Flink入门使用

完全参考：Flink1.3QuickStart

启动本地运行

首先找一台安装了hadoop的linux。
将安装包解压，到bin目录启动local模式的脚本。

tar -zxvf flink-1.3.1-bin-hadoop26-scala_2.11.tgz
./start-local.sh

运行wordCount例子

这个例子从sokect端口中每隔5秒读取其中的输入并进行记数。

//执行完nc输入单词，程序会开始记数。
nc -l 9001
//开另一个xshell，执行运行程序的命令
./bin/flink run examples/streaming/SocketWindowWordCount.jar --port 9001
//到log目录下可以看到输出了记数的文件

运行的jar中的源码如下：

package org.apache.flink.streaming.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;

@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;
		}
	}
}

创建flink项目

window的命令行执行以下命令即可下载一个模板项目，导入IDE中就可以愉快地撸了。

mvn archetype:generate -DarchetypeGroupId=org.apache.flink -DarchetypeArtifactId=flink-quickstart-java -DarchetypeVersion=1.3.0