Unique示例
更新時(shí)間:
本文為您介紹MapReduce的Unique示例。
前提條件
已通過快速入門完成測試所需環(huán)境配置。
測試準(zhǔn)備
準(zhǔn)備好測試程序的JAR包,假設(shè)名字為mapreduce-examples.jar,本地存放路徑為MaxCompute客戶端bin目錄下data\resources。
準(zhǔn)備好Unique的測試表和資源。
創(chuàng)建測試表。
CREATE TABLE ss_in(key BIGINT, value BIGINT); CREATE TABLE ss_out(key BIGINT, value BIGINT);
添加測試資源。
-- 首次添加忽略-f覆蓋指令。 add jar data\resources\mapreduce-examples.jar -f;
使用Tunnel將MaxCompute客戶端bin目錄下data.txt導(dǎo)入ss_in表中。
tunnel upload data.txt ss_in;
導(dǎo)入ss_in表的數(shù)據(jù)文件data的內(nèi)容如下。
1,1 1,1 2,2 2,2
測試步驟
在MaxCompute客戶端中執(zhí)行Unique。
jar -resources mapreduce-examples.jar -classpath data\resources\mapreduce-examples.jar
com.aliyun.odps.mapred.open.example.Unique ss_in ss_out key;
預(yù)期結(jié)果
作業(yè)成功結(jié)束后,輸出表ss_out中的內(nèi)容如下。
+------------+------------+
| key | value |
+------------+------------+
| 1 | 1 |
| 2 | 2 |
+------------+------------+
代碼示例
Pom依賴信息,請參見注意事項(xiàng)。
package com.aliyun.odps.mapred.open.example;
import java.io.IOException;
import java.util.Iterator;
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;
/**
* Unique Remove duplicate words
*
**/
public class Unique {
public static class OutputSchemaMapper extends MapperBase {
private Record key;
private Record value;
@Override
public void setup(TaskContext context) throws IOException {
key = context.createMapOutputKeyRecord();
value = context.createMapOutputValueRecord();
}
@Override
public void map(long recordNum, Record record, TaskContext context)
throws IOException {
long left = 0;
long right = 0;
if (record.getColumnCount() > 0) {
left = (Long) record.get(0);
if (record.getColumnCount() > 1) {
right = (Long) record.get(1);
}
key.set(new Object[] { (Long) left, (Long) right });
value.set(new Object[] { (Long) left, (Long) right });
context.write(key, value);
}
}
}
public static class OutputSchemaReducer 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 {
result.set(0, key.get(0));
while (values.hasNext()) {
Record value = values.next();
result.set(1, value.get(1));
}
context.write(result);
}
}
public static void main(String[] args) throws Exception {
if (args.length > 3 || args.length < 2) {
System.err.println("Usage: unique <in> <out> [key|value|all]");
System.exit(2);
}
String ops = "all";
if (args.length == 3) {
ops = args[2];
}
/** Reduce的輸入分組是由setOutputGroupingColumns的設(shè)置來決定的,這個(gè)參數(shù)如果不設(shè)置,默認(rèn)就是MapOutputKeySchema。*/
// Key Unique
if (ops.equals("key")) {
JobConf job = new JobConf();
job.setMapperClass(OutputSchemaMapper.class);
job.setReducerClass(OutputSchemaReducer.class);
job.setMapOutputKeySchema(SchemaUtils.fromString("key:bigint,value:bigint"));
job.setMapOutputValueSchema(SchemaUtils.fromString("key:bigint,value:bigint"));
job.setPartitionColumns(new String[] { "key" });
job.setOutputKeySortColumns(new String[] { "key", "value" });
job.setOutputGroupingColumns(new String[] { "key" });
job.set("tablename2", args[1]);
job.setNumReduceTasks(1);
job.setInt("table.counter", 0);
InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
JobClient.runJob(job);
}
// Key&Value Unique
if (ops.equals("all")) {
JobConf job = new JobConf();
job.setMapperClass(OutputSchemaMapper.class);
job.setReducerClass(OutputSchemaReducer.class);
job.setMapOutputKeySchema(SchemaUtils.fromString("key:bigint,value:bigint"));
job.setMapOutputValueSchema(SchemaUtils.fromString("key:bigint,value:bigint"));
job.setPartitionColumns(new String[] { "key" });
job.setOutputKeySortColumns(new String[] { "key", "value" });
job.setOutputGroupingColumns(new String[] { "key", "value" });
job.set("tablename2", args[1]);
job.setNumReduceTasks(1);
job.setInt("table.counter", 0);
InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
JobClient.runJob(job);
}
// Value Unique
if (ops.equals("value")) {
JobConf job = new JobConf();
job.setMapperClass(OutputSchemaMapper.class);
job.setReducerClass(OutputSchemaReducer.class);
job.setMapOutputKeySchema(SchemaUtils.fromString("key:bigint,value:bigint"));
job.setMapOutputValueSchema(SchemaUtils.fromString("key:bigint,value:bigint"));
job.setPartitionColumns(new String[] { "value" });
job.setOutputKeySortColumns(new String[] { "value" });
job.setOutputGroupingColumns(new String[] { "value" });
job.set("tablename2", args[1]);
job.setNumReduceTasks(1);
job.setInt("table.counter", 0);
InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
JobClient.runJob(job);
}
}
}
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