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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1297) Add support for tracking statistics of intermediate results
Date Tue, 21 Apr 2015 17:11:58 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14505292#comment-14505292
] 

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

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

    https://github.com/apache/flink/pull/605#discussion_r28799879
  
    --- Diff: flink-contrib/src/test/java/org/apache/flink/contrib/operatorstatistics/OperatorStatsAccumulatorsTest.java
---
    @@ -0,0 +1,144 @@
    +/*
    + * 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.contrib.operatorstatistics;
    +
    +import org.apache.flink.api.common.JobExecutionResult;
    +import org.apache.flink.api.common.accumulators.Accumulator;
    +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.test.util.AbstractTestBase;
    +import org.apache.flink.util.Collector;
    +import org.junit.Assert;
    +import org.junit.Test;
    +import org.slf4j.Logger;
    +import org.slf4j.LoggerFactory;
    +
    +import java.io.Serializable;
    +import java.util.Map;
    +import java.util.Random;
    +
    +public class OperatorStatsAccumulatorsTest extends AbstractTestBase {
    +
    +	private static final Logger LOG = LoggerFactory.getLogger(OperatorStatsAccumulatorsTest.class);
    +
    +	private static final String ACCUMULATOR_NAME = "op-stats";
    +
    +	public OperatorStatsAccumulatorsTest(){
    +		super(new Configuration());
    +	}
    +
    +	@Test
    +	public void testAccumulator() throws Exception {
    +
    +		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();
    +
    +		OperatorStatistics globalStats = result.getAccumulatorResult(ACCUMULATOR_NAME);
    +		LOG.debug("Global Stats");
    +		LOG.debug(globalStats.toString());
    +
    +		OperatorStatistics merged = null;
    +
    +		Map<String,Object> accResults = result.getAllAccumulatorResults();
    +		for (String accumulatorName:accResults.keySet()){
    +			if (accumulatorName.contains(ACCUMULATOR_NAME+"-")){
    +				OperatorStatistics localStats = (OperatorStatistics) accResults.get(accumulatorName);
    +				if (merged == null){
    +					merged = localStats.clone();
    +				}else {
    +					merged.merge(localStats);
    +				}
    +				LOG.debug("Local Stats: " + accumulatorName);
    +				LOG.debug(localStats.toString());
    +			}
    +		}
    +
    +		Assert.assertEquals(globalStats.cardinality,999);
    +		Assert.assertEquals(globalStats.estimateCountDistinct(),100);
    +		Assert.assertTrue(globalStats.getHeavyHitters().size()>0 && globalStats.getHeavyHitters().size()<=5);
    +		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());
    +
    +	}
    +
    +	public static class StringToInt extends RichFlatMapFunction<String, Tuple1<Integer>>
{
    +
    +		// Is instantiated later since the runtime context is not yet initialized
    +		private Accumulator<Object, Serializable> globalAccumulator;
    +		private Accumulator<Object,Serializable>[] localAccumulators;
    --- End diff --
    
    Does it make sense to use some event notification logic for pluggable components at critical
points (e.g. open/close method of UDFs)?


> 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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