/** * 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.hadoop.contrib.utils.join; import java.io.IOException; import java.util.Iterator; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reporter; /** * This abstract class serves as the base class for the mapper class of a data * join job. This class expects its subclasses to implement methods for the * following functionalities: * * 1. Compute the source tag of input values 2. Compute the map output value * object 3. Compute the map output key object * * The source tag will be used by the reducer to determine from which source * (which table in SQL terminology) a value comes. Computing the map output * value object amounts to performing projecting/filtering work in a SQL * statement (through the select/where clauses). Computing the map output key * amounts to choosing the join key. This class provides the appropriate plugin * points for the user defined subclasses to implement the appropriate logic. * */ public abstract class DataJoinMapperBase extends JobBase { protected String inputFile = null; protected JobConf job = null; protected Text inputTag = null; protected Reporter reporter = null; public void configure(JobConf job) { super.configure(job); this.job = job; this.inputFile = job.get("map.input.file"); this.inputTag = generateInputTag(this.inputFile); } /** * 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 a tagged map 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 value * @return an object of TaggedMapOutput computed from the given value. */ protected abstract TaggedMapOutput generateTaggedMapOutput(Object value); /** * 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 Text generateGroupKey(TaggedMapOutput aRecord); public void map(Object key, Object value, OutputCollector output, Reporter reporter) throws IOException { if (this.reporter == null) { this.reporter = reporter; } addLongValue("totalCount", 1); TaggedMapOutput aRecord = generateTaggedMapOutput(value); if (aRecord == null) { addLongValue("discardedCount", 1); return; } Text groupKey = generateGroupKey(aRecord); if (groupKey == null) { addLongValue("nullGroupKeyCount", 1); return; } output.collect(groupKey, 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 } }