Flink数据重分区操作

重分区操作，在DataStream类中可以看到很多Partitioner字眼的类。

其中partitionCustom(...)方法用于自定义重分区。

java代码：

package apitest.transform;

import apitest.beans.SensorReading;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

public class TransformTest6_Partition {
  public static void main(String[] args) throws Exception{

    // 创建执行环境
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

    // 设置并行度 = 4
    env.setParallelism(4);

    // 从文件读取数据
    DataStream inputStream = env.readTextFile("F:\JAVA\bigdata2107\zch\flink\src\main\resources\Sensor.txt");

    // 转换成SensorReading类型
    DataStream dataStream = inputStream.map(line -> {
      String[] fields = line.split(",");
      return new SensorReading(fields[0], new Long(fields[1]), new Double(fields[2]));
    });

    // SingleOutputStreamOperator多并行度默认就rebalance,轮询方式分配
    dataStream.print("input");

    // 1. shuffle (并非批处理中的获取一批后才打乱，这里每次获取到直接打乱且分区)
    DataStream shuffleStream = inputStream.shuffle();
    shuffleStream.print("shuffle");

    // 2. keyBy (Hash，然后取模)
    dataStream.keyBy(SensorReading::getId).print("keyBy");

    // 3. global (直接发送给第一个分区，少数特殊情况才用)
    dataStream.global().print("global");

    env.execute();
  }
}

输出：

input:3> SensorReading{id='sensor_1', timestamp=1547718199, temperature=35.8}
input:3> SensorReading{id='sensor_6', timestamp=1547718201, temperature=15.4}
input:1> SensorReading{id='sensor_1', timestamp=1547718207, temperature=36.3}
input:1> SensorReading{id='sensor_1', timestamp=1547718209, temperature=32.8}
shuffle:2> sensor_6,1547718201,15.4
shuffle:1> sensor_1,1547718199,35.8
input:4> SensorReading{id='sensor_7', timestamp=1547718202, temperature=6.7}
input:4> SensorReading{id='sensor_10', timestamp=1547718205, temperature=38.1}
shuffle:1> sensor_1,1547718207,36.3
shuffle:2> sensor_1,1547718209,32.8
global:1> SensorReading{id='sensor_1', timestamp=1547718199, temperature=35.8}
keyBy:3> SensorReading{id='sensor_1', timestamp=1547718199, temperature=35.8}
global:1> SensorReading{id='sensor_6', timestamp=1547718201, temperature=15.4}
keyBy:3> SensorReading{id='sensor_6', timestamp=1547718201, temperature=15.4}
keyBy:3> SensorReading{id='sensor_1', timestamp=1547718207, temperature=36.3}
keyBy:3> SensorReading{id='sensor_1', timestamp=1547718209, temperature=32.8}
global:1> SensorReading{id='sensor_1', timestamp=1547718207, temperature=36.3}
shuffle:1> sensor_7,1547718202,6.7
global:1> SensorReading{id='sensor_1', timestamp=1547718209, temperature=32.8}
shuffle:2> sensor_10,1547718205,38.1
input:2> SensorReading{id='sensor_1', timestamp=1547718212, temperature=37.1}
global:1> SensorReading{id='sensor_7', timestamp=1547718202, temperature=6.7}
keyBy:4> SensorReading{id='sensor_7', timestamp=1547718202, temperature=6.7}
keyBy:2> SensorReading{id='sensor_10', timestamp=1547718205, temperature=38.1}
global:1> SensorReading{id='sensor_10', timestamp=1547718205, temperature=38.1}
shuffle:1> sensor_1,1547718212,37.1
keyBy:3> SensorReading{id='sensor_1', timestamp=1547718212, temperature=37.1}
global:1> SensorReading{id='sensor_1', timestamp=1547718212, temperature=37.1}