[Flink/FlinkCDC] 实践总结：Flink 1.12.6 升级 Flink 1.15.4

来源：网络更新时间：2024-11-01 09:32:51

Flink DataStream/API

未变的重要特性

虽然官宣建议弃用 JDK 8，使用JDK 11+；但：仍继续支持 JDK 8

个人猜测：JDK 8 的用户群实在太大，牵一发而动全身，防止步子扯太大，遏制自身项目的发展势头。

依赖模块的变化

版本变化

flink.version : 1.12.6 => 1.15.4
flink.connector.version : 1.12.6 => 1.15.4
flink.connector.cdc.version : 1.3.0 => 2.3.0

Flink Cdc : flink cdc 2.0.0 之后，【groupId、包路径】从 `com.alibaba.ververica` 变为 `com.ververica`

apache flink cdc 1.3.0


	com.alibaba.ververica
	flink-connector-mysql-cdc
	1.3.0

apache flink cdc 2.3.0


	com.alibaba.ververica
	flink-connector-mysql-cdc
	2.3.0

详情参见：

Flink CDC 官网： Flink CDC 包 && Flink && JDK && MYSQL 的版本对照 - 博客园/千千寰宇

各模块摆脱了 scala

详情参见：

https://github.com/apache/flink/blob/release-1.15.4/docs/content.zh/release-notes/flink-1.15.md 【推荐】
https://nightlies.apache.org/flink/flink-docs-release-1.15/release-notes/flink-1.15/

org.apache.flink:flink-clients:${flink.version}
flink-streaming-java:
org.apache.flink:flink-table-api-java-bridge

org.apache.flink:flink-table-api-java-bridge_${scala.version}:${flink.version}

org.apache.flink:flink-connector-kafka:${flink.version}
org.apache.flink:flink-runtime-web:${flink.version}
org.apache.flink:flink-statebackend-rocksdb:${flink.version}
org.apache.flink:flink-table-planner:${flink.version}

org.apache.flink:flink-table-planner-blink_${scala.version}:${flink.version}

停止支持 scala 2.11，但支持 2.12

scala.version = 2.12
flinkversion = 1.15.4

org.apache.flink:flink-connector-hive_${scala.version}:${flink.version}
org.apache.flink:flink-table-api-java-bridge:${flink.version}

相比 flink 1.12.6 时： org.apache.flink:flink-table-api-java-bridge_${scala.version=2.11}:${flink.version=1.12.6}

`table-*-blink` 转正 : flink-table-planner/runtime-blink => flink-table-planner、flink-table-runtime

从 Flink 1.15 开始，发行版包含两个规划器：

flink-table-planner_2.12-${flink.version}.jar : in /opt, 包含查询规划器

flink-table-planner-loader-${flink.version}.jar 【推荐】 : 默认加载 /lib ，包含隐藏在隔离类路径后面的查询计划器

注意：这2个规划器(planner_2)不能同时存在于类路径中。如果将它们都加载到 /lib 表作业 中，则会失败，报错 Could not instantiate the executor. Make sure a planner module is on the classpath 。

Exception in thread "main" org.apache.flink.table.api.TableException: Could not instantiate the executor. Make sure a planner module is on the classpath
    at org.apache.flink.table.api.bridge.internal.AbstractStreamTableEnvironmentImpl.lookupExecutor(AbstractStreamTableEnvironmentImpl.java:108)
    at org.apache.flink.table.api.bridge.java.internal.StreamTableEnvironmentImpl.create(StreamTableEnvironmentImpl.java:100)
    at org.apache.flink.table.api.bridge.java.StreamTableEnvironment.create(StreamTableEnvironment.java:122)
    at org.apache.flink.table.api.bridge.java.StreamTableEnvironment.create(StreamTableEnvironment.java:94)
    at table.FlinkTableTest.main(FlinkTableTest.java:15)
Caused by: org.apache.flink.table.api.ValidationException: Multiple factories for identifier 'default' that implement 'org.apache.flink.table.delegation.ExecutorFactory' found in the classpath.

