Flink实例（125）：状态管理（十四）自定义操作符状态（五）list state（二）

1.需求

/**
 * 需求：每两个元素输出一次
 */

2 代码

package com.nx.streaming.lesson03;

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

/**
 * 需求：每两个元素输出一次
 */
public class TestOperatorStateMain {
    public static void main(String[] args) throws  Exception{
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStreamSource<Tuple2<String, Integer>> dataStreamSource =
                env.fromElements(
                        Tuple2.of("Spark", 3),
                        Tuple2.of("Flink", 5),
                        Tuple2.of("Hadoop", 7),
                        Tuple2.of("Spark", 4));

        dataStreamSource
                .addSink(new CustomSink(2)).setParallelism(1);


        env.execute("TestOperatorStateMain...");
    }
}

package com.nx.streaming.lesson03;

import org.apache.flink.api.common.state.ListState;
import org.apache.flink.api.common.state.ListStateDescriptor;
import org.apache.flink.api.common.typeinfo.TypeHint;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.runtime.state.FunctionInitializationContext;
import org.apache.flink.runtime.state.FunctionSnapshotContext;
import org.apache.flink.streaming.api.checkpoint.CheckpointedFunction;
import org.apache.flink.streaming.api.functions.sink.SinkFunction;

import java.util.ArrayList;
import java.util.List;

/**
 *
 *
 */
public class CustomSink  implements SinkFunction<Tuple2<String, Integer>>, CheckpointedFunction {
    // 用于缓存结果数据的
    private List<Tuple2<String, Integer>> bufferElements;
    // 表示内存中数据的大小阈值
    private int threshold;
    // 用于保存内存中的状态信息
    private ListState<Tuple2<String, Integer>> checkpointState;
    // StateBackend
    // checkpoint

    public CustomSink(int threshold) {
        this.threshold = threshold;
        this.bufferElements = new ArrayList<>();
    }

    @Override
    public void invoke(Tuple2<String, Integer> value, Context context) throws Exception {
        // 可以将接收到的每一条数据保存到任何的存储系统中
        bufferElements.add(value);
        if (bufferElements.size() == threshold) {
            // 简单打印
            System.out.println(bufferElements);
            bufferElements.clear();
        }
    }

    // 用于将内存中数据保存到状态中
    @Override
    public void snapshotState(FunctionSnapshotContext context) throws Exception {
        checkpointState.clear();
        for (Tuple2<String, Integer> ele : bufferElements) {
            checkpointState.add(ele);
        }
    }
    // 用于在程序挥发的时候从状态中恢复数据到内存
    @Override
    public void initializeState(FunctionInitializationContext context) throws Exception {
        ListStateDescriptor<Tuple2<String, Integer>> descriptor =
                new ListStateDescriptor<Tuple2<String, Integer>>(
                        "bufferd -elements",
                        TypeInformation.of(new TypeHint<Tuple2<String, Integer>>() {}));

        // 注册一个 operator state
        checkpointState = context.getOperatorStateStore().getListState(descriptor);

        if (context.isRestored()) {
            for (Tuple2<String, Integer> ele : checkpointState.get()) {
                bufferElements.add(ele);
            }
        }
    }

}