1. 下载并安装
运行Flink之前,先确保您的java环境是Java 8 or 11,请使用java -version查看版本
$ cd ~/Downloads # Go to download directory
$ tar xzf flink-*.tgz # Unpack the downloaded archive
$ cd flink-1.10.0
启动:
$ ./bin/start-cluster.sh # Start Flink
查看日志可以看到如下信息:
$ 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 ... at ResourceManager
2. 运行示例
示例代码:
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 '");
return;
}
// get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// get input data by connecting to the socket
DataStream text = env.socketTextStream("localhost", port, "\n");
// parse the data, group it, window it, and aggregate the counts
DataStream windowCounts = text
.flatMap(new FlatMapFunction() {
@Override
public void flatMap(String value, Collector 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() {
@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;
}
}
}
首先先使用netcat打开本地服务
$ nc -l 9000
提交示例程序
$ ./bin/flink run examples/streaming/SocketWindowWordCount.jar --port 9000
Starting execution of program
程序连接到socket,并等待输入,可以在web端查看程序是否符合预期效果
开始输入数据,测试程序效果:
$ nc -l 9000
lorem ipsum
ipsum ipsum ipsum
bye
输出:
$ tail -f log/flink-*-taskexecutor-*.out
lorem : 1
bye : 1
ipsum : 4