This topic describes an example of using Unique in MapReduce.
Preparations
- Prepare the JAR package of the test program. In this topic, the JAR package is named mapreduce-examples.jar and stored in the local path data\resources.
- Prepare test tables and resources for Unique.
- Create test tables.
create table ss_in(key bigint, value bigint); create table ss_out(key bigint, value bigint);
- Add test resources.
add jar data\resources\mapreduce-examples.jar -f;
- Create test tables.
- Use Tunnel to import data.
tunnel upload data ss_in;
The following data is imported to the ss_in table:1,1 1,1 2,2 2,2
Procedure
Run Unique on the MaxCompute client.
jar -resources mapreduce-examples.jar -classpath data\resources\mapreduce-examples.jar
com.aliyun.odps.mapred.open.example.Unique ss_in ss_out key;
Expected result
The job runs normally. The following data is returned in the ss_out table:
+------------+------------+
| key | value |
+------------+------------+
| 1 | 1 |
| 2 | 2 |
+------------+------------+
Sample code
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];
}
/** The input group of Reduce is determined by the value of the setOutputGroupingColumns parameter. If this parameter is not specified, the default value MapOutputKeySchema is used. */
// 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);
}
}
}