Ambiguous factory classes are:

org.apache.flink.table.planner.delegation.DefaultExecutorFactory
org.apache.flink.table.planner.loader.DelegateExecutorFactory
    at org.apache.flink.table.factories.FactoryUtil.discoverFactory(FactoryUtil.java:553)
    at org.apache.flink.table.api.bridge.internal.AbstractStreamTableEnvironmentImpl.lookupExecutor(AbstractStreamTableEnvironmentImpl.java:105)
    ... 4 more

Process finished with exit code 1

flink 1.14 版本以后，之前版本 flink-table-*-blink-* 转正。所以：

flink-table-planner-blink => flink-table-planner

flink-table-runtime-blink => flink-table-runtime

`flink-shaded-guava` 模块的版本变化与包冲突问题

若报下列错误，即：版本不同引起的包冲突。

NoClassDefFoundError: org/apache/flink/shaded/guava30/com/google/common/collect/Lists

原因： flink 1.16、1.15 、1.12.6 等版本使用的 flink-shaded-guava 版本基本不一样，且版本不兼容，需要修改 cdc 中的 flink-shaded-guava 版本。

不同flink版本对应 flink-shaded-guava 模块的版本

flink 1.12.6 : flink-shaded-guava 18.0-12.0

flink 1.15.4 : flink-shaded-guava 30.1.1-jre-15.0

flink 1.16.0 : flink-shaded-guava 30.1.1-jre-16.0

如果工程内没有主动引入 org.apache.flink:flink-shaded-guava 工程，则无需关心此问题———— flink-core / flink-runtime / flink-clients 等模块内部会默认引入正确的版本

flink 1.15.4

flink 1.12.6

MySQL JDBC Version : `≥ 8.0.16` => `≥8.0.27`

版本依据: Apache Flink CDC 官网

https://github.com/apache/flink-cdc/tree/release-1.3.0 | ≥8.0.16

https://github.com/apache/flink-cdc/tree/release-2.3.0 | ≥8.0.27

详情参见: Flink CDC 官网： Flink CDC MYSQL 包 && Flink && JDK && MYSQL 的版本对照 - 博客园/千千寰宇

针对报错： Caused by: java.lang.NoSuchMethodError: com.mysql.cj.CharsetMapping.getJavaEncodingForMysqlCharset(Ljava/lang/String;)Ljava/lang/String;

如果MySQL是8.0，fink cdc 2.1 之后由 debezium 连接器引起的问题。

建议统一使用：mysql jdbc 8.0.28


	mysql
	mysql-connector-java
	8.0.28

应用程序的源代码调整

Flink

KafkaRecordDeserializer : 不再存在/不再被支持(flink1.13.0及之后)，并替换为 `KafkaDeserializationSchema` ， `KafkaSourceBuilder` 创建本对象的语法稍有变化

org.apache.flink.connector.kafka.source.reader.deserializer.KafkaRecordDeserializer | flink-connector-kafka_2.11 : 1.12.6

flink 1.12.6
https://github.com/apache/flink/blob/release-1.12.6/flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/deserializer/KafkaRecordDeserializer.java

flink 1.12.7 : 仍存在/支持 KafkaRecordDeserializer

https://github.com/apache/flink/blob/release-1.12.7/flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/deserializer/KafkaRecordDeserializer.java

flink 1.13.0 : 不再存在/不再支持 KafkaRecordDeserializer

https://github.com/apache/flink/tree/release-1.13.0/flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/deserializer

flink 14.0

https://github.com/apache/flink/tree/release-1.14.0/flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/deserializer

flink 1.15.4

https://github.com/apache/flink/tree/release-1.15.4/flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/deserializer/KafkaRecordDeserializationSchema.java

flink-connector-kafka : 3.0.0 | 了解即可，暂无需被此工程干扰上面思路

https://github.com/apache/flink-connector-kafka/blob/v3.0.0/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/deserializer/KafkaRecordDeserializationSchema.java

改造原因、改造思路

在 Apache Flink 1.13.0起， KafkaRecordDeserializer 已被弃用、并被移除。
如果你正在使用的是Flink的旧版本，并且你看到了 KafkaRecordDeserializer 的提示，你应该将其替换为使用 KafkaDeserializationSchema 【推荐】或 KafkaDeserializer 。
KafkaDeserializationSchema 相比 KafkaRecordDeserializer ，多了需要强制实现的2个方法：

boolean isEndOfStream(T var1) : 默认返回 false 即可

T deserialize(ConsumerRecord var1) : 老方法 void deserialize(ConsumerRecord message, Collector out) 内部调用的即本方法

// flink 1.15.4
//org.apache.flink.streaming.connectors.kafka.KafkaDeserializationSchema

package org.apache.flink.streaming.connectors.kafka;

import java.io.Serializable;
import org.apache.flink.annotation.PublicEvolving;
import org.apache.flink.api.common.serialization.DeserializationSchema;
import org.apache.flink.api.java.typeutils.ResultTypeQueryable;
import org.apache.flink.util.Collector;
import org.apache.kafka.clients.consumer.ConsumerRecord;

