这篇文章主要介绍“flinksql如何链接kafka”，在日常操作中，相信很多人在flinksql如何链接kafka问题上存在疑惑，小编查阅了各式资料，整理出简单好用的操作方法，希望对大家解答”flinksql如何链接kafka”的疑惑有所帮助！接下来，请跟着小编一起来学习吧！
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>org.example</groupId>
<artifactId>flinksqldemo</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<!-- Encoding -->
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<scala.binary.version>2.11</scala.binary.version>
<scala.version>2.11.8</scala.version>
<kafka.version>0.10.2.1</kafka.version>
<flink.version>1.12.0</flink.version>
<hadoop.version>2.7.3</hadoop.version>
<!-- scope 本地调试时注销 设定为默认的 compile 打包时设定为 provided -->
<setting.scope>compile</setting.scope>
</properties>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>8</source>
<target>8</target>
</configuration>
</plugin>
</plugins>
</build>
<dependencies>
<!--flink start-->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-planner-blink_2.11</artifactId>
<version>1.12.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>${flink.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-java_2.11</artifactId>
<version>${flink.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients_2.11</artifactId>
<version>${flink.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-kafka_2.11</artifactId>
<version>1.12.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-csv</artifactId>
<version>1.12.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
<version>${flink.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<!--<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-statebackend-rocksdb_${scala.binary.version}</artifactId>
<version>${flink.version}</version>
</dependency>-->
<!-- flink end-->
<!-- kafka start -->
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_${scala.binary.version}</artifactId>
<version>${kafka.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<!-- kafka end-->
<!-- hadoop start -->
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>${hadoop.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>${hadoop.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
<scope>${setting.scope}</scope>
</dependency>
<!-- hadoop end -->
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.25</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.72</version>
</dependency>
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
<version>2.7.3</version>
</dependency>
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>29.0-jre</version>
</dependency>
</dependencies>
</project>代码：
package com.jd.data;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.DataTypes;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.descriptors.Csv;
import org.apache.flink.table.descriptors.Kafka;
import org.apache.flink.table.descriptors.Schema;
import org.apache.flink.types.Row;
public class TableApiConnectKafka04 {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(1);
// 1、创建表执行环节
StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
tableEnv.connect(new Kafka()
.version("0.11") // 定义版本
.topic("xxx") // 定义主题
.property("zookeeper.connect", "localhost:2181")
.property("bootstrap.servers", "localhost:9092")
).withFormat(new Csv()).withSchema(new Schema().field("a", DataTypes.STRING()) // 定义表的结构
.field("b", DataTypes.STRING())
.field("c", DataTypes.STRING())
)
.inAppendMode()
.createTemporaryTable("xxx");
Table xxx = tableEnv.from("xxx");
xxx.printSchema();
tableEnv.toAppendStream(xxx, Row.class ).print();
env.execute("job");
}
}到此，关于“flinksql如何链接kafka”的学习就结束了，希望能够解决大家的疑惑。理论与实践的搭配能更好的帮助大家学习，快去试试吧！若想继续学习更多相关知识，请继续关注亿速云网站，小编会继续努力为大家带来更多实用的文章！
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