/*
* 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 com.aliyun.odps.mapred.local;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.Iterator;
import org.junit.Before;
import org.junit.Test;
import com.aliyun.odps.data.Record;
import com.aliyun.odps.data.TableInfo;
import com.aliyun.odps.mapred.JobClient;
import com.aliyun.odps.mapred.MapperBase;
import com.aliyun.odps.mapred.conf.JobConf;
import com.aliyun.odps.mapred.local.utils.TestUtils;
import com.aliyun.odps.mapred.utils.InputUtils;
import com.aliyun.odps.mapred.utils.OutputUtils;
/**
* This is an example ODPS Map/Reduce application. It reads the input table, map
* each column into words and counts them. The output is a locally sorted list
* of words and the count of how often they occurred.
* <p>
* To run: jar -libjars mapreduce-examples.jar -classpath
* clt/lib/mapreduce-examples.jar com.aliyun.odps.mapreduce.examples.WordCount
* <i>in-tbl</i> <i>out-tbl</i>
*/
public class Resource {
@Before
public void setUp() throws Exception {
TestUtils.setEnvironment(TestUtils.odps_test_mrtask);
}
/**
* Counts the words in each record. For each record, emit each column as
* (<b>word</b>, <b>1</b>).
*/
public static class TokenizerMapper extends MapperBase {
Record result;
@Override
public void setup(TaskContext context) throws IOException {
result = context.createOutputRecord();
InputStream in = context.readResourceFileAsStream("file_resource.txt");
BufferedReader br = new BufferedReader(new InputStreamReader(in));
String line;
long count = 0;
while ((line = br.readLine()) != null) {
count++;
}
br.close();
result.set(0, "file_resource");
result.set(1, count);
context.write(result);
Iterator<Record> iterator = context.readResourceTable("table_resource1");
count = 0;
while (iterator.hasNext()) {
count++;
iterator.next();
}
result.set(0, "table_resource1");
result.set(1, count);
context.write(result);
iterator = context.readResourceTable("table_resource2");
count = 0;
while (iterator.hasNext()) {
count++;
iterator.next();
}
result.set(0, "table_resource2");
result.set(1, count);
context.write(result);
}
@Override
public void map(long recordNum, Record record, TaskContext context) throws IOException {
}
}
@Test
public void test() throws Exception {
String[] args = new String[2];
args[0] = "grep_in";
args[1] = "resource_out";
JobConf job = new JobConf();
job.setMapperClass(TokenizerMapper.class);
job.setNumReduceTasks(0);
job.setResources("file_resource.txt");
InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
JobClient.runJob(job);
}
}