[Flink]Flink1.3 指南二 安装与启动

1. 下载

Flink 可以运行在 Linux, Mac OS X和Windows上。为了运行Flink, 唯一的要求是必须在Java 7.x (或者更高版本)上安装。Windows 用户, 请查看 Flink在Windows上的安装指南。

你可以使用以下命令检查Java当前运行的版本：

java -version

如果你安装的是Java 8，输出结果类似于如下:

java version "1.8.0_91"Java(TM) SE Runtime Environment (build 1.8.0_91-b14)Java HotSpot(TM) 64-Bit Server VM (build 25.91-b14, mixed mode)

从下载页下载一个二进制的包，你可以选择任何你喜欢的Hadoop/Scala组合方式。如果你只是打算使用本地文件系统，那么可以使用任何版本的Hadoop。进入下载目录，解压下载的压缩包:

xiaosi@yoona:~$ tar -zxvf flink-1.3.2-bin-hadoop27-scala_2.11.tgz -C opt/flink-1.3.2/flink-1.3.2/opt/flink-1.3.2/opt/flink-cep_2.11-1.3.2.jarflink-1.3.2/opt/flink-metrics-datadog-1.3.2.jarflink-1.3.2/opt/flink-metrics-statsd-1.3.2.jarflink-1.3.2/opt/flink-gelly_2.11-1.3.2.jarflink-1.3.2/opt/flink-metrics-dropwizard-1.3.2.jarflink-1.3.2/opt/flink-gelly-scala_2.11-1.3.2.jarflink-1.3.2/opt/flink-metrics-ganglia-1.3.2.jarflink-1.3.2/opt/flink-cep-scala_2.11-1.3.2.jarflink-1.3.2/opt/flink-table_2.11-1.3.2.jarflink-1.3.2/opt/flink-ml_2.11-1.3.2.jarflink-1.3.2/opt/flink-metrics-graphite-1.3.2.jarflink-1.3.2/lib/...

2. 启动本地集群

使用如下命令启动Flink：

xiaosi@yoona:~/opt/flink-1.3.2$ ./bin/start-local.shStarting jobmanager daemon on host yoona.

通过访问 http://localhost:8081 检查JobManager网页,确保所有组件都启动并已运行。网页会显示一个有效的TaskManager实例。

你也可以通过检查日志目录里的日志文件来验证系统是否已经运行:

xiaosi@yoona:~/opt/flink-1.3.2/log$ cat flink-xiaosi-jobmanager-0-yoona.log | less2017-10-16 14:42:10,972 INFO  org.apache.flink.runtime.jobmanager.JobManager                -  Starting JobManager (Version: 1.3.2, Rev:0399bee, Date:03.08.2017 @ 10:23:11 UTC)...2017-10-16 14:42:11,109 INFO  org.apache.flink.runtime.jobmanager.JobManager                - Starting JobManager without high-availability2017-10-16 14:42:11,111 INFO  org.apache.flink.runtime.jobmanager.JobManager                - Starting JobManager on localhost:6123 with execution mode LOCAL...2017-10-16 14:42:11,915 INFO  org.apache.flink.runtime.jobmanager.JobManager                - Starting JobManager web frontend...2017-10-16 14:42:13,941 INFO  org.apache.flink.runtime.instance.InstanceManager             - Registered TaskManager at localhost (akka://flink/user/taskmanager) as 0df4d4ebd25ffec4878906726c29f88c. Current number of registered hosts is 1. Current number of alive task slots is 1....

3. Example Code

你可以在GitHub上找到SocketWindowWordCount例子的完整代码，有Java和Scala两个版本。

Scala:

/* * 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 org.apache.flink.streaming.scala.examples.socketimport org.apache.flink.api.java.utils.ParameterToolimport org.apache.flink.streaming.api.scala._import org.apache.flink.streaming.api.windowing.time.Time/** * 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 sever (at port 12345) * using the ''netcat'' tool via * {{{ * nc -l 12345 * }}} * and run this example with the hostname and the port as arguments.. */object SocketWindowWordCount {  /** Main program method */  def main(args: Array[String]) : Unit = {    // the host and the port to connect to    var hostname: String = "localhost"    var port: Int = 0    try {      val params = ParameterTool.fromArgs(args)      hostname = if (params.has("hostname")) params.get("hostname") else "localhost"      port = params.getInt("port")    } catch {      case e: Exception => {        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    val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment    // get input data by connecting to the socket    val text: DataStream[String] = env.socketTextStream(hostname, port, '\n')    // parse the data, group it, window it, and aggregate the counts    val windowCounts = text          .flatMap { w => w.split("\\s") }          .map { w => WordWithCount(w, 1) }          .keyBy("word")          .timeWindow(Time.seconds(5))          .sum("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 */  case class WordWithCount(word: String, count: Long)}

