TestInputSampler.java
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* 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.hadoop.mapreduce.lib.partition;
import static org.junit.Assert.assertEquals;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapreduce.InputFormat;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.junit.Test;
public class TestInputSampler {
static class SequentialSplit extends InputSplit {
private int i;
SequentialSplit(int i) {
this.i = i;
}
public long getLength() { return 0; }
public String[] getLocations() { return new String[0]; }
public int getInit() { return i; }
}
static class MapredSequentialSplit implements org.apache.hadoop.mapred.InputSplit {
private int i;
MapredSequentialSplit(int i) {
this.i = i;
}
@Override
public long getLength() { return 0; }
@Override
public String[] getLocations() { return new String[0]; }
public int getInit() { return i; }
@Override
public void write(DataOutput out) throws IOException {
}
@Override
public void readFields(DataInput in) throws IOException {
}
}
static class TestInputSamplerIF
extends InputFormat<IntWritable,NullWritable> {
final int maxDepth;
final ArrayList<InputSplit> splits = new ArrayList<InputSplit>();
TestInputSamplerIF(int maxDepth, int numSplits, int... splitInit) {
this.maxDepth = maxDepth;
assert splitInit.length == numSplits;
for (int i = 0; i < numSplits; ++i) {
splits.add(new SequentialSplit(splitInit[i]));
}
}
public List<InputSplit> getSplits(JobContext context)
throws IOException, InterruptedException {
return splits;
}
public RecordReader<IntWritable,NullWritable> createRecordReader(
final InputSplit split, TaskAttemptContext context)
throws IOException, InterruptedException {
return new RecordReader<IntWritable,NullWritable>() {
private int maxVal;
private final IntWritable i = new IntWritable();
public void initialize(InputSplit split, TaskAttemptContext context)
throws IOException, InterruptedException {
i.set(((SequentialSplit)split).getInit() - 1);
maxVal = i.get() + maxDepth + 1;
}
public boolean nextKeyValue() {
i.set(i.get() + 1);
return i.get() < maxVal;
}
public IntWritable getCurrentKey() { return i; }
public NullWritable getCurrentValue() { return NullWritable.get(); }
public float getProgress() { return 1.0f; }
public void close() { }
};
}
}
static class TestMapredInputSamplerIF extends TestInputSamplerIF implements
org.apache.hadoop.mapred.InputFormat<IntWritable,NullWritable> {
TestMapredInputSamplerIF(int maxDepth, int numSplits, int... splitInit) {
super(maxDepth, numSplits, splitInit);
}
@Override
public org.apache.hadoop.mapred.InputSplit[] getSplits(JobConf job,
int numSplits) throws IOException {
List<InputSplit> splits = null;
try {
splits = getSplits(Job.getInstance(job));
} catch (InterruptedException e) {
throw new IOException(e);
}
org.apache.hadoop.mapred.InputSplit[] retVals =
new org.apache.hadoop.mapred.InputSplit[splits.size()];
for (int i = 0; i < splits.size(); ++i) {
MapredSequentialSplit split = new MapredSequentialSplit(
((SequentialSplit) splits.get(i)).getInit());
retVals[i] = split;
}
return retVals;
}
@Override
public org.apache.hadoop.mapred.RecordReader<IntWritable, NullWritable>
getRecordReader(final org.apache.hadoop.mapred.InputSplit split,
JobConf job, Reporter reporter) throws IOException {
return new org.apache.hadoop.mapred.RecordReader
<IntWritable, NullWritable>() {
private final IntWritable i =
new IntWritable(((MapredSequentialSplit)split).getInit());
private int maxVal = i.get() + maxDepth + 1;
@Override
public boolean next(IntWritable key, NullWritable value)
throws IOException {
i.set(i.get() + 1);
return i.get() < maxVal;
}
@Override
public IntWritable createKey() {
return new IntWritable(i.get());
}
@Override
public NullWritable createValue() {
return NullWritable.get();
}
@Override
public long getPos() throws IOException {
return 0;
}
@Override
public void close() throws IOException {
}
@Override
public float getProgress() throws IOException {
return 0;
}
};
}
}
/**
* Verify SplitSampler contract, that an equal number of records are taken
* from the first splits.
