本文为您介绍MapReduce的Grep示例。
前提条件
已通过快速入门完成测试所需环境配置。
测试准备
准备好测试程序的JAR包,假设名字为mapreduce-examples.jar,本地存放路径为MaxCompute客户端bin目录下data\resources。
准备好Grep测试表和资源。
创建测试表。
CREATE TABLE mr_src(key STRING, value STRING); CREATE TABLE mr_grep_tmp (key STRING, cnt BIGINT); CREATE TABLE mr_grep_out (key BIGINT, value STRING);
添加测试资源。
-- 首次添加忽略-f覆盖指令。 add jar data\resources\mapreduce-examples.jar -f;
使用Tunnel将MaxCompute客户端bin目录下data.txt导入mr_src表中。
tunnel upload data.txt mr_src;
导入mr_src表的数据如下。
hello,odps hello,world
测试步骤
在MaxCompute客户端中执行Grep。
jar -resources mapreduce-examples.jar -classpath data\resources\mapreduce-examples.jar
com.aliyun.odps.mapred.open.example.Grep mr_src mr_grep_tmp mr_grep_out hello;
预期结果
作业成功结束后,输出表mr_grep_out中的内容如下。
+------------+------------+
| key | value |
+------------+------------+
| 2 | hello |
+------------+------------+
代码示例
Pom依赖信息,请参见注意事项。
package com.aliyun.odps.mapred.open.example;
import java.io.IOException;
import java.util.Iterator;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import com.aliyun.odps.data.Record;
import com.aliyun.odps.data.TableInfo;
import com.aliyun.odps.mapred.JobClient;
import com.aliyun.odps.mapred.Mapper;
import com.aliyun.odps.mapred.MapperBase;
import com.aliyun.odps.mapred.ReducerBase;
import com.aliyun.odps.mapred.RunningJob;
import com.aliyun.odps.mapred.TaskContext;
import com.aliyun.odps.mapred.conf.JobConf;
import com.aliyun.odps.mapred.utils.InputUtils;
import com.aliyun.odps.mapred.utils.OutputUtils;
import com.aliyun.odps.mapred.utils.SchemaUtils;
/**
*
* Extracts matching regexs from input files and counts them.
*
**/
public class Grep {
/**
* RegexMapper
**/
public static class RegexMapper extends MapperBase {
private Pattern pattern;
private int group;
private Record word;
private Record one;
@Override
public void setup(TaskContext context) throws IOException {
JobConf job = (JobConf) context.getJobConf();
pattern = Pattern.compile(job.get("mapred.mapper.regex"));
group = job.getInt("mapred.mapper.regex.group", 0);
word = context.createMapOutputKeyRecord();
one = context.createMapOutputValueRecord();
one.set(new Object[] { 1L });
}
@Override
public void map(long recordNum, Record record, TaskContext context) throws IOException {
for (int i = 0; i < record.getColumnCount(); ++i) {
String text = record.get(i).toString();
Matcher matcher = pattern.matcher(text);
while (matcher.find()) {
word.set(new Object[] { matcher.group(group) });
context.write(word, one);
}
}
}
}
/**
* LongSumReducer
**/
public static class LongSumReducer extends ReducerBase {
private Record result = null;
@Override
public void setup(TaskContext context) throws IOException {
result = context.createOutputRecord();
}
@Override
public void reduce(Record key, Iterator<Record> values, TaskContext context) throws IOException {
long count = 0;
while (values.hasNext()) {
Record val = values.next();
count += (Long) val.get(0);
}
result.set(0, key.get(0));
result.set(1, count);
context.write(result);
}
}
/**
* A {@link Mapper} that swaps keys and values.
**/
public static class InverseMapper extends MapperBase {
private Record word;
private Record count;
@Override
public void setup(TaskContext context) throws IOException {
word = context.createMapOutputValueRecord();
count = context.createMapOutputKeyRecord();
}
/**
* The inverse function. Input keys and values are swapped.
**/
@Override
public void map(long recordNum, Record record, TaskContext context) throws IOException {
word.set(new Object[] { record.get(0).toString() });
count.set(new Object[] { (Long) record.get(1) });
context.write(count, word);
}
}
/**
* IdentityReducer
**/
public static class IdentityReducer extends ReducerBase {
private Record result = null;
@Override
public void setup(TaskContext context) throws IOException {
result = context.createOutputRecord();
}
/** Writes all keys and values directly to output. **/
@Override
public void reduce(Record key, Iterator<Record> values, TaskContext context) throws IOException {
result.set(0, key.get(0));
while (values.hasNext()) {
Record val = values.next();
result.set(1, val.get(0));
context.write(result);
}
}
}
public static void main(String[] args) throws Exception {
if (args.length < 4) {
System.err.println("Grep <inDir> <tmpDir> <outDir> <regex> [<group>]");
System.exit(2);
}
JobConf grepJob = new JobConf();
grepJob.setMapperClass(RegexMapper.class);
grepJob.setReducerClass(LongSumReducer.class);
grepJob.setMapOutputKeySchema(SchemaUtils.fromString("word:string"));
grepJob.setMapOutputValueSchema(SchemaUtils.fromString("count:bigint"));
InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), grepJob);
OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), grepJob);
/**设置grepJob的grep的正则表达式。*/
grepJob.set("mapred.mapper.regex", args[3]);
if (args.length == 5) {
grepJob.set("mapred.mapper.regex.group", args[4]);
}
@SuppressWarnings("unused")
RunningJob rjGrep = JobClient.runJob(grepJob);
/**grepJob的输出作为sortJob的输入。*/
JobConf sortJob = new JobConf();
sortJob.setMapperClass(InverseMapper.class);
sortJob.setReducerClass(IdentityReducer.class);
sortJob.setMapOutputKeySchema(SchemaUtils.fromString("count:bigint"));
sortJob.setMapOutputValueSchema(SchemaUtils.fromString("word:string"));
InputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), sortJob);
OutputUtils.addTable(TableInfo.builder().tableName(args[2]).build(), sortJob);
sortJob.setNumReduceTasks(1); // write a single file
sortJob.setOutputKeySortColumns(new String[] { "count" });
@SuppressWarnings("unused")
RunningJob rjSort = JobClient.runJob(sortJob);
}
}
文档内容是否对您有帮助?