/*
* 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.pig.backend.hadoop.executionengine.tez.plan.udf;
import java.io.IOException;
import java.util.Iterator;
import java.util.Map;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.InputSizeReducerEstimator;
import org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigMapReduce;
import org.apache.pig.backend.hadoop.executionengine.tez.runtime.PigProcessor;
import org.apache.pig.data.DataBag;
import org.apache.pig.data.Tuple;
import org.apache.pig.impl.builtin.PartitionSkewedKeys;
public class PartitionSkewedKeysTez extends PartitionSkewedKeys {
private static final Log LOG = LogFactory.getLog(PartitionSkewedKeysTez.class);
public PartitionSkewedKeysTez() {
super();
}
public PartitionSkewedKeysTez(String[] args) {
super(args);
}
@Override
public Map<String, Object> exec(Tuple in) throws IOException {
if (in == null || in.size() == 0) {
return null;
}
int estimatedNumReducers = -1;
boolean estimate_sample_quantile = PigMapReduce.sJobConfInternal.get().getBoolean
(PigProcessor.ESTIMATE_PARALLELISM, false);
if (estimate_sample_quantile) {
int specifiedNumReducer = (Integer) in.get(0);
DataBag samples = (DataBag) in.get(1);
long totalSampleSize = 0;
long totalInputRows = 0;
Iterator<Tuple> iter = samples.iterator();
while (iter.hasNext()) {
Tuple t = iter.next();
totalInputRows += (Long)t.get(t.size() - 1);
totalSampleSize += getMemorySize(t);
}
long totalSampleCount_ = samples.size();
long estimatedInputSize = (long)((double)totalSampleSize/totalSampleCount_ * totalInputRows);
long bytesPerTask = PigMapReduce.sJobConfInternal.get().getLong(InputSizeReducerEstimator.BYTES_PER_REDUCER_PARAM,
InputSizeReducerEstimator.DEFAULT_BYTES_PER_REDUCER);
estimatedNumReducers = (int)Math.ceil((double)estimatedInputSize/bytesPerTask);
estimatedNumReducers = Math.min(estimatedNumReducers, InputSizeReducerEstimator.DEFAULT_MAX_REDUCER_COUNT_PARAM);
LOG.info("Estimating parallelism: estimatedInputSize is " + estimatedInputSize + ". bytesPerTask is " + bytesPerTask + ". estimatedNumReducers is " + estimatedNumReducers + ".");
this.totalReducers_ = estimatedNumReducers;
LOG.info("Use estimated reducer instead:" + estimatedNumReducers + ", orig: " + specifiedNumReducer);
}
Map<String, Object> result = super.exec(in);
if (estimate_sample_quantile) {
result.put(PigProcessor.ESTIMATED_NUM_PARALLELISM, totalReducers_);
}
PigProcessor.sampleMap = result;
return result;
}
}