@PublicEvolving
public interface KafkaDeserializationSchema extends Serializable, ResultTypeQueryable {
    default void open(DeserializationSchema.InitializationContext context) throws Exception {
    }

    boolean isEndOfStream(T var1);

    T deserialize(ConsumerRecord var1) throws Exception;//方法1

    default void deserialize(ConsumerRecord message, Collector out) throws Exception {//方法2
        T deserialized = this.deserialize(message);// 复用/调用的方法1
        if (deserialized != null) {
            out.collect(deserialized);
        }
    }
}

故新适配新增的 T deserialize(ConsumerRecord var1) 方法是很容易的：

import com.xxx.StringUtils;
import org.apache.flink.api.common.serialization.DeserializationSchema;
import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.typeutils.TupleTypeInfo;
//import org.apache.flink.connector.kafka.source.reader.deserializer.KafkaRecordDeserializer;
import org.apache.flink.streaming.connectors.kafka.KafkaDeserializationSchema;
import org.apache.flink.util.Collector;
import org.apache.kafka.clients.consumer.ConsumerRecord;

//public class MyKafkaRecordDeserializer implements KafkaRecordDeserializer> {
public class MyKafkaRecordDeserializer implements KafkaDeserializationSchema> {
/*    @Override
    public void open(DeserializationSchema.InitializationContext context) throws Exception {
        KafkaDeserializationSchema.super.open(context);
    }*/

    @Override
    public boolean isEndOfStream(Tuple2 stringStringTuple2) {
        return false;
    }

    @Override
    public Tuple2 deserialize(ConsumerRecord consumerRecord) throws Exception {//适配新方法1 | 强制
        if(consumerRecord.key() == null){
            return new Tuple2<>("null", StringUtils.bytesToHexString(consumerRecord.value()) );
        }
        return new Tuple2<>( new String(consumerRecord.key() ) , StringUtils.bytesToHexString(consumerRecord.value() ) );
    }

//    @Override
//    public void deserialize(ConsumerRecord consumerRecord, Collector> collector) throws Exception {//适配老方法2 | 非强制
//        collector.collect(new Tuple2<>(consumerRecord.key() == null ? "null" : new String(consumerRecord.key()), StringUtils.bytesToHexString(consumerRecord.value())));
//    }

    @Override
    public TypeInformation> getProducedType() {
        return new TupleTypeInfo<>(BasicTypeInfo.STRING_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO);
    }
}

使用本类、创建本类对象的方式，也稍有变化：

// org.apache.flink.connector.kafka.source.KafkaSourceBuilder | flink-connector-kafka:1.15.4
KafkaSourceBuilder> kafkaConsumerSourceBuilder = KafkaSource.>builder()
	.setTopics(canTopic)
	.setProperties(kafkaConsumerProperties)
	.setClientIdPrefix(Constants.JOB_NAME + "#" + System.currentTimeMillis() + "")
	.setDeserializer( KafkaRecordDeserializationSchema.of(new MyKafkaRecordDeserializer()) ); // flink 1.15.4
	//.setDeserializer(new MyKafkaRecordDeserializer());// flink 1.12.6

推荐文献

Flink1.14新版KafkaSource和KafkaSink实践使用(自定义反序列化器、Topic选择器、序列化器、分区器) - CSDN

https://nightlies.apache.org/flink/flink-docs-release-1.15/zh/docs/connectors/datastream/kafka/

Flink Cdc : flink cdc 2.0.0 之后，【groupId、包路径】从 `com.alibaba.ververica` 变为 `com.ververica`

MySQLSource : 包路径被调整(2.0.0及之后)、类名大小写有变化(flink cdc 2.0.0 及之后)、不再被推荐使用(flink cdc 2.1.0 及之后)

com.alibaba.ververica.cdc.connectors.mysql.MySQLSource | flink cdc 1.3.0

https://github.com/apache/flink-cdc/blob/release-1.3.0/flink-connector-mysql-cdc/src/main/java/com/alibaba/ververica/cdc/connectors/mysql/MySQLSource.java
包路径被调整、类名大小写有变化

https://github.com/apache/flink-cdc/blob/release-2.0.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/MySqlSource.java
com.ververica.cdc.connectors.mysql.MySqlSource 自 flink cdc 2.1.0 及之后 被建议弃用 、但 com.ververica.cdc.connectors.mysql.source.MySqlSource 被推荐可用
https://github.com/apache/flink-cdc/blob/release-2.1.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/MySqlSource.java
Flink CDC这个MySqlSource弃用了，还有别的方式吗？ - aliyun 【推荐】

