Flink1.8中如何进行流处理SocketWordCount
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概述:
这里主要演示flink源码实例中“WordCount”程序的流窗口版本。
此程序连接到socket服务器并从socket读取字符串。最简单的尝试方法是打开一个文本服务器(在端口9999),使用netcat工具
我这里也贴一下:
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* Licensed to the Apache Software Foundation (ASF) under one
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* to you under the Apache License, Version 2.0 (the
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*
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package com.hadoop.ljs.flink.streaming;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.Collector;
/**
* Implements a streaming windowed version of the "WordCount" program.
*
*
This program connects to a server socket and reads strings from the socket.
* The easiest way to try this out is to open a text server (at port 12345)
* using the netcat tool via
*
* nc -l 12345 on Linux or nc -l -p 12345 on Windows
*
* and run this example with the hostname and the port as arguments.
*/
@SuppressWarnings("serial")
public class SocketWordCount {
public static void main(String[] args) throws Exception {
// the host and the port to connect to
final String hostname;
final int port;
try {
final ParameterTool params = ParameterTool.fromArgs(args);
hostname = params.has("hostname") ? params.get("hostname") : "localhost";
port = params.getInt("port");
/*hostname = "10.124.165.98";
port = 9999;*/
} catch (Exception e) {
System.err.println("No port specified. Please run 'SocketWordCount " +
"--hostname --port ', where hostname (localhost by default) " +
"and port is the address of the text server");
System.err.println("To start a simple text server, run 'netcat -l ' and " +
"type the input text into the command line");
return;
}
// get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// get input data by connecting to the socket
DataStream text = env.socketTextStream(hostname, 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))
.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;
}
}
}
通过maven package打出jar包:flink191-1.0-SNAPSHOT-jar-with-dependencies
直接提交到flink在yarn中已启动的一个session中,从flink界面上传jar:
上传后,选中jar前面的复选框,可直接填写相关参数:
参数格式:--参数名 参数值 --参数名2 参数值2
参数获取是通过上面代码第49行的工具类获取(固定格式):
ParameterTool params = ParameterTool.fromArgs(args);
最后点击“Submit”按钮,提交任务运行即可。
界面也可查看日志和输出:
以上就是Flink1.8中如何进行流处理SocketWordCount,小编相信有部分知识点可能是我们日常工作会见到或用到的。希望你能通过这篇文章学到更多知识。更多详情敬请关注创新互联行业资讯频道。
文章标题:Flink1.8中如何进行流处理SocketWordCount
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