FlinkCDC的分析和应用代码

前言：原本想讲如何基于Flink实现定制化计算引擎的开发，并以FlinkCDC为例介绍；发现这两个在表达上不知以谁为主，所以先分析FlinkCDC的应用场景和技术实现原理，下一篇再去分析Flink能在哪些方面，做定制化计算引擎的开发操作。本文将从FlinkCDC应用场景开始，然后讲述其基于Flink的实现原理和代码应用，为下一篇介绍基于Flink开发定制化引擎做铺垫。

一、FlinkCDC应用场景

经常有同事或朋友问，Flink和FlinkCDC有什么区别？

Flink是一个流数据处理计算框架，FlinkCDC是数据采集工具：

Flink应用场景对比的是Storm、Spark；

FlinkCDC应用场景对比的是Sqoop、Canal、Maxwell和KafkaConnectSource、Debezium等；

FlinkCDC是Flink社区伙伴对数据采集需求，开发的一个SDK工具，让Flink在数据捕捉场景，使用起来更方便一些。

1.1 CDC的应用场景分析

       CDC的英文名是Change Data Capture (变化数据获取)；解决的应用场景，是对存储中间件中数据的采集，比如Mysql、Orcle、PGSql、MongoDB等中间件；

采集的方式分为基于查询和基于BinLog两种；

以mysql的数据采集为例：可以通过jdbc批次查询，也可以通过Binlog解析增量数据采集；

两者的一些特性对比如下：

基于查询的CDC直接获取数据，基于binlog的采集需要开启binlog服务。

1.2 FlinkCDC的应用分析

       FlinkCDC和Canal实现的应用场景需求是差不多的，都是通过binlog采集增量数据；

但是可用性上的不同是：  

对于cannal类似的采集服务需要三步:

• 1.开启mysql的binlog
• 2.将数据写到kafka
• 3.用flink订阅kafka中的数据进行业务需求处理

对于FlinkCDC：只需要在binlog开启后，直接在一个Flink任务内做业务处理（可以写到kafka处理也行）；

       所有如cannal的采集功能服务，都需要单独维护一套服务，增加了运维负担，FlinkCDC可以当作任务部署到集群，大幅减轻了数据采集的应用难度；

用一个任务就完成这个应用功能：

二、FlinkCDC技术分析与本地操作

2.1 FlinkCDC的技术架构分析

       与Canal这些提供服务能力的服务不同，FlinkCdc只是一个任务，可以简单的开发和部署。

       Flink是借用了Debezium的功能，Debezium是一个可轻量级嵌入代码逻辑的服务，将Debezium的采集功能，用Flink的sourceFunction包装，然后打包成SDK提供给Flink开发使用；

       借用Flink自己的算子和sink能力，可以将采集到的数据以Flink的特性加工数据，并将数据写入Flink内置的connect组件，sink到服务里，如Kafka、Pulser、ES、RabbitMQ、MongoDB等。

2.2 本地操作

2.2.1准备mysql数据库表和数据

use flink_test;
#检测binlog是否开启
show variables like '%log_bin%'#构建测试表
CREATE TABLE `event_info` (`id` int NOT NULL AUTO_INCREMENT,`name` varchar(255) NOT NULL,`category` varchar(512) DEFAULT NULL,`pv` int DEFAULT 0,`uv` int DEFAULT 0,PRIMARY KEY (`id`)
) ENGINE=InnoDB  DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;#写入数据
insert  into `event_info`(`id`,`name`,`category`,`pv`,`uv`) values 
(1,'aaa','nfh',20,8),
(2,'bbb','dfgf',30,2),
(3,'ccc','fsd',40,4),
(4,'ddd','afs',50,7),
(5,'eee','asfa',60,3)
(6,'aaa','nfh',20,8),
(7,'bbb','dfgf',30,2),
(8,'ccc','fsd',40,4),
(9,'ddd','afs',50,7),
(10,'eee','asfa',60,3);

2.2.2 pom文件

       注意Flink和FlinkCDC的版本映射，很多显示的可以关联的版本之间是冲突的，这是一个很繁琐的工作，我调试各个版本之间的映射，花了一天左右的时间[求赞求收藏]；