有两个MysqlSource，一个是弃用的，另一个是可用的，包名不同。 com.ververica.cdc.connectors.mysql.source 这个包下的是可用的。

com.ververica.cdc.connectors.mysql.source.MySqlSource | flink cdc 2.3.0

https://github.com/apache/flink-cdc/blob/release-2.3.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/MySqlSource.java

serverId : 如果选择新的 `MySqlSource` 类，则：其设置入参稍有变化

com.alibaba.ververica.cdc.connectors.mysql.MySQLSource#serverId() | flink cdc 1.3.0

https://github.com/apache/flink-cdc/blob/release-1.3.0/flink-connector-mysql-cdc/src/main/java/com/alibaba/ververica/cdc/connectors/mysql/MySQLSource.java

com.ververica.cdc.connectors.mysql.source.MySqlSource | flink cdc 2.1.0 、 2.3.0 【被推荐使用】

https://github.com/apache/flink-cdc/blob/release-2.1.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/source/MySqlSource.java

没有 serverId 方法
https://github.com/apache/flink-cdc/blob/release-2.1.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/source/MySqlSourceBuilder.java
有 serverId 方法，通过 MySqlSource.builder() 即 MySqlSourceBuilder

/**
 * A numeric ID or a numeric ID range of this database client, The numeric ID syntax is like
 * '5400', the numeric ID range syntax is like '5400-5408', The numeric ID range syntax is
 * required when 'scan.incremental.snapshot.enabled' enabled. Every ID must be unique across all
 * currently-running database processes in the MySQL cluster. This connector joins the MySQL
 * cluster as another server (with this unique ID) so it can read the binlog. By default, a
 * random number is generated between 5400 and 6400, though we recommend setting an explicit
 * value."
 */
public MySqlSourceBuilder serverId(String serverId) {
	this.configFactory.serverId(serverId);
	return this;
}

com.ververica.cdc.connectors.mysql.source.MySqlSource#serverId(int serverId) | flink cdc 2.1.0 【被建议弃用】、flink cdc 2.3.0 【被废止/无法用】

https://github.com/apache/flink-cdc/blob/release-2.1.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/MySqlSource.java

/**
 * A numeric ID of this database client, which must be unique across all currently-running
 * database processes in the MySQL cluster. This connector joins the MySQL database cluster
 * as another server (with this unique ID) so it can read the binlog. By default, a random
 * number is generated between 5400 and 6400, though we recommend setting an explicit value.
 */
public Builder serverId(int serverId) {
	this.serverId = serverId;
	return this;
}

改造Demo: flink 1.3.0

SourceFunction mySqlSource = 
	MySqlSource.builder()
	//数据库地址
	.hostname(jobParameterTool.get("cdc.mysql.hostname"))
	//端口号
	.port(Integer.parseInt(jobParameterTool.get("cdc.mysql.port")))
	//用户名
	.username(jobParameterTool.get("cdc.mysql.username"))
	//密码
	.password(jobParameterTool.get("cdc.mysql.password"))
	//监控的数据库
	.databaseList(jobParameterTool.get("cdc.mysql.databaseList"))
	//监控的表名，格式数据库.表名
	.tableList(jobParameterTool.get("cdc.mysql.tableList"))
	//虚拟化方式
	.deserializer(new MySQLCdcMessageDeserializationSchema())
	//时区
	.serverTimeZone("UTC")
	.serverId( randomServerId(5000, Constants.JOB_NAME + "#xxxConfig") )
	.startupOptions(StartupOptions.latest())
	.build();


public static Integer randomServerId(int interval, String jobCdcConfigDescription){
	//startServerId ∈[ interval + 0, interval + interval)
	//int serverId = RANDOM.nextInt(interval) + interval; // RANDOM.nextInt(n) : 生成介于 [0,n) 区间的随机整数
	//serverId = [ 7000 + 0, Integer.MAX_VALUE - interval)
	int serverId = RANDOM.nextInt(Integer.MAX_VALUE - interval - 7000) + 7000;
	log.info("Success to generate random server id result! serverId : {}, interval : {}, jobCdcConfigDescription : {}"
			, serverId , interval , jobCdcConfigDescription );
	return serverId;
}

