Flink笔记-广播流

一、keyBy的广播流使用

        KeyedBroadcastProcessFunction

public class TwoStreamJoinWithBroadcastStream {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(3);

        FlinkKafkaConsumer010<String> dwdConsumer = new FlinkKafkaConsumer010<>("dwd", new SimpleStringSchema(), KafkaUtils.comsumerProps());
        FlinkKafkaConsumer010<String> dimConsumer = new FlinkKafkaConsumer010<>("dim", new SimpleStringSchema(), KafkaUtils.comsumerProps());

        DataStreamSource<String> dwdStream = env.addSource(dwdConsumer);
        DataStreamSource<String> dimStream = env.addSource(dimConsumer);

        // 声明一个MapStateDescriptor，维度表作为广播state
        MapStateDescriptor<String, String> dimState = new MapStateDescriptor<>("dimState", BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO);
        BroadcastStream<String> broadcastStream = dimStream.broadcast(dimState);

        KeyedStream<String, String> vodKeyStream = dwdStream.keyBy(new KeySelector<String, String>() {
            @Override
            public String getKey(String line) throws Exception {
                JSONObject jn = JSON.parseObject(line);
                return jn.get("vodid").toString();
            }
        });

        SingleOutputStreamOperator<Stri