HBASE-1850 src/examples/mapred do not compile after HBASE-1822
git-svn-id: https://svn.apache.org/repos/asf/hadoop/hbase/trunk@816323 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Jonathan Gray
parent
4f294977d2
commit
dfd1091da5
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@ -33,6 +33,7 @@ Release 0.21.0 - Unreleased
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for when Writable is not Configurable (Stack via jgray)
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HBASE-1847 Delete latest of a null qualifier when non-null qualifiers
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exist throws a RuntimeException
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HBASE-1850 src/examples/mapred do not compile after HBASE-1822
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IMPROVEMENTS
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HBASE-1760 Cleanup TODOs in HTable
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@ -1,139 +1,148 @@
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/**
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* Copyright 2009 The Apache Software Foundation
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*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.hadoop.hbase.mapred;
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import java.io.IOException;
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import java.util.Iterator;
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import java.util.Map.Entry;
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import org.apache.hadoop.conf.Configuration;
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import org.apache.hadoop.fs.Path;
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import org.apache.hadoop.hbase.io.BatchUpdate;
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import org.apache.hadoop.hbase.io.HbaseMapWritable;
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import org.apache.hadoop.hbase.HBaseConfiguration;
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import org.apache.hadoop.hbase.client.Put;
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import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
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import org.apache.hadoop.hbase.mapred.TableMapReduceUtil;
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import org.apache.hadoop.hbase.mapred.TableReduce;
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import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
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import org.apache.hadoop.hbase.util.Bytes;
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import org.apache.hadoop.io.LongWritable;
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import org.apache.hadoop.io.Text;
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import org.apache.hadoop.mapred.FileInputFormat;
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import org.apache.hadoop.mapred.JobClient;
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import org.apache.hadoop.mapred.JobConf;
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import org.apache.hadoop.mapred.MapReduceBase;
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import org.apache.hadoop.mapred.Mapper;
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import org.apache.hadoop.mapred.OutputCollector;
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import org.apache.hadoop.mapred.Reporter;
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import org.apache.hadoop.util.Tool;
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import org.apache.hadoop.util.ToolRunner;
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import org.apache.hadoop.mapreduce.Job;
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import org.apache.hadoop.mapreduce.Mapper;
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import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
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import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
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import org.apache.hadoop.util.GenericOptionsParser;
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/*
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* Sample uploader.
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*
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/**
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* Sample Uploader MapReduce
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* <p>
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* This is EXAMPLE code. You will need to change it to work for your context.
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*
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* Uses TableReduce to put the data into hbase. Change the InputFormat to suit
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* your data. Use the map to massage the input so it fits hbase. Currently its
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* just a pass-through map. In the reduce, you need to output a row and a
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* map of columns to cells. Change map and reduce to suit your input.
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*
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* <p>The below is wired up to handle an input whose format is a text file
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* which has a line format as follow:
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* <pre>
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* row columnname columndata
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* </pre>
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*
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* <p>The table and columnfamily we're to insert into must preexist.
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*
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* <p>
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* Uses {@link TableReducer} to put the data into HBase. Change the InputFormat
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* to suit your data. In this example, we are importing a CSV file.
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* <p>
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* <pre>row,family,qualifier,value</pre>
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* <p>
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* The table and columnfamily we're to insert into must preexist.
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* <p>
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* There is no reducer in this example as it is not necessary and adds
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* significant overhead. If you need to do any massaging of data before
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* inserting into HBase, you can do this in the map as well.
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* <p>Do the following to start the MR job:
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* <pre>
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* ./bin/hadoop org.apache.hadoop.hbase.mapred.SampleUploader /tmp/input.txt TABLE_NAME
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* ./bin/hadoop org.apache.hadoop.hbase.mapreduce.SampleUploader /tmp/input.csv TABLE_NAME
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* </pre>
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*
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* <p>This code was written against hbase 0.1 branch.
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* <p>
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* This code was written against HBase 0.21 trunk.
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*/
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public class SampleUploader extends MapReduceBase
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implements Mapper<LongWritable, Text, ImmutableBytesWritable, HbaseMapWritable<byte [], byte []>>,
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Tool {
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public class SampleUploader {
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private static final String NAME = "SampleUploader";
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private Configuration conf;
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static class Uploader
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extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {
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public JobConf createSubmittableJob(String[] args)
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throws IOException {
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JobConf c = new JobConf(getConf(), SampleUploader.class);
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c.setJobName(NAME);
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FileInputFormat.setInputPaths(c, new Path(args[0]));
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c.setMapperClass(this.getClass());
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c.setMapOutputKeyClass(ImmutableBytesWritable.class);
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c.setMapOutputValueClass(HbaseMapWritable.class);
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c.setReducerClass(TableUploader.class);
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TableMapReduceUtil.initTableReduceJob(args[1], TableUploader.class, c);
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return c;
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}
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public void map(LongWritable k, Text v,
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OutputCollector<ImmutableBytesWritable, HbaseMapWritable<byte [], byte []>> output,
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Reporter r)
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throws IOException {
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// Lines are space-delimited; first item is row, next the columnname and
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// then the third the cell value.
