/* * 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; } }