本文介紹如何在mac電腦端安裝flink、運(yùn)行flink自帶exmaple团滥。
唯一的前置條件為電腦端安裝Java 8.x 托酸。
mac電腦端安裝flink命令：
brew install apache-flink
查看flink安裝位置，啟動(dòng)flink
brew info apache-flink
/usr/local/Cellar/apache-flink/1.8.1/libexec/bin
cd /usr/local/Cellar/apache-flink/1.8.1/libexec/bin;./start-cluster.sh
//輸出:
//Starting cluster.
//Starting standalonesession daemon on host MacBook-Pro.local.
//Starting taskexecutor daemon on host MacBook-Pro.local.
查看flink控制臺(tái)
http://localhost:8081/#/overview
創(chuàng)建一個(gè)flink的maven項(xiàng)目安皱，這里使用flink-quickstart-scala模版生成項(xiàng)目,同時(shí)可以使用scala與java代碼編寫flink應(yīng)用
mvn archetype:generate -DarchetypeGroupId=org.apache.flink -DarchetypeArtifactId=flink-quickstart-scala -DarchetypeVersion=1.8.1 -DgroupId=com.galaxy.flink -DartifactId=galaxyFlink -Dversion=1.0-SNAPSHOT -Dpackage=com.galaxy.flink -DinteractiveMode=false
從github的flink項(xiàng)目獲得代碼爷贫，類名：org.apache.flink.streaming.examples.socket.SocketWindowWordCount
package com.galaxy.flink.examples.socket;
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 or Mac
* </pre>
* and run this example with the hostname and the port as arguments.
*/
@SuppressWarnings("serial")
public class SocketWindowWordCount {
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");
} catch (Exception e) {
System.err.println("No port specified. Please run 'SocketWindowWordCount " +
"--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;
}
}
}
添加README.md文件與.gitignore文件认然，并將本地項(xiàng)目提交到github，方便預(yù)研代碼托管漫萄。
image.png
使用 netcat 啟動(dòng)一個(gè)本地server：[注意：在mac端卷员，要使用p參數(shù)]
nc -l -p 9000
//隨機(jī)敲入字符
a d
w e
運(yùn)行example：
有兩種方式啟動(dòng)代碼：
- 直接在IDEA中啟動(dòng)代碼類，任務(wù)將在本地內(nèi)嵌的Flink環(huán)境中運(yùn)行
//從控制臺(tái)日志中可以看到
15:01:38,218 INFO org.apache.flink.streaming.api.environment.LocalStreamEnvironment - Running job on local embedded Flink mini cluster
15:01:38,659 INFO org.apache.flink.runtime.minicluster.MiniCluster - Starting Flink Mini Cluster
控制臺(tái)中會(huì)打印出統(tǒng)計(jì)信息腾务。
- 將代碼打成jar包子刮，提交到本地flink集群環(huán)境中運(yùn)行
//提交到本地flink集群命令
/usr/local/Cellar/apache-flink/1.8.1/libexec/bin/flink run -c com.galaxy.flink.examples.socket.SocketWindowWordCount /Users/baozhiwang/local_dir/codes/galaxyFlink/target/galaxyFlink-1.0-SNAPSHOT.jar --hostname localhost --port 9000
查看日志：
tailf /usr/local/Cellar/apache-flink/1.8.1/libexec/log/flink-baozhiwang-taskexecutor-0-baozhideMacBook-Pro.local.out
/**
a : 1
d : 1
w : 1
e : 1
*/