改造Demo: flink 2.3.0

MySqlSource mySqlSource = 
	MySqlSource.builder()
	//数据库地址
	.hostname(jobParameterTool.get("cdc.mysql.hostname"))
	//端口号
	.port(Integer.parseInt(jobParameterTool.get("cdc.mysql.port")))
	//用户名
	.username(jobParameterTool.get("cdc.mysql.username"))
	//密码
	.password(jobParameterTool.get("cdc.mysql.password"))
	//监控的数据库
	.databaseList(jobParameterTool.get("cdc.mysql.databaseList"))
	//监控的表名，格式数据库.表名
	.tableList(jobParameterTool.get("cdc.mysql.tableList"))
	//虚拟化方式
	.deserializer(new MySQLCdcMessageDeserializationSchema())
	//时区
	.serverTimeZone("UTC")
	.serverId( randomServerIdRange(5000, Constants.JOB_NAME + "#xxxConfig") )
	.startupOptions(StartupOptions.latest())
	.build();


//新增强制要求: interval >= 本算子的并行度
public static String randomServerIdRange(int interval, String jobCdcConfigDescription){
	// 生成1个起始随机数 |
	//startServerId = [interval + 0, interval + interval )
	//int startServerId = RANDOM.nextInt(interval) + interval; // RANDOM.nextInt(n) : 生成介于 [0,n) 区间的随机整数
	//startServerId = [ 7000 + 0, Integer.MAX_VALUE - interval)
	int startServerId = RANDOM.nextInt(Integer.MAX_VALUE - interval - 7000) + 7000;

	//endServerId ∈ [startServerId, startServerId + interval];
	int endServerId = startServerId + interval;
	log.info("Success to generate random server id result! startServerId : {},endServerId : {}, interval : {}, jobCdcConfigDescription : {}"
			, startServerId, endServerId , interval , jobCdcConfigDescription );
	return String.format("%d-%d", startServerId, endServerId);
}

MySQLSourceBuilder#build 方法: 返回类型存在变化: `SourceFunction/DebeziumSourceFunction` => `MySqlSource`

org.apache.flink.streaming.api.functions.source.SourceFunction => com.ververica.cdc.connectors.mysql.source.MySqlSource

//com.alibaba.ververica.cdc.connectors.mysql.MySQLSource.Builder#build | flink cdc 1.3.0
// 返回: com.alibaba.ververica.cdc.debezium.DebeziumSourceFunction
// public class DebeziumSourceFunction extends RichSourceFunction implements CheckpointedFunction, CheckpointListener, ResultTypeQueryable
//public abstract class org.apache.flink.streaming.api.functions.source.RichSourceFunction extends AbstractRichFunction implements SourceFunction
public DebeziumSourceFunction build() {
	Properties props = new Properties();
	props.setProperty("connector.class", MySqlConnector.class.getCanonicalName());
	props.setProperty("database.server.name", "mysql_binlog_source");
	props.setProperty("database.hostname", (String)Preconditions.checkNotNull(this.hostname));
	props.setProperty("database.user", (String)Preconditions.checkNotNull(this.username));
	props.setProperty("database.password", (String)Preconditions.checkNotNull(this.password));
	props.setProperty("database.port", String.valueOf(this.port));
	props.setProperty("database.history.skip.unparseable.ddl", String.valueOf(true));
	if (this.serverId != null) {
		props.setProperty("database.server.id", String.valueOf(this.serverId));
	}
	...
}


//com.ververica.cdc.connectors.mysql.source.MySqlSourceBuilder#build | flink cdc 2.3.0
//// 返回: 
public MySqlSource build() {
	return new MySqlSource(this.configFactory, (DebeziumDeserializationSchema)Preconditions.checkNotNull(this.deserializer));
}

使用变化Demo: Flink cdc 1.3.0

mysqlSource 想要监听 mysql 表结构变更（例如：添加新的字段），要怎么办？设置 - aliyun

Properties properties = new Properties();
properties.setProperty("database.hostname", "localhost");
properties.setProperty("database.port", "3306");
properties.setProperty("database.user", "your_username");
properties.setProperty("database.password", "your_password");
properties.setProperty("database.server.id", "1"); // 设置唯一的 server id
properties.setProperty("database.server.name", "mysql_source");

DebeziumSourceFunction sourceFunction = MySQLSource.builder()
    .hostname("localhost")
    .port(3306)
    .username("your_username")
    .password("your_password")
    .databaseList("your_database")
    .tableList("your_table")
    .includeSchemaChanges(true) // 开启监听表结构变更
    .deserializer(new StringDebeziumDeserializationSchema())
    .build();

