org.apache.pig.impl.builtin.PoissonSampleLoader Maven / Gradle / Ivy
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* 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,
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* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.pig.impl.builtin;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Properties;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.pig.backend.executionengine.ExecException;
import org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigSplit;
import org.apache.pig.data.Tuple;
import org.apache.pig.data.TupleFactory;
import org.apache.pig.impl.PigContext;
import org.apache.pig.impl.io.FileSpec;
import org.apache.pig.impl.util.Pair;
/**
* See "Skewed Join sampler" in http://wiki.apache.org/pig/PigSampler
*/
public class PoissonSampleLoader extends SampleLoader {
// marker string to mark the last sample row, which has total number or rows
// seen by this map instance
// this string will be in the 2nd last column of the last sample row
// it is used by GetMemNumRows
public static final String NUMROWS_TUPLE_MARKER =
"\u4956\u3838_pig_inTeRnal-spEcial_roW_num_tuple3kt579CFLehkblah";
//num of rows sampled so far
private int numRowsSampled = 0;
//average size of tuple in memory, for tuples sampled
private long avgTupleMemSz = 0;
//current row number
private long rowNum = 0;
// number of tuples to skip after each sample
long skipInterval = -1;
// bytes in input to skip after every sample.
// divide this by avgTupleMemSize to get skipInterval
private long memToSkipPerSample = 0;
// has the special row with row number information been returned
private boolean numRowSplTupleReturned = false;
/// For a given mean and a confidence, a sample rate is obtained from a poisson cdf
private static final String SAMPLE_RATE = "pig.sksampler.samplerate";
// 17 is not a magic number. It can be obtained by using a poisson cumulative distribution function with the mean
// set to 10 (emperically, minimum number of samples) and the confidence set to 95%
private static final int DEFAULT_SAMPLE_RATE = 17;
private int sampleRate = DEFAULT_SAMPLE_RATE;
/// % of memory available for the input data. This is currenty equal to the memory available
/// for the skewed join
private static final String PERC_MEM_AVAIL = "pig.skewedjoin.reduce.memusage";
private double heapPerc = PartitionSkewedKeys.DEFAULT_PERCENT_MEMUSAGE;
// new Sample tuple
private Tuple newSample = null;
// private final Log log = LogFactory.getLog(getClass());
public PoissonSampleLoader(String funcSpec, String ns) {
super(funcSpec);
super.setNumSamples(Integer.valueOf(ns)); // will be overridden
}
@Override
public Tuple getNext() throws IOException {
if(numRowSplTupleReturned){
// row num special row has been returned after all inputs
// were read, nothing more to read
return null;
}
if(skipInterval == -1){
//select first tuple as sample and calculate
// number of tuples to be skipped
Tuple t = loader.getNext();
if(t == null)
return createNumRowTuple(null);
long availRedMem = (long) (Runtime.getRuntime().maxMemory() * heapPerc);
memToSkipPerSample = availRedMem/sampleRate;
updateSkipInterval(t);
rowNum++;
newSample = t;
}
// skip tuples
for(long numSkipped = 0; numSkipped < skipInterval; numSkipped++){
if(!skipNext()){
return createNumRowTuple(newSample);
}
rowNum++;
}
// skipped enough, get new sample
Tuple t = loader.getNext();
if(t == null)
return createNumRowTuple(newSample);
updateSkipInterval(t);
rowNum++;
Tuple currentSample = newSample;
newSample = t;
return currentSample;
}
/**
* Update the average tuple size base on newly sampled tuple t
* and recalculate skipInterval
* @param t - tuple
*/
private void updateSkipInterval(Tuple t) {
avgTupleMemSz =
((avgTupleMemSz*numRowsSampled) + t.getMemorySize())/(numRowsSampled + 1);
skipInterval = memToSkipPerSample/avgTupleMemSz;
// skipping fewer number of rows the first few times, to reduce
// the probability of first tuples size (if much smaller than rest)
// resulting in
// very few samples being sampled. Sampling a little extra is OK
if(numRowsSampled < 5)
skipInterval = skipInterval/(10-numRowsSampled);
++numRowsSampled;
}
/**
* @param sample - sample tuple
* @return - Tuple appended with special marker string column, num-rows column
* @throws ExecException
*/
private Tuple createNumRowTuple(Tuple sample) throws ExecException {
int sz = (sample == null) ? 0 : sample.size();
TupleFactory factory = TupleFactory.getInstance();
Tuple t = factory.newTuple(sz + 2);
if (sample != null) {
for(int i=0; i