884
windows
多路输入输出示例__示例程序_MapReduce_大数据计算服务-阿里云
目前ODPS支持多表的输入及输出。
测试准备
(1)准备好测试程序jar包,假设名字为mapreduce-examples.jar;
(2)准备好多路输入输出的测试表和资源;
创建表
create table wc_in1(key string, value string);
create table wc_in2(key string, value string);
create table mr_multiinout_out1 (key string, cnt bigint);
create table mr_multiinout_out2 (key string, cnt bigint) partitioned by (a string, b string);
alter table mr_multiinout_out2 add partition (a='1', b='1');
alter table mr_multiinout_out2 add partition (a='2', b='2');
添加资源
add jar mapreduce-examples.jar -f;
(3)使用tunnel导入数据;
tunnel upload data1 wc_in1;
tunnel upload data2 wc_in2;
- 导入wc_in1表的数据文件data内容为:
hello,odps
- 导入wc_in2表的数据文件data内容为:
hello,world
测试步骤
在odpscmd中执行MultipleInOut
jar -resources mapreduce-examples.jar -classpath mapreduce-examples.jar
com.aliyun.odps.mapred.open.example.MultipleInOut wc_in1,wc_in2 mr_multiinout_out1,mr_multiinout_out2|a=1/b=1|out1,mr_multiinout_out2|a=2/b=2|out2;
预期结果
作业成功结束。mr_multiinout_out1中内容为:
+------------+------------+
| key | cnt |
+------------+------------+
| default | 1 |
+------------+------------+
mr_multiinout_out2中内容为:
+--------+------------+---+---+
| key | cnt | a | b |
+--------+------------+---+---+
| odps | 1 | 1 | 1 |
| world | 1 | 1 | 1 |
| out1 | 1 | 1 | 1 |
| hello | 2 | 2 | 2 |
| out2 | 1 | 2 | 2 |
+--------+------------+---+---+
代码示例
package com.aliyun.odps.mapred.open.example;
import java.io.IOException;
import java.util.Iterator;
import java.util.LinkedHashMap;
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.ReducerBase;
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;
/**
* Multi input & output example.
**/
public class MultipleInOut {
public static class TokenizerMapper extends MapperBase {
Record word;
Record one;
@Override
public void setup(TaskContext context) throws IOException {
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++) {
word.set(new Object[] { record.get(i).toString() });
context.write(word, one);
}
}
}
public static class SumReducer extends ReducerBase {
private Record result;
private Record result1;
private Record result2;
@Override
public void setup(TaskContext context) throws IOException {
result = context.createOutputRecord();
result1 = context.createOutputRecord("out1");
result2 = context.createOutputRecord("out2");
}
@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);
}
long mod = count % 3;
if (mod == 0) {
result.set(0, key.get(0));
result.set(1, count);
//不指定label,输出的默认(default)输出
context.write(result);
} else if (mod == 1) {
result1.set(0, key.get(0));
result1.set(1, count);
context.write(result1, "out1");
} else {
result2.set(0, key.get(0));
result2.set(1, count);
context.write(result2, "out2");
}
}
@Override
public void cleanup(TaskContext context) throws IOException {
Record result = context.createOutputRecord();
result.set(0, "default");
result.set(1, 1L);
context.write(result);
Record result1 = context.createOutputRecord("out1");
result1.set(0, "out1");
result1.set(1, 1L);
context.write(result1, "out1");
Record result2 = context.createOutputRecord("out2");
result2.set(0, "out2");
result2.set(1, 1L);
context.write(result2, "out2");
}
}
public static LinkedHashMap<String, String> convertPartSpecToMap(
String partSpec) {
LinkedHashMap<String, String> map = new LinkedHashMap<String, String>();
if (partSpec != null && !partSpec.trim().isEmpty()) {
String[] parts = partSpec.split("/");
for (String part : parts) {
String[] ss = part.split("=");
if (ss.length != 2) {
throw new RuntimeException("ODPS-0730001: error part spec format: "
+ partSpec);
}
map.put(ss[0], ss[1]);
}
}
return map;
}
public static void main(String[] args) throws Exception {
String[] inputs = null;
String[] outputs = null;
if (args.length == 2) {
inputs = args[0].split(",");
outputs = args[1].split(",");
} else {
System.err.println("MultipleInOut in... out...");
System.exit(1);
}
JobConf job = new JobConf();
job.setMapperClass(TokenizerMapper.class);
job.setReducerClass(SumReducer.class);
job.setMapOutputKeySchema(SchemaUtils.fromString("word:string"));
job.setMapOutputValueSchema(SchemaUtils.fromString("count:bigint"));
//解析用户的输入表字符串
for (String in : inputs) {
String[] ss = in.split("\|");
if (ss.length == 1) {
InputUtils.addTable(TableInfo.builder().tableName(ss[0]).build(), job);
} else if (ss.length == 2) {
LinkedHashMap<String, String> map = convertPartSpecToMap(ss[1]);
InputUtils.addTable(TableInfo.builder().tableName(ss[0]).partSpec(map).build(), job);
} else {
System.err.println("Style of input: " + in + " is not right");
System.exit(1);
}
}
//解析用户的输出表字符串
for (String out : outputs) {
String[] ss = out.split("\|");
if (ss.length == 1) {
OutputUtils.addTable(TableInfo.builder().tableName(ss[0]).build(), job);
} else if (ss.length == 2) {
LinkedHashMap<String, String> map = convertPartSpecToMap(ss[1]);
OutputUtils.addTable(TableInfo.builder().tableName(ss[0]).partSpec(map).build(), job);
} else if (ss.length == 3) {
if (ss[1].isEmpty()) {
LinkedHashMap<String, String> map = convertPartSpecToMap(ss[2]);
OutputUtils.addTable(TableInfo.builder().tableName(ss[0]).partSpec(map).build(), job);
} else {
LinkedHashMap<String, String> map = convertPartSpecToMap(ss[1]);
OutputUtils.addTable(TableInfo.builder().tableName(ss[0]).partSpec(map)
.label(ss[2]).build(), job);
}
} else {
System.err.println("Style of output: " + out + " is not right");
System.exit(1);
}
}
JobClient.runJob(job);
}
}
最后更新:2016-09-22 10:05:19
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