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String tmp = v.toString();
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if (tmp.length() == 0) {
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return;
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}
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String [] splits = v.toString().split(" ");
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HbaseMapWritable<byte [], byte []> mw =
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new HbaseMapWritable<byte [], byte []>();
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mw.put(Bytes.toBytes(splits[1]), Bytes.toBytes(splits[2]));
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byte [] row = Bytes.toBytes(splits[0]);
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r.setStatus("Map emitting " + splits[0] + " for record " + k.toString());
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output.collect(new ImmutableBytesWritable(row), mw);
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}
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public static class TableUploader extends MapReduceBase
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implements TableReduce<ImmutableBytesWritable, HbaseMapWritable<byte [], byte []>> {
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public void reduce(ImmutableBytesWritable k, Iterator<HbaseMapWritable<byte [], byte []>> v,
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OutputCollector<ImmutableBytesWritable, BatchUpdate> output,
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Reporter r)
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private long checkpoint = 100;
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private long count = 0;
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@Override
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public void map(LongWritable key, Text line, Context context)
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throws IOException {
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while (v.hasNext()) {
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r.setStatus("Reducer committing " + k);
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BatchUpdate bu = new BatchUpdate(k.get());
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while (v.hasNext()) {
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HbaseMapWritable<byte [], byte []> hmw = v.next();
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for (Entry<byte [], byte []> e: hmw.entrySet()) {
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bu.put(e.getKey(), e.getValue());
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}
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}
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output.collect(k, bu);
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// Input is a CSV file
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// Each map() is a single line, where the key is the line number
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// Each line is comma-delimited; row,family,qualifier,value
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// Split CSV line
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String [] values = line.toString().split(",");
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if(values.length != 4) {
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return;
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}
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// Extract each value
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byte [] row = Bytes.toBytes(values[0]);
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byte [] family = Bytes.toBytes(values[1]);
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byte [] qualifier = Bytes.toBytes(values[2]);
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byte [] value = Bytes.toBytes(values[3]);
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// Create Put
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Put put = new Put(row);
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put.add(family, qualifier, value);
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// Uncomment below to disable WAL. This will improve performance but means
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// you will experience data loss in the case of a RegionServer crash.
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// put.setWriteToWAL(false);
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try {
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context.write(new ImmutableBytesWritable(row), put);
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} catch (InterruptedException e) {
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e.printStackTrace();
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}
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// Set status every checkpoint lines
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if(++count % checkpoint == 0) {
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context.setStatus("Emitting Put " + count);
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}
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}
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}
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static int printUsage() {
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System.out.println(NAME + " <input> <table_name>");
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return -1;
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}
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public int run(@SuppressWarnings("unused") String[] args) throws Exception {
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// Make sure there are exactly 2 parameters left.
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if (args.length != 2) {
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System.out.println("ERROR: Wrong number of parameters: " +
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args.length + " instead of 2.");
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return printUsage();
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}
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JobClient.runJob(createSubmittableJob(args));
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return 0;
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}
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public Configuration getConf() {
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return this.conf;
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}
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public void setConf(final Configuration c) {
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this.conf = c;
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/**
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* Job configuration.
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*/
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public static Job configureJob(Configuration conf, String [] args)
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throws IOException {
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Path inputPath = new Path(args[0]);
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String tableName = args[1];
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Job job = new Job(conf, NAME + "_" + tableName);
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job.setJarByClass(Uploader.class);
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FileInputFormat.setInputPaths(job, inputPath);
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job.setInputFormatClass(SequenceFileInputFormat.class);
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job.setMapperClass(Uploader.class);
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// No reducers. Just write straight to table. Call initTableReducerJob
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// because it sets up the TableOutputFormat.
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TableMapReduceUtil.initTableReducerJob(tableName, null, job);
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job.setNumReduceTasks(0);
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return job;
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}
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/**
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* Main entry point.
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*
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* @param args The command line parameters.
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* @throws Exception When running the job fails.
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*/
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public static void main(String[] args) throws Exception {
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int errCode = ToolRunner.run(new Configuration(), new SampleUploader(),
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args);
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System.exit(errCode);
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HBaseConfiguration conf = new HBaseConfiguration();
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String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
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if(otherArgs.length != 2) {
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System.err.println("Wrong number of arguments: " + otherArgs.length);
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System.err.println("Usage: " + NAME + " <input> <tablename>");
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System.exit(-1);
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}
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Job job = configureJob(conf, otherArgs);
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System.exit(job.waitForCompletion(true) ? 0 : 1);
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}
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}
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