上接:flink1.12.x Table API 和 SQL:从kafka读取数据,执行查询,将结果写入到kafka中
修改pom.xml
修改依赖
flink自带的jar包,在依赖上要添加 <scope>provided</scope>,打包时,不要包含这些依赖
<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>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.30</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
<version>1.7.30</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
<scope>provided</scope>
</dependency>
<!-- table api、sql需要的依赖 -->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-planner-blink_2.12</artifactId>
<version>${flink.version}</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>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-json</artifactId>
<version>${flink.version}</version>
</dependency>
<!-- table api、sql需要的依赖 -->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-planner-blink_2.12</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-files</artifactId>
<version>${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>
<!-- 用的是 scala2.11,所以不能打包 -->
<!--<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>
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
启动 hadoop1、hadoop2、hadoop3
启动zookeeper
登录 hadoop1,执行下面命令
/program/bin/zk.sh start
启动kafka
登录 hadoop1,执行下面命令
/program/bin/kafka.sh start
启动hadoop
要将 flink jar提交到yarn运行,所以要启动 yarn,这里都启动了
/program/bin/hadoop.sh start
准备 kafka 主题
创建主题 user_order_input
flink 从该主题读取数据:
/program/kafka_2.12-2.4.1/bin/kafka-topics.sh --create --zookeeper hadoop1:2181 --replication-factor 2 --partitions 3 --topic user-order-input
注意: zookeeper 的主题名称不要有 . 或 _,详见 链接
创建主题 user-order-output
flink 将结果 发送到该主题:
/program/kafka_2.12-2.4.1/bin/kafka-topics.sh --create --zookeeper hadoop1:2181 --replication-factor 2 --partitions 3 --topic user-order-output
启动 user-order-output 主题消费者
启动另一个窗口执行下面命令:
/program/kafka_2.12-2.4.1/bin/kafka-console-consumer.sh --bootstrap-server hadoop1:9092 --topic user-order-output
用于查看数据
测试
上传 程序 jar 包
将体积大的 jar 包上传到 /program/ 目录
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 sql.SQLKafka /program/flink-1.0-SNAPSHOT.jar
看到下图表示启动成功:
注意:启动 2个 yarn任务
启动生产者 user-order-input,发送数据
启动另一个窗口执行下面命令:
/program/kafka_2.12-2.4.1/bin/kafka-console-producer.sh --broker-list hadoop1:9092 --topic user-order-input
在上面的环境中,输入下面内容,发送数据(可一条一条发,也可多条发):
{"name":"java从入门到精通","price":50,"username":"李雷"}
{"name":"spark从入门到精通","price":80,"username":"李雷"}
{"name":"hadoop从入门到精通","price":90,"username":"韩梅梅"}
{"name":"flink从入门到精通","price":70,"username":"韩梅梅"}
{"name":"mysql从入门到精通","price":100,"username":"李雷"}
{"name":"hive从入门到精通","price":100,"username":"lucy"}
{"name":"html从入门到精通","price":120,"username":"lucy"}
观察结果
user-order-output消费者窗口
输出下面内容
{"name":"hive从入门到精通","price":100.0}

