原文地址：https://ci.apache.org/projects/flink/flink-docs-release-1.6/quickstart/setup_quickstart.html

只需几个简单的步骤即可启动并运行Flink示例程序。

设置：下载并配置Flink

Flink可在 Linux，Mac OS X 和 Windows上运行。为了能够运行 Flink，唯一的要求是安装一个有效的 Java 8.x 环境。Windows用户请查看 Flink on Windows 指南，该指南介绍了如何在Windows上配置运行Flink。

您可以运行以下命令来检查Java环境：

java -version

如果你有Java 8，将输出如下所示：

java version "1.8.0_111"
Java(TM) SE Runtime Environment (build 1.8.0_111-b14)
Java HotSpot(TM) 64-Bit Server VM (build 25.111-b14, mixed mode)

下载与解压

1. 从 downloads page 下载二进制文件。您可以选择任何您喜欢的 Hadoop/Scala组合。 如果您打算只使用本地文件系统，任何Hadoop版本都可以正常工作。
2. 转到下载目录。
3. 解压缩下载的存档。

$ cd ~/Downloads        # Go to download directory
$ tar xzf flink-*.tgz   # Unpack the downloaded archive
$ cd flink-1.6.1

启动本地Flink群集

$ ./bin/start-cluster.sh  # Start Flink

检查Dispatcher的web前端 http://localhost:8081 并确保一切正常运行。Web前端应报告单个可用的 TaskManager 实例。

您还可以通过检查logs目录中的日志文件来验证系统是否正在运行：

$ tail log/flink-*-standalonesession-*.log
INFO ... - Rest endpoint listening at localhost:8081
INFO ... - http://localhost:8081 was granted leadership ...
INFO ... - Web frontend listening at http://localhost:8081.
INFO ... - Starting RPC endpoint for StandaloneResourceManager at akka://flink/user/resourcemanager .
INFO ... - Starting RPC endpoint for StandaloneDispatcher at akka://flink/user/dispatcher .
INFO ... - ResourceManager akka.tcp://flink@localhost:6123/user/resourcemanager was granted leadership ...
INFO ... - Starting the SlotManager.
INFO ... - Dispatcher akka.tcp://flink@localhost:6123/user/dispatcher was granted leadership ...
INFO ... - Recovering all persisted jobs.
INFO ... - Registering TaskManager ... under ... at the SlotManager.

看代码

您可以在scala和 Java上的GitHub上找到此 SocketWindowWordCount 示例的完整源代码。

public class SocketWindowWordCount {

    public static void main(String[] args) throws Exception {

        // the port to connect to
        final int port;
        try {
            final ParameterTool params = ParameterTool.fromArgs(args);
            port = params.getInt("port");
        } catch (Exception e) {
            System.err.println("No port specified. Please run 'SocketWindowWordCount --port <port>'");
            return;
        }

        // get the execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // get input data by connecting to the socket
        DataStream<String> text = env.socketTextStream("localhost", port, "\n");

        // parse the data, group it, window it, and aggregate the counts
        DataStream<WordWithCount> windowCounts = text
            .flatMap(new FlatMapFunction<String, WordWithCount>() {
                @Override
                public void flatMap(String value, Collector<WordWithCount> out) {
                    for (String word : value.split("\\s")) {
                        out.collect(new WordWithCount(word, 1L));
                    }
                }
            })
            .keyBy("word")
            .timeWindow(Time.seconds(5), Time.seconds(1))
            .reduce(new ReduceFunction<WordWithCount>() {
                @Override
                public WordWithCount reduce(WordWithCount a, WordWithCount b) {
                    return new WordWithCount(a.word, a.count + b.count);
                }
            });

        // print the results with a single thread, rather than in parallel
        windowCounts.print().setParallelism(1);

        env.execute("Socket Window WordCount");
    }

    // Data type for words with count
    public static class WordWithCount {

        public String word;
        public long count;

        public WordWithCount() {}

        public WordWithCount(String word, long count) {
            this.word = word;
            this.count = count;
        }

        @Override
        public String toString() {
            return word + " : " + count;
        }
    }
}

运行示例

现在，我们将运行此Flink应用程序。它将从socket读取文本，并且每5秒打印一次在前5秒内每个不同单词的出现次数。

• 首先，我们使用netcat来启动本地服务器

$ nc -l 9000

• 提交Flink 程序：

$ ./bin/flink run examples/streaming/SocketWindowWordCount.jar --port 9000
Starting execution of program

程序连接到 socket 并等待输入。 您可以检查Web界面以验证作业是否按预期运行：

单词在5秒的时间窗口中计算（处理时间，切换窗口）并输出到 stdout。 监视TaskManager 的输出文件并在 nc 中写入一些文本（输入在点击后逐行发送到Flink）：

$ nc -l 9000
lorem ipsum
ipsum ipsum ipsum
bye

.out 文件在每次时间窗口结束后输出统计总数：

$ tail -f log/flink-*-taskexecutor-*.out
lorem : 1
bye : 1
ipsum : 4

可以用以下命令停止Flink：

$ ./bin/stop-cluster.sh