001/**
002 *
003 * Licensed to the Apache Software Foundation (ASF) under one
004 * or more contributor license agreements.  See the NOTICE file
005 * distributed with this work for additional information
006 * regarding copyright ownership.  The ASF licenses this file
007 * to you under the Apache License, Version 2.0 (the
008 * "License"); you may not use this file except in compliance
009 * with the License.  You may obtain a copy of the License at
010 *
011 *     http://www.apache.org/licenses/LICENSE-2.0
012 *
013 * Unless required by applicable law or agreed to in writing, software
014 * distributed under the License is distributed on an "AS IS" BASIS,
015 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
016 * See the License for the specific language governing permissions and
017 * limitations under the License.
018 */
019package org.apache.hadoop.hbase.mapreduce;
020
021import java.io.IOException;
022import org.apache.hadoop.conf.Configuration;
023import org.apache.hadoop.conf.Configured;
024import org.apache.hadoop.fs.Path;
025import org.apache.hadoop.hbase.HBaseConfiguration;
026import org.apache.hadoop.hbase.client.Put;
027import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
028import org.apache.hadoop.hbase.util.Bytes;
029import org.apache.hadoop.io.LongWritable;
030import org.apache.hadoop.io.Text;
031import org.apache.hadoop.mapreduce.Job;
032import org.apache.hadoop.mapreduce.Mapper;
033import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
034import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
035import org.apache.hadoop.util.Tool;
036import org.apache.hadoop.util.ToolRunner;
037import org.apache.yetus.audience.InterfaceAudience;
038
039/**
040 * Sample Uploader MapReduce
041 * <p>
042 * This is EXAMPLE code.  You will need to change it to work for your context.
043 * <p>
044 * Uses {@link TableReducer} to put the data into HBase. Change the InputFormat
045 * to suit your data.  In this example, we are importing a CSV file.
046 * <p>
047 * <pre>row,family,qualifier,value</pre>
048 * <p>
049 * The table and columnfamily we're to insert into must preexist.
050 * <p>
051 * There is no reducer in this example as it is not necessary and adds
052 * significant overhead.  If you need to do any massaging of data before
053 * inserting into HBase, you can do this in the map as well.
054 * <p>Do the following to start the MR job:
055 * <pre>
056 * ./bin/hadoop org.apache.hadoop.hbase.mapreduce.SampleUploader /tmp/input.csv TABLE_NAME
057 * </pre>
058 * <p>
059 * This code was written against HBase 0.21 trunk.
060 */
061@InterfaceAudience.Private
062public class SampleUploader extends Configured implements Tool {
063
064  private static final String NAME = "SampleUploader";
065
066  static class Uploader
067  extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {
068
069    private long checkpoint = 100;
070    private long count = 0;
071
072    @Override
073    public void map(LongWritable key, Text line, Context context)
074    throws IOException {
075
076      // Input is a CSV file
077      // Each map() is a single line, where the key is the line number
078      // Each line is comma-delimited; row,family,qualifier,value
079
080      // Split CSV line
081      String [] values = line.toString().split(",");
082      if(values.length != 4) {
083        return;
084      }
085
086      // Extract each value
087      byte [] row = Bytes.toBytes(values[0]);
088      byte [] family = Bytes.toBytes(values[1]);
089      byte [] qualifier = Bytes.toBytes(values[2]);
090      byte [] value = Bytes.toBytes(values[3]);
091
092      // Create Put
093      Put put = new Put(row);
094      put.addColumn(family, qualifier, value);
095
096      // Uncomment below to disable WAL. This will improve performance but means
097      // you will experience data loss in the case of a RegionServer crash.
098      // put.setWriteToWAL(false);
099
100      try {
101        context.write(new ImmutableBytesWritable(row), put);
102      } catch (InterruptedException e) {
103        e.printStackTrace();
104      }
105
106      // Set status every checkpoint lines
107      if(++count % checkpoint == 0) {
108        context.setStatus("Emitting Put " + count);
109      }
110    }
111  }
112
113  /**
114   * Job configuration.
115   */
116  public static Job configureJob(Configuration conf, String [] args)
117  throws IOException {
118    Path inputPath = new Path(args[0]);
119    String tableName = args[1];
120    Job job = new Job(conf, NAME + "_" + tableName);
121    job.setJarByClass(Uploader.class);
122    FileInputFormat.setInputPaths(job, inputPath);
123    job.setInputFormatClass(SequenceFileInputFormat.class);
124    job.setMapperClass(Uploader.class);
125    // No reducers.  Just write straight to table.  Call initTableReducerJob
126    // because it sets up the TableOutputFormat.
127    TableMapReduceUtil.initTableReducerJob(tableName, null, job);
128    job.setNumReduceTasks(0);
129    return job;
130  }
131
132  /**
133   * Main entry point.
134   *
135   * @param otherArgs  The command line parameters after ToolRunner handles standard.
136   * @throws Exception When running the job fails.
137   */
138  public int run(String[] otherArgs) throws Exception {
139    if(otherArgs.length != 2) {
140      System.err.println("Wrong number of arguments: " + otherArgs.length);
141      System.err.println("Usage: " + NAME + " <input> <tablename>");
142      return -1;
143    }
144    Job job = configureJob(getConf(), otherArgs);
145    return (job.waitForCompletion(true) ? 0 : 1);
146  }
147
148  public static void main(String[] args) throws Exception {
149    int status = ToolRunner.run(HBaseConfiguration.create(), new SampleUploader(), args);
150    System.exit(status);
151  }
152}