Flink 获取 KeyedState State Value 并在 Another Stream 中使用

Question

我知道键控状态属于它的键，只有当前键访问它的状态值，其他键不能访问不同键的状态值。

我尝试使用相同的密钥但在不同的流中访问状态。可能吗？

如果不可能，那么我会有 2 个重复数据？

不是：我需要两个流，因为它们每个都有不同的时间窗口和不同的实现。

示例如下（我知道 keyBy(sommething) 对于两个流操作是相同的）：

public class Sample{
       streamA
                .keyBy(something)
                .timeWindow(Time.seconds(4))
                .process(new CustomMyProcessFunction())
                .name("CustomMyProcessFunction")
                .print();

       streamA
                .keyBy(something)
                .timeWindow(Time.seconds(1))
                .process(new CustomMyAnotherProcessFunction())
                .name("CustomMyProcessFunction")
                .print();
}

public class CustomMyProcessFunction extends ProcessWindowFunction<..>
{
    private Logger logger = LoggerFactory.getLogger(CustomMyProcessFunction.class);
    private transient ValueState<SimpleEntity> simpleEntityValueState;
    private SimpleEntity simpleEntity;

    @Override
    public void open(Configuration parameters) throws Exception
    {
        ValueStateDescriptor<SimpleEntity> simpleEntityValueStateDescriptor = new ValueStateDescriptor<SimpleEntity>(
                "sample",
                TypeInformation.of(SimpleEntity.class)
        );
        simpleEntityValueState = getRuntimeContext().getState(simpleEntityValueStateDescriptor);
    }

    @Override
    public void process(...) throws Exception
    {
        SimpleEntity value = simpleEntityValueState.value();
        if (value == null)
        {
            SimpleEntity newVal = new SimpleEntity("sample");
            logger.info("New Value put");
            simpleEntityValueState.update(newVal);
        }
        ...
    }
...
}

public class CustomMyAnotherProcessFunction extends ProcessWindowFunction<..>
{


    private transient ValueState<SimpleEntity> simpleEntityValueState;

    @Override
    public void open(Configuration parameters) throws Exception
    {

        ValueStateDescriptor<SimpleEntity> simpleEntityValueStateDescriptor = new ValueStateDescriptor<SimpleEntity>(
                "sample",
                TypeInformation.of(SimpleEntity.class)
        );
        simpleEntityValueState = getRuntimeContext().getState(simpleEntityValueStateDescriptor);
    }

    @Override
    public void process(...) throws Exception
    {
        SimpleEntity value = simpleEntityValueState.value();
        if (value != null)
            logger.info(value.toString()); // I expect that SimpleEntity("sample")
        out.collect(...);
    }
...
}

Answer 1

我试过你的想法，使用相同的密钥在两个操作员之间共享状态。

import org.apache.flink.api.common.state.ValueState;
import org.apache.flink.api.common.state.ValueStateDescriptor;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.streaming.api.functions.windowing.ProcessWindowFunction;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

import java.io.IOException;

public class FlinkReuseState {

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

        DataStream<Integer> stream1 = env.addSource(new SourceFunction<Integer>() {
            @Override
            public void run(SourceContext<Integer> sourceContext) throws Exception {
                int i = 0;
                while (true) {
                    sourceContext.collect(1);
                    Thread.sleep(1000);
                }
            }

            @Override
            public void cancel() {

            }
        });

        DataStream<Integer> stream2 = env.addSource(new SourceFunction<Integer>() {
            @Override
            public void run(SourceContext<Integer> sourceContext) throws Exception {
                while (true) {
                    sourceContext.collect(1);
                    Thread.sleep(1000);
                }
            }

            @Override
            public void cancel() {

            }
        });


        DataStream<Integer> windowedStream1 = stream1.keyBy(Integer::intValue)
                .timeWindow(Time.seconds(3))
                .process(new ProcessWindowFunction<Integer, Integer, Integer, TimeWindow>() {
                    private ValueState<Integer> value;

                    @Override
                    public void open(Configuration parameters) throws Exception {
                        super.open(parameters);
                        ValueStateDescriptor<Integer> desc = new ValueStateDescriptor<Integer>("value", Integer.class);
                        value = getRuntimeContext().getState(desc);
                    }

                    @Override
                    public void process(Integer integer, Context context, Iterable<Integer> iterable, Collector<Integer> collector) throws Exception {
                        iterable.forEach(x -> {
                            try {
                                if (value.value() == null) {
                                    value.update(1);
                                } else {
                                    value.update(value.value() + 1);
                                }
                            } catch (IOException e) {
                                e.printStackTrace();
                            }
                        });
                        collector.collect(value.value());
                    }
                });

        DataStream<String> windowedStream2 = stream2.keyBy(Integer::intValue)
                .timeWindow(Time.seconds(3))
                .process(new ProcessWindowFunction<Integer, String, Integer, TimeWindow>() {

                    private ValueState<Integer> value;

                    @Override
                    public void open(Configuration parameters) throws Exception {
                        super.open(parameters);
                        ValueStateDescriptor<Integer> desc = new ValueStateDescriptor<Integer>("value", Integer.class);
                        value = getRuntimeContext().getState(desc);
                    }

                    @Override
                    public void process(Integer s, Context context, Iterable<Integer> iterable, Collector<String> collector) throws Exception {
                        iterable.forEach(x -> {
                            try {
                                if (value.value() == null) {
                                    value.update(1);
                                } else {
                                    value.update(value.value() + 1);
                                }
                            } catch (IOException e) {
                                e.printStackTrace();
                            }
                        });
                        collector.collect(String.valueOf(value.value()));
                    }
                });

        windowedStream2.print();

        windowedStream1.print();

        env.execute();

    }
}

不行，每个流只更新自己的值状态，输出如下。

keyed state

根据官方文档，*每个键控状态在逻辑上都绑定到 <parallel-operator-instance, key> 的唯一组合，并且由于每个键“属于”键控运算符的一个并行实例，我们可以认为这只是 <operator, key>*。

我认为不可能通过为不同运算符中的状态赋予相同的名称来共享状态。

你试过协同处理功能吗？通过这样做，您还可以为每个流实现两个进程函数，唯一的问题将是时间窗口。您能否提供有关流程逻辑的更多详细信息？

Answer 2

正如已经指出的那样，状态对于单个运算符实例始终是本地的。无法共享。

但是，您可以做的是将状态更新从持有状态的操作员流式传输到需要它的其他操作员。使用 side outputs，您可以创建复杂的数据流而无需共享状态。

Answer 3

为什么你不能 return 状态作为映射操作的一部分并且该流可用于连接到其他流

Flink 获取 KeyedState State Value 并在 Another Stream 中使用

Flink Get the KeyedState State Value and use in Another Stream

apache-flink

flink-streaming