/**
* 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.zebra.mapred;
import java.io.IOException;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.zebra.mapred.BasicTableOutputFormat;
import org.apache.hadoop.zebra.types.ParseException;
import org.apache.hadoop.zebra.types.Schema;
import org.apache.hadoop.zebra.types.TypesUtils;
import org.apache.pig.data.Tuple;
/**
* This is a sample a complete MR sample code for Table. It doens't contain
* 'read' part. But, it should be similar and easier to write. Refer to test
* cases in the same directory.
*
* Assume the input files contain rows of word and count, separated by a space:
*
* <pre>
* this 2
* is 1
* a 4
* test 2
* hello 1
* world 3
* </pre>
*
*/
public class TableMRSample1 {
static class MapClass implements
Mapper<LongWritable, Text, BytesWritable, Tuple> {
private BytesWritable bytesKey;
private Tuple tupleRow;
@Override
public void map(LongWritable key, Text value,
OutputCollector<BytesWritable, Tuple> output, Reporter reporter)
throws IOException {
// value should contain "word count"
String[] wdct = value.toString().split(" ");
if (wdct.length != 2) {
// LOG the error
throw new IOException("Does not contain two fields");
}
byte[] word = wdct[0].getBytes();
bytesKey.set(word, 0, word.length);
tupleRow.set(0, new String(word));
tupleRow.set(1, Integer.parseInt(wdct[1]));
output.collect(bytesKey, tupleRow);
}
@Override
public void configure(JobConf job) {
bytesKey = new BytesWritable();
try {
Schema outSchema = BasicTableOutputFormat.getSchema(job);
tupleRow = TypesUtils.createTuple(outSchema);
} catch (IOException e) {
throw new RuntimeException(e);
} catch (ParseException e) {
throw new RuntimeException(e);
}
}
@Override
public void close() throws IOException {
// no-op
}
}
public static void main(String[] args) throws ParseException, IOException {
JobConf jobConf = new JobConf();
jobConf.setJobName("tableMRSample");
jobConf.set("table.output.tfile.compression", "gz");
// input settings
jobConf.setInputFormat(TextInputFormat.class);
jobConf.setMapperClass(TableMRSample1.MapClass.class);
FileInputFormat.setInputPaths(jobConf, new Path("/user/joe/input.txt"));
jobConf.setNumMapTasks(2);
// output settings
Path outPath = new Path("/user/joe/tableout");
jobConf.setOutputFormat(BasicTableOutputFormat.class);
BasicTableOutputFormat.setOutputPath(jobConf, outPath);
// set the logical schema with 2 columns
BasicTableOutputFormat.setSchema(jobConf, "word:string, count:int");
// for demo purposes, create 2 physical column groups
BasicTableOutputFormat.setStorageHint(jobConf, "[word];[count]");
// set map-only job.
jobConf.setNumReduceTasks(0);
JobClient.runJob(jobConf);
}
}