DataStreamSource stream = env.addSource(sourceFunction);//可以使用 addSource

stream.print();
env.execute("MySQL CDC Job");

使用变化Demo: Flink cdc 2.3.0

https://flink-tpc-ds.github.io/flink-cdc-connectors/release-2.3/content/connectors/mysql-cdc(ZH).html
无法使用 env.addSource(SourceFunction, String sourceName) ，只能使用 env.fromSource(Source source, WatermarkStrategy timestampsAndWatermarks, String sourceName)

import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
import com.ververica.cdc.connectors.mysql.source.MySqlSource;

public class MySqlSourceExample {
  public static void main(String[] args) throws Exception {
    MySqlSource mySqlSource = MySqlSource.builder()
        .hostname("yourHostname")
        .port(yourPort)
        .databaseList("yourDatabaseName") // 设置捕获的数据库， 如果需要同步整个数据库，请将 tableList 设置为 ".*".
        .tableList("yourDatabaseName.yourTableName") // 设置捕获的表
        .username("yourUsername")
        .password("yourPassword")
        .deserializer(new JsonDebeziumDeserializationSchema()) // 将 SourceRecord 转换为 JSON 字符串
        .build();

    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

    // 设置 3s 的 checkpoint 间隔
    env.enableCheckpointing(3000);

    env
      .fromSource(mySqlSource, WatermarkStrategy.noWatermarks(), "MySQL Source")
      // 设置 source 节点的并行度为 4
      .setParallelism(4)
      .print().setParallelism(1); // 设置 sink 节点并行度为 1 

    env.execute("Print MySQL Snapshot + Binlog");
  }
}

StartupOptions : 包路径被调整(2.0.0及之后)

import com.alibaba.ververica.cdc.connectors.mysql.table.StartupOptions | flink 1.3.0

https://github.com/apache/flink-cdc/blob/release-1.3.0/flink-connector-mysql-cdc/src/main/java/com/alibaba/ververica/cdc/connectors/mysql/table/StartupOptions.java

com.ververica.cdc.connectors.mysql.table.StartupOptions | flink 2.3.0

https://github.com/apache/flink-cdc/blob/release-2.3.0/flink-connector-mysql-cdc/src/main/java/com/ververica/cdc/connectors/mysql/table/StartupOptions.java

DebeziumDeserializationSchema : 包路径被调整(flink-cdc2.0.0及之后)

com.alibaba.ververica.cdc.debezium.DebeziumDeserializationSchema | flink cdc 1.3.0

com.ververica:flink-connector-debezium:1.3.0
https://github.com/apache/flink-cdc/blob/release-1.3.0/flink-connector-debezium/src/main/java/com/alibaba/ververica/cdc/debezium/DebeziumDeserializationSchema.java

com.ververica.cdc.debezium.DebeziumDeserializationSchema | flink cdc 2.3.0

com.ververica:flink-connector-debezium:2.3.0
https://github.com/apache/flink-cdc/blob/release-2.3.0/flink-connector-debezium/src/main/java/com/ververica/cdc/debezium/DebeziumDeserializationSchema.java

X 参考文献

Flink+Flink CDC版本升级的依赖问题总结 - CSDN
apache flink cdc

https://github.com/apache/flink-cdc

https://github.com/apache/flink-cdc/blob/master/docs/content/docs/faq/faq.md

https://github.com/apache/flink-cdc/tree/master/flink-cdc-connect/flink-cdc-source-connectors/flink-sql-connector-mysql-cdc

com.alibaba.ververica:flink-connector-mysql-cdc:1.3.0

https://github.com/apache/flink-cdc/blob/release-1.3.0/flink-connector-mysql-cdc/pom.xml 【推荐】 Flink 1.12.6

com.ververica:flink-connector-mysql-cdc:2.0

MYSQL (Database: 5.7, 8.0.x / JDBC Driver: 8.0.16 ) | Flink 1.12 + | JDK 8+
https://github.com/apache/flink-cdc/tree/release-2.0
https://github.com/apache/flink-cdc/blob/release-2.0/flink-connector-mysql-cdc/pom.xml

com.ververica:flink-connector-mysql-cdc:2.3.0

https://github.com/apache/flink-cdc/blob/release-2.3.0/flink-connector-mysql-cdc/pom.xml 【推荐】 Flink 1.15.4

org.apache.flink:flink-connector-mysql-cdc:${flink.cdc.version}

https://ververica.github.io/flink-cdc-connectors/master/content/about.html [已废止]