java Flink（三十四）Flink ReducingState简单使用

最新推荐文章于 2023-08-03 08:34:24 发布

原创最新推荐文章于 2023-08-03 08:34:24 发布 · 501 阅读

2 ·

CC 4.0 BY-SA版权

Java 同时被 2 个专栏收录

97 篇文章

订阅专栏

Java Flink

45 篇文章

订阅专栏

该博客展示了如何在Apache Flink中利用ReduceState处理数据流，通过RichFlatMapFunction和ReducingStateDescriptor实现状态累加，从而对特定key的值进行聚合计算。

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()));
        }
    }
}