在Apache Flink中对两个消息流使用相同的接收器

Question

我们有两种消息向Flink传来

1. 控制消息->仅滚动文件
2. 数据消息->将使用接收器存储在S3中

package com.ranjit.com.flinkdemo;

import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.fs.DateTimeBucketer;
import org.apache.flink.streaming.connectors.fs.RollingSink;

import org.apache.flink.streaming.connectors.fs.StringWriter;;

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

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(2);

        DataStream<String> ctrl_message_stream = env.socketTextStream("localhost", 8088);

        ctrl_message_stream.broadcast();

        DataStream<String> message_stream = env.socketTextStream("localhost", 8087);

        RollingSink sink = new RollingSink<String>("/base/path");
        sink.setBucketer(new DateTimeBucketer("yyyy-MM-dd--HHmm"));
        sink.setWriter(new StringWriter<String>() );
        sink.setBatchSize(1024 * 1024 * 400); // this is 400 MB,

        ctrl_message_stream.broadcast().addSink(sink);
        message_stream.addSink(sink);

        env.execute("stream");
    }

}

package com.gslab.com.dataSets;
import java.io.File;
import java.util.ArrayList;
import java.util.List;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericData.Record;
import org.apache.avro.generic.GenericRecord;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

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

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(2);

        List<String> controlMessageList = new ArrayList<String>();
        controlMessageList.add("controlMessage1");
        controlMessageList.add("controlMessage2");

        List<String> dataMessageList = new ArrayList<String>();
        dataMessageList.add("Person1");
        dataMessageList.add("Person2");
        dataMessageList.add("Person3");
        dataMessageList.add("Person4");

        DataStream<String> controlMessageStream  = env.fromCollection(controlMessageList);
        DataStream<String> dataMessageStream  = env.fromCollection(dataMessageList);

        DataStream<GenericRecord> controlMessageGenericRecordStream = controlMessageStream.map(new MapFunction<String, GenericRecord>() {
            @Override
            public GenericRecord map(String value) throws Exception {
                 Record gr = new GenericData.Record(new Schema.Parser().parse(new File("src/main/resources/controlMessageSchema.avsc")));
                 gr.put("TYPE", value);
                 return gr;
            }
        });

        DataStream<GenericRecord> dataMessageGenericRecordStream = dataMessageStream.map(new MapFunction<String, GenericRecord>() {
            @Override
            public GenericRecord map(String value) throws Exception {
                 Record gr = new GenericData.Record(new Schema.Parser().parse(new File("src/main/resources/dataMessageSchema.avsc")));
                 gr.put("FIRSTNAME", value);
                 gr.put("LASTNAME", value+": lastname");
                 return gr;
            }
        });

        //Displaying Generic records
        dataMessageGenericRecordStream.map(new MapFunction<GenericRecord, GenericRecord>() {
            @Override
            public GenericRecord map(GenericRecord value) throws Exception {
                System.out.println("data before union: "+ value);
                return value;
            }
        });

        controlMessageGenericRecordStream.broadcast().union(dataMessageGenericRecordStream).map(new MapFunction<GenericRecord, GenericRecord>() {
            @Override
            public GenericRecord map(GenericRecord value) throws Exception {
                System.out.println("data after union: " + value);
                return value;
            }
        });
        env.execute("stream");
    }
}

05/09/2016 13:02:12 Source: Collection Source(1/1) switched to FINISHED 
05/09/2016 13:02:12 Source: Collection Source(1/1) switched to FINISHED 
05/09/2016 13:02:13 Map(1/2) switched to FINISHED 
05/09/2016 13:02:13 Map(2/2) switched to FINISHED 
data after union: {"TYPE": "controlMessage1"}
data before union: {"FIRSTNAME": "Person2", "LASTNAME": "Person2: lastname"}
data after union: {"TYPE": "controlMessage1"}
data before union: {"FIRSTNAME": "Person1", "LASTNAME": "Person1: lastname"}
data after union: {"TYPE": "controlMessage2"}
data after union: {"TYPE": "controlMessage2"}
data after union: {"FIRSTNAME": "Person1", "LASTNAME": "Person1"}
data before union: {"FIRSTNAME": "Person4", "LASTNAME": "Person4: lastname"}
data before union: {"FIRSTNAME": "Person3", "LASTNAME": "Person3: lastname"}
data after union: {"FIRSTNAME": "Person2", "LASTNAME": "Person2"}
data after union: {"FIRSTNAME": "Person3", "LASTNAME": "Person3"}
05/09/2016 13:02:13 Map -> Map(2/2) switched to FINISHED 
data after union: {"FIRSTNAME": "Person4", "LASTNAME": "Person4"}
05/09/2016 13:02:13 Map -> Map(1/2) switched to FINISHED 
05/09/2016 13:02:13 Map(1/2) switched to FINISHED 
05/09/2016 13:02:13 Map(2/2) switched to FINISHED 
05/09/2016 13:02:13 Job execution switched to status FINISHED.

我们可以看到LASTNAME值不正确，它会被每个记录的FIRSTNAME值替换

Answer 1

您的代码基本上用您定义的接收器的副本终止这两个流。你想要的是这样的东西：

java prettyprint-override">final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(2);

DataStream<String> ctrl_message_stream = env.socketTextStream("localhost", 8088);

DataStream<String> message_stream = env.socketTextStream("localhost", 8087);

RollingSink sink = new RollingSink<String>("/base/path");
sink.setBucketer(new DateTimeBucketer("yyyy-MM-dd--HHmm"));
sink.setWriter(new StringWriter<String>() );
sink.setBatchSize(1024 * 1024 * 400); // this is 400 MB,

ctrl_message_stream.broadcast().union(message_stream).addSink(sink);

env.execute("stream");