*/
@Test
@SuppressWarnings("unchecked") // IntWritable comparator not typesafe
public void testSplitSampler() throws Exception {
final int TOT_SPLITS = 15;
final int NUM_SPLITS = 5;
final int STEP_SAMPLE = 5;
final int NUM_SAMPLES = NUM_SPLITS * STEP_SAMPLE;
InputSampler.Sampler<IntWritable,NullWritable> sampler =
new InputSampler.SplitSampler<IntWritable,NullWritable>(
NUM_SAMPLES, NUM_SPLITS);
int inits[] = new int[TOT_SPLITS];
for (int i = 0; i < TOT_SPLITS; ++i) {
inits[i] = i * STEP_SAMPLE;
}
Job ignored = Job.getInstance();
Object[] samples = sampler.getSample(
new TestInputSamplerIF(100000, TOT_SPLITS, inits), ignored);
assertEquals(NUM_SAMPLES, samples.length);
Arrays.sort(samples, new IntWritable.Comparator());
for (int i = 0; i < NUM_SAMPLES; ++i) {
assertEquals(i, ((IntWritable)samples[i]).get());
}
}
/**
* Verify SplitSampler contract in mapred.lib.InputSampler, which is added
* back for binary compatibility of M/R 1.x
*/
@Test (timeout = 30000)
@SuppressWarnings("unchecked") // IntWritable comparator not typesafe
public void testMapredSplitSampler() throws Exception {
final int TOT_SPLITS = 15;
final int NUM_SPLITS = 5;
final int STEP_SAMPLE = 5;
final int NUM_SAMPLES = NUM_SPLITS * STEP_SAMPLE;
org.apache.hadoop.mapred.lib.InputSampler.Sampler<IntWritable,NullWritable>
sampler = new org.apache.hadoop.mapred.lib.InputSampler.SplitSampler
<IntWritable,NullWritable>(NUM_SAMPLES, NUM_SPLITS);
int inits[] = new int[TOT_SPLITS];
for (int i = 0; i < TOT_SPLITS; ++i) {
inits[i] = i * STEP_SAMPLE;
}
Object[] samples = sampler.getSample(
new TestMapredInputSamplerIF(100000, TOT_SPLITS, inits),
new JobConf());
assertEquals(NUM_SAMPLES, samples.length);
Arrays.sort(samples, new IntWritable.Comparator());
for (int i = 0; i < NUM_SAMPLES; ++i) {
// mapred.lib.InputSampler.SplitSampler has a sampling step
assertEquals(i % STEP_SAMPLE + TOT_SPLITS * (i / STEP_SAMPLE),
((IntWritable)samples[i]).get());
}
}
/**
* Verify IntervalSampler contract, that samples are taken at regular
* intervals from the given splits.
*/
@Test
@SuppressWarnings("unchecked") // IntWritable comparator not typesafe
public void testIntervalSampler() throws Exception {
final int TOT_SPLITS = 16;
final int PER_SPLIT_SAMPLE = 4;
final int NUM_SAMPLES = TOT_SPLITS * PER_SPLIT_SAMPLE;
final double FREQ = 1.0 / TOT_SPLITS;
InputSampler.Sampler<IntWritable,NullWritable> sampler =
new InputSampler.IntervalSampler<IntWritable,NullWritable>(
FREQ, NUM_SAMPLES);
int inits[] = new int[TOT_SPLITS];
for (int i = 0; i < TOT_SPLITS; ++i) {
inits[i] = i;
}
Job ignored = Job.getInstance();
Object[] samples = sampler.getSample(new TestInputSamplerIF(
NUM_SAMPLES, TOT_SPLITS, inits), ignored);
assertEquals(NUM_SAMPLES, samples.length);
Arrays.sort(samples, new IntWritable.Comparator());
for (int i = 0; i < NUM_SAMPLES; ++i) {
assertEquals(i, ((IntWritable)samples[i]).get());
}
}
/**
* Verify IntervalSampler in mapred.lib.InputSampler, which is added back
* for binary compatibility of M/R 1.x
*/
@Test (timeout = 30000)
@SuppressWarnings("unchecked") // IntWritable comparator not typesafe
public void testMapredIntervalSampler() throws Exception {
final int TOT_SPLITS = 16;
final int PER_SPLIT_SAMPLE = 4;
final int NUM_SAMPLES = TOT_SPLITS * PER_SPLIT_SAMPLE;
final double FREQ = 1.0 / TOT_SPLITS;
org.apache.hadoop.mapred.lib.InputSampler.Sampler<IntWritable,NullWritable>
sampler = new org.apache.hadoop.mapred.lib.InputSampler.IntervalSampler
<IntWritable,NullWritable>(FREQ, NUM_SAMPLES);
int inits[] = new int[TOT_SPLITS];
for (int i = 0; i < TOT_SPLITS; ++i) {
inits[i] = i;
}
Job ignored = Job.getInstance();
Object[] samples = sampler.getSample(new TestInputSamplerIF(
NUM_SAMPLES, TOT_SPLITS, inits), ignored);
assertEquals(NUM_SAMPLES, samples.length);
Arrays.sort(samples, new IntWritable.Comparator());
for (int i = 0; i < NUM_SAMPLES; ++i) {
assertEquals(i,
((IntWritable)samples[i]).get());
}
}
}