修改pom.xml
不包含flink自带包
flink自带的jar包,在依赖上要添加 <scope>provided</scope>,打包时,不要包含这些包
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-java_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.30</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
<version>1.7.30</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
<scope>provided</scope>
</dependency>
注意
flink-runtime-web_2.12 要设置 <scope>provided</scope>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-runtime-web_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
注意
org.apache.bahir 不要用,因为是 scala 2.11 版本,与 flink 中的scala 2.12 版不匹配
<dependency>
<groupId>org.apache.bahir</groupId>
<artifactId>flink-connector-redis_2.11</artifactId>
<version>1.0</version>
</dependency>
添加打包插件
<build>
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.7.0</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>3.1.1</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
<!-- 修改主类-->
<mainClass></mainClass>
</transformer>
<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
<resource>reference.conf</resource>
</transformer>
</transformers>
<relocations>
<relocation>
<pattern>org.codehaus.plexus.util</pattern>
<shadedPattern>org.shaded.plexus.util</shadedPattern>
<excludes>
<exclude>org.codehaus.plexus.util.xml.Xpp3Dom</exclude>
<exclude>org.codehaus.plexus.util.xml.pull.*</exclude>
</excludes>
</relocation>
</relocations>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
完整依赖
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>1.8</maven.compiler.source>
<maven.compiler.target>1.8</maven.compiler.target>
<flink.version>1.12.0</flink.version>
</properties>
<dependencies>
<!--java-->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-java_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.30</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
<version>1.7.30</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
<scope>provided</scope>
</dependency>
<!-- kafka Dependency -->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-kafka_2.12</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-files</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-runtime-web_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-jdbc_2.12</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.47</version>
</dependency>
<!--<dependency>-->
<!-- <groupId>org.apache.bahir</groupId>-->
<!-- <artifactId>flink-connector-redis_2.11</artifactId>-->
<!-- <version>1.0</version>-->
<!--</dependency>-->
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
<version>2.9.0</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.7.0</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>3.1.1</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
<!-- 修改主类-->
<mainClass></mainClass>
</transformer>
<transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
<resource>reference.conf</resource>
</transformer>
</transformers>
<relocations>
<relocation>
<pattern>org.codehaus.plexus.util</pattern>
<shadedPattern>org.shaded.plexus.util</shadedPattern>
<excludes>
<exclude>org.codehaus.plexus.util.xml.Xpp3Dom</exclude>
<exclude>org.codehaus.plexus.util.xml.pull.*</exclude>
</excludes>
</relocation>
</relocations>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
java 类
package map;
import org.apache.flink.api.common.RuntimeExecutionMode;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;
public class TestSocket {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// env.setRuntimeMode(RuntimeExecutionMode.BATCH);//批模式
// env.setRuntimeMode(RuntimeExecutionMode.STREAMING);//流模式
env.setRuntimeMode(RuntimeExecutionMode.AUTOMATIC);//自动模式,根据数据源自行判断
DataStream<String> dataStream = env.socketTextStream("hadoop1", 9999);
SingleOutputStreamOperator<Tuple2<String, Integer>> soso=dataStream.flatMap(new Splitter());
KeyedStream<Tuple2<String, Integer>,String> ks=soso.keyBy(new keyByImpl());//流处理中的分组
// .window(TumblingProcessingTimeWindows.of(Time.seconds(5)))
SingleOutputStreamOperator<Tuple2<String, Integer>> soso2=ks.sum(1);//按照第二个元素聚合
soso2.print();
//启动并等待程序结束,可传入任务名
env.execute("Window WordCount");
}
/**
* 拆分、并记为1,每个元素是元祖,格式: (单词,1)
* FlatMapFunction<String, Tuple2<String, Integer>> 泛型解释:
* String:传入的是字符串
* Tuple2<String, Integer>,集合的泛型。对字符串进行处理,封装成Tuple类型,格式:(单词,1),然后放到该集合中
*/
public static class Splitter implements FlatMapFunction<String, Tuple2<String, Integer>> {
/**
*
* @param sentence 表示每一行数据
* @param out 传出的集合
*/
@Override
public void flatMap(String sentence, Collector<Tuple2<String, Integer>> out) throws Exception {
for (String word: sentence.split(" ")) {
out.collect(new Tuple2<String, Integer>(word, 1));
}
}
}
/**
根据第一个元素(即:单词)进行分组
KeySelector<Tuple2<String, Integer>,String> 泛型解释:
Tuple2<String, Integer>:传入的是 Tuple类型,也就是上面封装的Tuple,格式: (单词,1)
String:传出类型,也就是Tuple中的单词,根据该单词进行分组
*/
public static class keyByImpl implements KeySelector<Tuple2<String, Integer>,String>{
/**
*
* @param t:传入的元祖,格式:(单词,1)
* @return
* @throws Exception
*/
@Override
public String getKey(Tuple2<String, Integer> t) throws Exception {
return t.f0;
}
}
}
log4j.properties
在 resources 目录下创建 log4j.properties 文件,内容如下:
# DEBUG 级别,即:所有信息都会输出
log4j.rootLogger=INFO, stdout
# 配置 stdout,输出到控制台
log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=%d %p [%c] - %m%n
注意:不加此文件会显示警告
测试
打包
双击 maven 的 package,打包,结果有2个 jar 文件,一个文件比较大,这个文件就是打包好的文件
启动 socket
登录 hadoop1,执行下面命令:
nc -lk 9999
上传
略
per-job cluster模式启动
/program/flink-1.12.5/bin/flink run -m yarn-cluster -ytm 1000 -yjm 1000 -ys 1 -c map.TestSocket /program/flink-1.0-SNAPSHOT.jar
看到下图表示启动成功:
输入数据
在 socket 窗口输入下面内容:
haha hehe
xixi haha xixi



