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https://issues.apache.org/jira/browse/FLINK-1297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14499419#comment-14499419
 ] 

ASF GitHub Bot commented on FLINK-1297:
---------------------------------------

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

    https://github.com/apache/flink/pull/605#discussion_r28575727
  
    --- Diff: 
flink-tests/src/test/java/org/apache/flink/test/accumulators/OperatorStatsAccumulatorsTest.java
 ---
    @@ -0,0 +1,118 @@
    +/*
    + * 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.test.accumulators;
    +
    +import org.apache.flink.api.common.JobExecutionResult;
    +import org.apache.flink.api.common.accumulators.OperatorStatsAccumulator;
    +import org.apache.flink.api.common.functions.RichFlatMapFunction;
    +import org.apache.flink.api.java.ExecutionEnvironment;
    +import org.apache.flink.api.java.io.DiscardingOutputFormat;
    +import org.apache.flink.api.java.tuple.Tuple1;
    +import org.apache.flink.configuration.Configuration;
    +import org.apache.flink.statistics.OperatorStatistics;
    +import org.apache.flink.test.util.AbstractTestBase;
    +import org.apache.flink.util.Collector;
    +import org.junit.Assert;
    +import org.junit.Test;
    +
    +import java.util.Random;
    +
    +public class OperatorStatsAccumulatorsTest extends AbstractTestBase {
    +
    +   private static final String ACCUMULATOR_NAME = "op-stats-accumulator";
    +
    +   public OperatorStatsAccumulatorsTest(){
    +           super(new Configuration());
    +   }
    +
    +   @Test
    +   public void testAccumulator() {
    +
    +           try {
    +                   String input = "";
    +
    +                   Random rand = new Random();
    +
    +                   for (int i = 1; i < 1000; i++) {
    +                           if(rand.nextDouble()<0.2){
    +                                   
input+=String.valueOf(rand.nextInt(5))+"\n";
    +                           }else{
    +                                   
input+=String.valueOf(rand.nextInt(100))+"\n";
    +                           }
    +                   }
    +
    +                   String inputFile = createTempFile("datapoints.txt", 
input);
    +
    +                   ExecutionEnvironment env = 
ExecutionEnvironment.getExecutionEnvironment();
    +
    +                   env.readTextFile(inputFile).
    +                                   flatMap(new StringToInt()).
    +                                   output(new 
DiscardingOutputFormat<Tuple1<Integer>>());
    +                   
    +                   JobExecutionResult result = env.execute();
    +                   System.out.println("Accumulator results:");
    +
    +                   OperatorStatistics globalStats = 
result.getOperatorStatisticsResult(ACCUMULATOR_NAME);
    +                   System.out.println("Global Stats");
    +                   System.out.println(globalStats.toString());
    +
    +                   OperatorStatistics[] localStats = 
result.getLocalOperatorStatisticsResults(ACCUMULATOR_NAME);
    +                   System.out.println("Local stats: 0");
    +                   System.out.println(localStats[0].toString());
    +
    +                   OperatorStatistics merged = localStats[0].clone();
    +                   for (int i=1;i<localStats.length;i++) {
    +                           merged.merge(localStats[i]);
    +                           System.out.println("Local stats: "+i);
    +                           System.out.println(localStats[i].toString());
    +                   }
    +                   
Assert.assertEquals(merged.getMin(),globalStats.getMin());
    +                   
Assert.assertEquals(merged.getMax(),globalStats.getMax());
    +                   
Assert.assertEquals(merged.estimateCountDistinct(),globalStats.estimateCountDistinct());
    +                   
Assert.assertEquals(merged.getHeavyHitters().size(),globalStats.getHeavyHitters().size());
    +
    +           }
    +           catch (Exception e) {
    --- End diff --
    
    I would fail the test in case of an exception


> Add support for tracking statistics of intermediate results
> -----------------------------------------------------------
>
>                 Key: FLINK-1297
>                 URL: https://issues.apache.org/jira/browse/FLINK-1297
>             Project: Flink
>          Issue Type: Improvement
>          Components: Distributed Runtime
>            Reporter: Alexander Alexandrov
>            Assignee: Alexander Alexandrov
>             Fix For: 0.9
>
>   Original Estimate: 1,008h
>  Remaining Estimate: 1,008h
>
> One of the major problems related to the optimizer at the moment is the lack 
> of proper statistics.
> With the introduction of staged execution, it is possible to instrument the 
> runtime code with a statistics facility that collects the required 
> information for optimizing the next execution stage.
> I would therefore like to contribute code that can be used to gather basic 
> statistics for the (intermediate) result of dataflows (e.g. min, max, count, 
> count distinct) and make them available to the job manager.
> Before I start, I would like to hear some feedback form the other users.
> In particular, to handle skew (e.g. on grouping) it might be good to have 
> some sort of detailed sketch about the key distribution of an intermediate 
> result. I am not sure whether a simple histogram is the most effective way to 
> go. Maybe somebody would propose another lightweight sketch that provides 
> better accuracy.



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