/** * 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 hip.ch6.joins.repartition.impl; import org.apache.hadoop.io.BooleanWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reporter; import java.io.IOException; import java.util.Iterator; /** * This abstract class serves as the base class for the mapper class of a data * join job. */ public abstract class OptimizedDataJoinMapperBase extends OptimizedJobBase { protected String inputFile = null; protected JobConf job = null; protected Text inputTag = null; protected Reporter reporter = null; protected CompositeKey outputKey = new CompositeKey(); protected BooleanWritable smaller; public void configure(JobConf job) { super.configure(job); this.job = job; this.inputFile = job.get("map.input.file"); this.inputTag = generateInputTag(this.inputFile); if (isInputSmaller(this.inputFile)) { smaller = new BooleanWritable(true); outputKey.setOrder(0); } else { smaller = new BooleanWritable(false); outputKey.setOrder(1); } } /** * Determine the source tag based on the input file name. * * @param inputFile * @return the source tag computed from the given file name. */ protected abstract Text generateInputTag(String inputFile); /** * Generate an output value. The user code can also perform * projection/filtering. If it decides to discard the input record when * certain conditions are met,it can simply return a null. * * @param o the Map input value * @return an object of OutputValue computed from the given value. */ protected abstract OutputValue genMapOutputValue(Object o); /** * Generate a map output key. The user code can compute the key * programmatically, not just selecting the values of some fields. In this * sense, it is more general than the joining capabilities of SQL. * * @param aRecord * @return the group key for the given record */ protected abstract String genGroupKey(Object key, OutputValue aRecord); /** * @param inputFile * @return true if the data from the supplied input file is smaller * than data from the other input file. */ protected abstract boolean isInputSmaller(String inputFile); public void map(Object key, Object value, OutputCollector output, Reporter reporter) throws IOException { if (this.reporter == null) { this.reporter = reporter; } addLongValue("totalCount", 1); OutputValue aRecord = genMapOutputValue(value); if (aRecord == null) { addLongValue("discardedCount", 1); return; } aRecord.setSmaller(smaller); String groupKey = genGroupKey(key, aRecord); if (groupKey == null) { addLongValue("nullGroupKeyCount", 1); return; } outputKey.setKey(groupKey); output.collect(outputKey, aRecord); addLongValue("collectedCount", 1); } public void close() throws IOException { if (this.reporter != null) { this.reporter.setStatus(super.getReport()); } } public void reduce(Object arg0, Iterator arg1, OutputCollector arg2, Reporter arg3) throws IOException { // TODO Auto-generated method stub } }