Java版本:

/* * 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 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;/** * 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 * </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;        }    }}

4. 运行Example

现在, 我们可以运行Flink 应用程序。 这个例子将会从一个socket中读取一段文本，并且每隔5秒打印之前5秒内每个单词出现的个数。例如：

a tumbling window of processing time, as long as words are floating in.

(1) 首先,我们可以通过netcat命令来启动本地服务:

nc -l 9000

(2) 提交Flink程序:

xiaosi@yoona:~/opt/flink-1.3.2$ ./bin/flink run examples/streaming/SocketWindowWordCount.jar --port 9000Cluster configuration: Standalone cluster with JobManager at localhost/127.0.0.1:6123Using address localhost:6123 to connect to JobManager.JobManager web interface address http://localhost:8081Starting execution of programSubmitting job with JobID: a963626a1e09f7aeb0dc34412adfb801. Waiting for job completion.Connected to JobManager at Actor[akka.tcp://flink@localhost:6123/user/jobmanager#941160871] with leader session id 00000000-0000-0000-0000-000000000000.10/16/2017 15:12:26 Job execution switched to status RUNNING.10/16/2017 15:12:26 Source: Socket Stream -> Flat Map(1/1) switched to SCHEDULED10/16/2017 15:12:26 TriggerWindow(TumblingProcessingTimeWindows(5000), ReducingStateDescriptor{serializer=org.apache.flink.api.java.typeutils.runtime.PojoSerializer@37ff898e, reduceFunction=org.apache.flink.streaming.examples.socket.SocketWindowWordCount$1@4d15107f}, ProcessingTimeTrigger(), WindowedStream.reduce(WindowedStream.java:300)) -> Sink: Unnamed(1/1) switched to SCHEDULED10/16/2017 15:12:26 Source: Socket Stream -> Flat Map(1/1) switched to DEPLOYING10/16/2017 15:12:26 TriggerWindow(TumblingProcessingTimeWindows(5000), ReducingStateDescriptor{serializer=org.apache.flink.api.java.typeutils.runtime.PojoSerializer@37ff898e, reduceFunction=org.apache.flink.streaming.examples.socket.SocketWindowWordCount$1@4d15107f}, ProcessingTimeTrigger(), WindowedStream.reduce(WindowedStream.java:300)) -> Sink: Unnamed(1/1) switched to DEPLOYING10/16/2017 15:12:26 Source: Socket Stream -> Flat Map(1/1) switched to RUNNING10/16/2017 15:12:26 TriggerWindow(TumblingProcessingTimeWindows(5000), ReducingStateDescriptor{serializer=org.apache.flink.api.java.typeutils.runtime.PojoSerializer@37ff898e, reduceFunction=org.apache.flink.streaming.examples.socket.SocketWindowWordCount$1@4d15107f}, ProcessingTimeTrigger(), WindowedStream.reduce(WindowedStream.java:300)) -> Sink: Unnamed(1/1) switched to RUNNING

应用程序连接socket并等待输入，你可以通过web界面来验证任务期望的运行结果：

单词的数量在5秒的时间窗口中进行累加（使用处理时间和tumbling窗口），并打印在stdout。监控JobManager的输出文件，并在nc写一些文本(回车一行就发送一行输入给Flink) :

xiaosi@yoona:~/opt/flink-1.3.2$  nc -l 9000lorem ipsumipsum ipsum ipsumbye

.out文件将在每个时间窗口截止之际打印每个单词的个数：

xiaosi@yoona:~/opt/flink-1.3.2$  tail -f log/flink-*-jobmanager-*.outlorem : 1bye : 1ipsum : 4

使用以下命令来停止Flink:

 ./bin/stop-local.sh

阅读更多的例子来熟悉Flink的编程API。 当你完成这些，可以继续阅读streaming指南。