Flink 异步 IO 处理是指在 Flink 数据流处理过程中,通过异步方式处理 IO 操作,以提高处理效率和性能。下面是一个 Flink 异步 IO 处理示例:

首先,在 Flink 程序中需要使用 AsyncDataStream 来构建异步数据流处理。例如:

AsyncDataStream.unorderedWait(inputDataStream, new MyAsyncFunction(), 1000, TimeUnit.MILLISECONDS, 100);

其中,inputDataStream 是输入数据流,MyAsyncFunction 是异步处理函数,1000 和 TimeUnit.MILLISECONDS 表示异步等待的时间,100 表示最大并行处理数。

接着,需要定义异步处理函数,例如:

public class MyAsyncFunction extends RichAsyncFunction<InputType, OutputType> {

    private transient SomeAsyncClient client;

    @Override
    public void open(Configuration parameters) throws Exception {
        // 初始化异步客户端
        client = new SomeAsyncClient();
    }

    @Override
    public void asyncInvoke(InputType input, ResultFuture<OutputType> resultFuture) throws Exception {
        // 异步调用客户端,处理数据
        Future<OutputType> future = client.handle(input);
        // 注册回调函数,当处理完成时,将结果添加到输出流
        Futures.addCallback(future, new FutureCallback<OutputType>() {
            @Override
            public void onSuccess(OutputType output) {
                resultFuture.complete(Collections.singleton(output));
            }

            @Override
            public void onFailure(Throwable throwable) {
                resultFuture.completeExceptionally(throwable);
            }
        }, getAsyncExecutor());
    }

    @Override
    public void timeout(InputType input, ResultFuture<OutputType> resultFuture) throws Exception {
        // 处理超时情况,可以返回一个默认值或者抛出异常
        resultFuture.complete(Collections.singleton(defaultOutput));
    }

    @Override
    public void close() throws Exception {
        // 关闭异步客户端
        client.close();
    }
}

在异步处理函数中,需要实现 asyncInvoke 方法和 timeout 方法。asyncInvoke 方法用于异步调用客户端处理数据,并注册回调函数。timeout 方法用于处理超时情况。

最后,需要将异步处理后的数据添加到输出流中,可以使用 ResultFuture.complete 方法或者 ResultFuture.completeExceptionally 方法。例如:

resultFuture.complete(Collections.singleton(output));

完整的 Flink 异步 IO 处理示例代码如下:

public class AsyncIOExample {

    public static void main(String[] args) throws Exception {
        // set up the streaming execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // add a source
        DataStream<String> input = env.socketTextStream('localhost', 9999);

        // process the stream asynchronously
        DataStream<String> output = AsyncDataStream.unorderedWait(
                input,
                new MyAsyncFunction(),
                1000,
                TimeUnit.MILLISECONDS,
                100);

        // print the result stream
        output.print();

        // execute the program
        env.execute('Async IO Example');
    }

    public static class MyAsyncFunction extends RichAsyncFunction<String, String> {

        private transient SomeAsyncClient client;

        @Override
        public void open(Configuration parameters) throws Exception {
            // initialize the async client
            client = new SomeAsyncClient();
        }

        @Override
        public void asyncInvoke(String input, ResultFuture<String> resultFuture) throws Exception {
            // async call the client to handle the input
            Future<String> future = client.handle(input);
            // register the callback function to add the result to the output stream when it's done
            Futures.addCallback(future, new FutureCallback<String>() {
                @Override
                public void onSuccess(String output) {
                    resultFuture.complete(Collections.singleton(output));
                }

                @Override
                public void onFailure(Throwable throwable) {
                    resultFuture.completeExceptionally(throwable);
                }
            }, getAsyncExecutor());
        }

        @Override
        public void timeout(String input, ResultFuture<String> resultFuture) throws Exception {
            // handle the timeout case
            resultFuture.complete(Collections.singleton('timeout'));
        }

        @Override
        public void close() throws Exception {
            // close the async client
            client.close();
        }
    }

    public static class SomeAsyncClient {

        public Future<String> handle(String input) {
            // do some async IO operation
            CompletableFuture<String> future = new CompletableFuture<>();
            new Thread(() -> {
                try {
                    Thread.sleep(500);
                    future.complete('output: ' + input);
                } catch (InterruptedException e) {
                    future.completeExceptionally(e);
                }
            }).start();
            return future;
        }

        public void close() {
            // close the client
        }
    }
}
Flink 异步 IO 处理示例 - 提高数据流处理效率

原文地址: https://www.cveoy.top/t/topic/lFxt 著作权归作者所有。请勿转载和采集!

免费AI点我,无需注册和登录