java Flink（三十四）Flink ReducingState简单使用

傷城~ 2022-08-30 11:45 271阅读 0赞

直接上代码：

import org.apache.flink.api.common.functions.ReduceFunction;
    import org.apache.flink.api.common.functions.RichFlatMapFunction;
    import org.apache.flink.api.common.state.ReducingState;
    import org.apache.flink.api.common.state.ReducingStateDescriptor;
    import org.apache.flink.api.java.tuple.Tuple2;
    import org.apache.flink.configuration.Configuration;
    import org.apache.flink.streaming.api.datastream.DataStreamSource;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.util.Collector;
    
    //实现ReduceState 每次将状态进行累加
    public class ReduceStateMain {
        public static void main(String[] args) throws Exception{
            StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    
            DataStreamSource<Tuple2<Long, Long>> dataStream = env.fromElements(Tuple2.of(1L, 3L), Tuple2.of(1L, 7L),
                    Tuple2.of(2L, 4L),
                    Tuple2.of(1L, 5L),
                    Tuple2.of(2L, 2L),
                    Tuple2.of(2L, 6L)
            );
    
            dataStream
                    .keyBy(0)
                    .flatMap(new UseReduceState())
                    .print();
            env.execute();
        }
    
        public static class UseReduceState extends RichFlatMapFunction<Tuple2<Long, Long>, Tuple2<Long, Long>>{
    
            private ReducingState<Long> reducingState;
    
            @Override
            public void open(Configuration parameters) throws Exception {
                super.open(parameters);
                reducingState = getRuntimeContext().getReducingState(new ReducingStateDescriptor<Long>("reduceState", new ReduceFunction<Long>() {
                    public Long reduce(Long value1, Long value2) throws Exception {
                        return value1+value2;
                    }
                },Long.class));
            }
    
            public void flatMap(Tuple2<Long, Long> value, Collector<Tuple2<Long, Long>> out) throws Exception {
                reducingState.add(value.f1);;
                out.collect(Tuple2.of(value.f0,reducingState.get()));
            }
        }
    }