cn.lhfei.hbase.ch04.SampleUploader.java Source code

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/*
 * Copyright 2010-2014 the original author or authors.
 *
 * Licensed 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 cn.lhfei.hbase.ch04;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

import cn.lhfei.hbase.basic.AppConfig;

/**
 * Sample Uploader MapReduce
 * <p>
 * This is EXAMPLE code. You will need to change it to work for your context.
 * <p>
 * Uses {@link TableReducer} to put the data into HBase. Change the InputFormat
 * to suit your data. In this example, we are importing a CSV file.
 * <p>
 * 
 * <pre>
 * row,family,qualifier,value
 * </pre>
 * <p>
 * The table and columnfamily we're to insert into must preexist.
 * <p>
 * There is no reducer in this example as it is not necessary and adds
 * significant overhead. If you need to do any massaging of data before
 * inserting into HBase, you can do this in the map as well.
 * <p>
 * Do the following to start the MR job:
 * 
 * <pre>
 * ./bin/hadoop org.apache.hadoop.hbase.mapreduce.SampleUploader /tmp/input.csv TABLE_NAME
 * </pre>
 * <p>
 * This code was written against HBase 0.21 trunk.
 * 
 * @version 0.1
 *
 * @author Hefei Li
 *
 * @since Jun 14, 2016
 */
public class SampleUploader extends Configured implements Tool {

    private static final String NAME = "SampleUploader";

    static class Uploader extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {

        private long checkpoint = 100;
        private long count = 0;

        @Override
        public void map(LongWritable key, Text line, Context context) throws IOException {

            // Input is a CSV file
            // Each map() is a single line, where the key is the line number
            // Each line is comma-delimited; row,family,qualifier,value

            // Split CSV line
            String[] values = line.toString().split(",");
            if (values.length != 4) {
                return;
            }

            // Extract each value
            byte[] row = Bytes.toBytes(values[0]);
            byte[] family = Bytes.toBytes(values[1]);
            byte[] qualifier = Bytes.toBytes(values[2]);
            byte[] value = Bytes.toBytes(values[3]);

            // Create Put
            Put put = new Put(row);
            put.addColumn(family, qualifier, value);

            // Uncomment below to disable WAL. This will improve performance but
            // means
            // you will experience data loss in the case of a RegionServer
            // crash.
            // put.setWriteToWAL(false);

            try {
                context.write(new ImmutableBytesWritable(row), put);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }

            // Set status every checkpoint lines
            if (++count % checkpoint == 0) {
                context.setStatus("Emitting Put " + count);
            }
        }
    }

    /**
     * Job configuration.
     */
    public static Job configureJob(Configuration conf, String[] args) throws IOException {
        Path inputPath = new Path(args[0]);
        String tableName = args[1];
        //Job job = new Job(conf, NAME + "_" + tableName);

        Job job = Job.getInstance(conf);

        //job.setJarByClass(Uploader.class);
        FileInputFormat.setInputPaths(job, inputPath);
        job.setInputFormatClass(SequenceFileInputFormat.class);
        job.setMapperClass(Uploader.class);
        // No reducers. Just write straight to table. Call initTableReducerJob
        // because it sets up the TableOutputFormat.
        TableMapReduceUtil.initTableReducerJob(tableName, null, job);
        job.setNumReduceTasks(0);
        return job;
    }

    /**
     * Main entry point.
     *
     * @param otherArgs
     *            The command line parameters after ToolRunner handles standard.
     * @throws Exception
     *             When running the job fails.
     */
    public int run(String[] otherArgs) throws Exception {
        if (otherArgs.length != 2) {
            System.err.println("Wrong number of arguments: " + otherArgs.length);
            System.err.println("Usage: " + NAME + " <input> <tablename>");
            return -1;
        }
        //Job job = configureJob(getConf(), otherArgs);
        Job job = configureJob(AppConfig.getConfiguration(), otherArgs);
        return (job.waitForCompletion(true) ? 0 : 1);
    }

    public static void main(String[] args) throws Exception {
        //      int status = ToolRunner.run(HBaseConfiguration.create(), new SampleUploader(), args);
        args = new String[] { "/user/lhfei/test-data.txt", "jsontable" };
        int status = ToolRunner.run(AppConfig.getConfiguration(), new SampleUploader(), args);

        System.exit(status);
    }
}