flink DataSet or DataStream operator.
> - All (join and grouping) keys of Flink operators are correctly specified.
> - The expressions which are to be executed in user-code are identified.
> - All fields are referenced with their physical execution-time index.
> - Flink type information is available.
> - Optional: Add physical execution hints for joins
> The translation should be the final part of Calcite's optimization process.
> For this task we need to:
> - implement a set of Flink DataSet RelNodes. Each RelNode corresponds to one Flink DataSet
operator (Map, Reduce, Join, ...). The RelNodes must hold all relevant operator information
(keys, user-code expression, strategy hints, parallelism).
> - implement rules to translate optimized Calcite RelNodes into Flink RelNodes. We start
with a straight-forward mapping and later add rules that merge several relational operators
into a single Flink operator, e.g., merge a join followed by a filter. Timo implemented some
rules for the first SQL implementation which can be used as a starting point.
> - Integrate the translation rules into the Calcite optimization process



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