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Flink1.8中如何進行流處理SocketWordCount

發布時間:2021-12-23 17:00:25 來源:億速云 閱讀:212 作者:柒染 欄目:大數據

本篇文章給大家分享的是有關Flink1.8中如何進行流處理SocketWordCount,小編覺得挺實用的,因此分享給大家學習,希望大家閱讀完這篇文章后可以有所收獲,話不多說,跟著小編一起來看看吧。

概述:

        這里主要演示flink源碼實例中“WordCount”程序的流窗口版本。

    此程序連接到socket服務器并從socket讀取字符串。最簡單的嘗試方法是打開一個文本服務器(在端口9999),使用netcat工具

我這里也貼一下:

/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements.  See the NOTICE file * distributed with this work for additional information * regarding copyright ownership.  The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License.  You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */
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. * * <p>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 <i>netcat</i> tool via * <pre> * nc -l 12345 on Linux or nc -l -p 12345 on Windows * </pre> * 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 <hostname> --port <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 <port>' 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<String> text = env.socketTextStream(hostname, 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))
       .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;    }  }}

    通過maven package打出jar包:flink191-1.0-SNAPSHOT-jar-with-dependencies

直接提交到flink在yarn中已啟動的一個session中,從flink界面上傳jar:

Flink1.8中如何進行流處理SocketWordCount

    上傳后,選中jar前面的復選框,可直接填寫相關參數:

Flink1.8中如何進行流處理SocketWordCount

參數格式:--參數名   參數值  --參數名2  參數值2

參數獲取是通過上面代碼第49行的工具類獲取(固定格式):

ParameterTool params = ParameterTool.fromArgs(args);

最后點擊“Submit”按鈕,提交任務運行即可。

界面也可查看日志和輸出:

Flink1.8中如何進行流處理SocketWordCount

以上就是Flink1.8中如何進行流處理SocketWordCount,小編相信有部分知識點可能是我們日常工作會見到或用到的。希望你能通過這篇文章學到更多知識。更多詳情敬請關注億速云行業資訊頻道。

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