一、FlinkCDC-DataStream

水善利万物而不争,处众人之所恶,故几于道💦

FlinkCDC以DataStream的方式读取MySQL变更,打印到控制台

文章目录

      • [1. 引入相关依赖](#1. 引入相关依赖)
      • [2. 编写代码](#2. 编写代码)
      • [3. 启动](#3. 启动)
      • 相关报错
        • [1. JsonDebeziumDeserializationSchema类型转换异常](#1. JsonDebeziumDeserializationSchema类型转换异常)
        • [2. 找不到方法getStaticJavaEncodingForMysqlCharset(Ljava/lang/String;)Ljava/lang/String](#2. 找不到方法getStaticJavaEncodingForMysqlCharset(Ljava/lang/String;)Ljava/lang/String)

1. 引入相关依赖

xml 复制代码
    <properties>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
        <flink-version>1.18.0</flink-version>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner_2.12</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-runtime</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java-bridge</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-base</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>com.ververica</groupId>
            <artifactId>flink-connector-mysql-cdc</artifactId>
            <version>3.0.0</version>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>8.0.31</version>
        </dependency>
        <dependency>
            <groupId>com.ververica</groupId>
            <artifactId>flink-connector-debezium</artifactId>
            <version>3.0.0</version>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.0.0</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>

2. 编写代码

将监控到的cdc打印到控制台

java 复制代码
import com.ververica.cdc.connectors.mysql.source.MySqlSource;
import com.ververica.cdc.connectors.mysql.table.StartupOptions;
import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

/**
 * Author: Pepsi
 * Date: 2026/2/8
 * Desc:
 */
public class FlinkCDC_DataStream {

    public static void main(String[] args) throws Exception {
        // 1. 获取flink执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        // 2. 开启CheckPoint

        // 3. 使用FlinkCDC构建MysqlSource


        MySqlSource<String> mySqlSource = MySqlSource.<String>builder()
                .hostname("localhost")
                .port(3306)
                .username("root")
                .password("xxxxxx")
                .databaseList("test")
                .tableList("test.a") //在写表时,需要带上库名。如果什么都不写,则表示监控所有的表
                .startupOptions(StartupOptions.initial())
                .deserializer(new JsonDebeziumDeserializationSchema()) // 返回String
                .build();

        //4.读取数据
        DataStreamSource<String> mysqlDS = env.fromSource(mySqlSource, WatermarkStrategy.noWatermarks(), "mysql-source");

        //5.打印
        mysqlDS.print();

        //6.启动
        env.execute();
    }

}

3. 启动

相关报错

1. JsonDebeziumDeserializationSchema类型转换异常

Error:(32, 31) java: 不兼容的类型:com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema 无法转换为com.ververica.cdc.debezium.DebeziumDeserializationSchema

要把类型改为String

2. 找不到方法getStaticJavaEncodingForMysqlCharset(Ljava/lang/String;)Ljava/lang/String

mysql连接器的jar包版本太低,没有这个方法,升级到8.0.31

相关推荐
二进制_博客3 个月前
Flink doesn‘t support ENFORCED mode for PRIMARY KEY constraint
大数据·flink·flinkcdc
LiRuiJie7 个月前
基于Hadoop3.3.4+Flink1.17.0+FlinkCDC3.0.0+Iceberg1.5.0整合,实现数仓实时同步mysql数据
大数据·hadoop·flink·iceberg·flinkcdc
m0_3775959010 个月前
Flinkcdc 实现 MySQL 写入 Doris
mysql·flink·doris·flinkcdc
遇码1 年前
阿里开源的免费数据集成工具——DataX
大数据·开源·kettle·datax·数据集成·flinkcdc·seatunnel
锵锵锵锵~蒋1 年前
实时数据开发|Flink如何实现不同数据源输入--DataSource模块
flink·实时数仓·datasource·datastream
小何才露尖尖角1 年前
pyflink datastream数据流ds经过一系列转换后转为table,t_env.from_data_stream(ds)
datastream·pyflink·`f0` raw·from_data_stre
SelectDB技术团队1 年前
Apache Doris Flink Connector 24.0.0 版本正式发布
大数据·flink·doris·flinkcdc·数据同步
大数据002 年前
FlinkCDC初体验
flink·debezium·flinkcdc·flinksql
Hadoop_Liang2 年前
Flink CDC的使用
大数据·flink·flinkcdc