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Librares that make easier to solve data problems using Hadoop and higher level languages based on it.

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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 datafu.hourglass.mapreduce;

import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.Serializable;

import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.mapred.AvroKey;
import org.apache.avro.mapred.AvroValue;
import org.apache.hadoop.mapreduce.ReduceContext;


import datafu.hourglass.fs.DateRange;
import datafu.hourglass.jobs.DateRangeConfigurable;
import datafu.hourglass.model.Accumulator;
import datafu.hourglass.schemas.PartitionCollapsingSchemas;

/**
 * The combiner used by {@link datafu.hourglass.jobs.AbstractPartitionCollapsingIncrementalJob} and its derived classes.
 * 
 * 

* An implementation of {@link datafu.hourglass.model.Accumulator} is used to perform aggregation and produce the * intermediate value. *

* */ public class CollapsingCombiner extends ObjectReducer implements DateRangeConfigurable, Serializable { private Accumulator _accumulator; private boolean _reusePreviousOutput; private PartitionCollapsingSchemas _schemas; private long _beginTime; private long _endTime; @SuppressWarnings("unchecked") public void reduce(Object keyObj, Iterable values, ReduceContext context) throws IOException, InterruptedException { Accumulator acc = getAccumulator(); if (acc == null) { throw new RuntimeException("No combiner factory set"); } long accumulatedCount = 0; acc.cleanup(); for (Object valueObj : values) { GenericRecord value = ((AvroValue)valueObj).datum(); if (value.getSchema().getFullName().equals(getSchemas().getIntermediateValueSchema().getFullName())) { acc.accumulate(value); accumulatedCount++; } else if (value.getSchema().getFullName().equals(getSchemas().getDatedIntermediateValueSchema().getFullName())) { if (!_reusePreviousOutput) { throw new RuntimeException("Did not expect " + getSchemas().getDatedIntermediateValueSchema().getFullName()); } Long time = (Long)value.get("time"); GenericRecord data = (GenericData.Record)value.get("value"); if (time == null) { throw new RuntimeException("time is null"); } if (data == null) { throw new RuntimeException("value is null"); } if (time >= _beginTime && time <= _endTime) { acc.accumulate(data); accumulatedCount++; } else if (time < _beginTime) { // pass through unchanged, reducer will handle it context.write((AvroKey)keyObj,new AvroValue(value)); } else { throw new RuntimeException(String.format("Time %d is greater than end time %d",time,_endTime)); } } else if (value.getSchema().getFullName().equals(getSchemas().getOutputValueSchema().getFullName())) { if (!_reusePreviousOutput) { throw new RuntimeException("Did not expect " + getSchemas().getOutputValueSchema().getFullName()); } // pass through unchanged, reducer will handle it context.write((AvroKey)keyObj,new AvroValue(value)); } else { throw new RuntimeException("Unexpected type: " + value.getSchema().getFullName()); } } if (accumulatedCount > 0) { GenericRecord intermediateValue = acc.getFinal(); if (intermediateValue != null) { context.write((AvroKey)keyObj,new AvroValue(intermediateValue)); } } } /** * Sets the schemas. * * @param schemas schemas used by the combiner */ public void setSchemas(PartitionCollapsingSchemas schemas) { _schemas = schemas; } /** * Gets the schemas. * * @return schemas schemas used by the combiner */ public PartitionCollapsingSchemas getSchemas() { return _schemas; } /** * Gets whether previous output is being reused. * * @return true if previous output is reused */ public boolean getReuseOutput() { return _reusePreviousOutput; } /** * Sets whether previous output is being reused. * * @param reuseOutput true if previous output is reused */ public void setReuseOutput(boolean reuseOutput) { _reusePreviousOutput = reuseOutput; } /** * Gets the accumulator used to perform aggregation. * * @return The accumulator */ public Accumulator getAccumulator() { return _accumulator; } /** * Sets the accumulator used to perform aggregation. * * @param acc The accumulator */ public void setAccumulator(Accumulator acc) { _accumulator = cloneAccumulator(acc); } public void setOutputDateRange(DateRange dateRange) { _beginTime = dateRange.getBeginDate().getTime(); _endTime = dateRange.getEndDate().getTime(); } /** * Clone a {@link Accumulator} by serializing and deserializing it. * * @param acc The accumulator to clone * @return The clone accumulator */ private Accumulator cloneAccumulator(Accumulator acc) { try { // clone by serializing ByteArrayOutputStream outputStream = new ByteArrayOutputStream(); ObjectOutputStream objStream; objStream = new ObjectOutputStream(outputStream); objStream.writeObject(acc); objStream.close(); outputStream.close(); ByteArrayInputStream inputStream = new ByteArrayInputStream(outputStream.toByteArray()); ObjectInputStream objInputStream = new ObjectInputStream(inputStream); @SuppressWarnings("unchecked") Accumulator result = (Accumulator)objInputStream.readObject(); objInputStream.close(); inputStream.close(); return result; } catch (IOException e) { throw new RuntimeException(e); } catch (ClassNotFoundException e) { throw new RuntimeException(e); } } }