/* * 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.executionengine.ExecException; 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.BagFactory; import org.apache.pig.data.DataBag; import org.apache.pig.data.Tuple; import org.apache.pig.data.TupleFactory; import org.apache.pig.impl.builtin.FindQuantiles; public class FindQuantilesTez extends FindQuantiles { private static final Log LOG = LogFactory.getLog(FindQuantilesTez.class); private static TupleFactory tf = TupleFactory.getInstance(); public FindQuantilesTez() { super(); } public FindQuantilesTez(String[] args) { super(args); } @Override public Map<String, Object> exec(Tuple in) throws IOException { // In Tez, we also need to estimate the quantiles with regard to sample // and the special tuple containing the total number of records int estimatedNumReducers = -1; boolean estimate_sample_quantile = PigMapReduce.sJobConfInternal.get().getBoolean (PigProcessor.ESTIMATE_PARALLELISM, false); DataBag mySamples = (DataBag)in.get(1); this.samples = BagFactory.getInstance().newDefaultBag(); Iterator<Tuple> iter = mySamples.iterator(); Tuple t; //total input rows for the order by long totalInputRows = 0; long sampleSize = 0; while (iter.hasNext()) { t = iter.next(); if (t.get(t.size() - 1) != null) { totalInputRows += (Long)t.get(t.size() - 1); } if (t.get(t.size() - 2) != null) { sampleSize += getMemorySize(t); } if (t.size() > 2) { Tuple newTuple = tf.newTuple(t.size()-2); for (int i=0;i<t.size()-2;i++) { newTuple.set(i, t.get(i)); } this.samples.add(newTuple); } } if (estimate_sample_quantile) { long bytesPerTask = PigMapReduce.sJobConfInternal.get().getLong(InputSizeReducerEstimator.BYTES_PER_REDUCER_PARAM, InputSizeReducerEstimator.DEFAULT_BYTES_PER_REDUCER); long estimatedInputSize = (long)((double)sampleSize/mySamples.size() * totalInputRows); estimatedNumReducers = (int)Math.ceil((double)estimatedInputSize/bytesPerTask); estimatedNumReducers = Math.min(estimatedNumReducers, InputSizeReducerEstimator.DEFAULT_MAX_REDUCER_COUNT_PARAM); if (estimatedNumReducers==0) { estimatedNumReducers = 1; } LOG.info("Estimating parallelism: estimatedInputSize is " + estimatedInputSize + ". bytesPerTask is " + bytesPerTask + ". estimatedNumQuantiles is " + estimatedNumReducers + "."); this.numQuantiles = estimatedNumReducers; LOG.info("Use estimated parallelism instead:" + estimatedNumReducers); } Map<String, Object> result = super.exec(in); if (estimate_sample_quantile) { result.put(PigProcessor.ESTIMATED_NUM_PARALLELISM, numQuantiles); } PigProcessor.sampleMap = result; return result; } // the last field of the tuple is a tuple for memory size and disk size protected long getMemorySize(Tuple t) { int s = t.size(); try { return (Long) t.get(s - 2); } catch (ExecException e) { throw new RuntimeException( "Unable to retrive the size field from tuple.", e); } } }