下面这是Flink1.14.5版本和FlinkCDC2.2.1版本已经调好的依赖：

<?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>changedateDoris</artifactId><version>1.0-SNAPSHOT</version><properties><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><scala.version>2.12</scala.version><java.version>1.8</java.version><flink.version>1.14.5</flink.version><fastjson.version>1.2.62</fastjson.version><hadoop.version>2.8.3</hadoop.version><scope.mode>compile</scope.mode><slf4j.version>1.7.30</slf4j.version></properties><dependencies><!--        springboot 依赖--><!-- flink  --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-planner_${scala.version}</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-scala_${scala.version}</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-clients_${scala.version}</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-jdbc_${scala.version}</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-kafka_${scala.version}</artifactId><version>${flink.version}</version></dependency><dependency><groupId>com.alibaba</groupId><artifactId>fastjson</artifactId><version>${fastjson.version}</version></dependency><!-- Add log dependencies when debugging locally --><dependency><groupId>org.slf4j</groupId><artifactId>slf4j-api</artifactId><version>${slf4j.version}</version></dependency><dependency><groupId>org.slf4j</groupId><artifactId>slf4j-log4j12</artifactId><version>${slf4j.version}</version></dependency><!-- mysql-connector --><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>8.0.12</version></dependency><dependency><groupId>com.ververica</groupId><artifactId>flink-sql-connector-mysql-cdc</artifactId><version>2.2.1 </version><exclusions><exclusion><artifactId>flink-shaded-guava</artifactId><groupId>org.apache.flink</groupId></exclusion></exclusions></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-runtime-web_${scala.version}</artifactId><version>${flink.version}</version></dependency></dependencies><build>
<!--        <filters>-->
<!--            <filter>${project.basedir}/src/main/resources/env/application-${profileActive}.properties</filter>-->
<!--        </filters>--><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-shade-plugin</artifactId><version>2.1</version><executions><execution><phase>package</phase><goals><goal>shade</goal></goals><configuration><filters><filter><artifact>*:*</artifact><excludes><exclude>META-INF/*.SF</exclude><exclude>META-INF/*.DSA</exclude><exclude>META-INF/*.RSA</exclude></excludes></filter></filters><artifactSet><includes><include>*:*</include></includes><excludes><exclude>org.slf4j:slf4j-api:jar:</exclude></excludes></artifactSet><transformers><transformerimplementation="org.apache.maven.plugins.shade.resource.AppendingTransformer"><resource>META-INF/spring.handlers</resource></transformer><transformerimplementation="org.apache.maven.plugins.shade.resource.AppendingTransformer"><resource>META-INF/spring.schemas</resource></transformer><transformerimplementation="org.apache.maven.plugins.shade.resource.AppendingTransformer"><resource>META-INF/spring.factories</resource></transformer></transformers></configuration></execution></executions></plugin><plugin><artifactId>maven-resources-plugin</artifactId><configuration><encoding>utf-8</encoding><useDefaultDelimiters>true</useDefaultDelimiters><delimiters><delimiter>$[*]</delimiter></delimiters></configuration></plugin><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-assembly-plugin</artifactId><executions><execution><phase>package</phase><goals><goal>single</goal></goals><configuration><descriptorRefs><descriptorRef>jar-with-dependencies</descriptorRef></descriptorRefs></configuration></execution></executions></plugin><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-compiler-plugin</artifactId><configuration><source>8</source><target>8</target></configuration></plugin></plugins></build>
</project>

2.2.3 java代码

package yto.com.net.demo;import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import com.ververica.cdc.connectors.mysql.source.MySqlSource;
import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.configuration.RestOptions;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;public class mysqlBinlogRead {private static final Logger log = LoggerFactory.getLogger(mysqlBinlogRead.class);public static void main(String[] args) throws Exception {MySqlSource<String> mySqlSource = MySqlSource.<String>builder().hostname("ip").port(3306).databaseList("flink_test").tableList("flink_test.event_info").username("mysqlUser").password("password").deserializer(new JsonDebeziumDeserializationSchema()) // converts SourceRecord to JSON String
//                .startupOptions(StartupOptions.earliest()).build();Configuration configuration = new Configuration();configuration.setInteger(RestOptions.PORT, 8083);StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(configuration);
//        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();env.setParallelism(1);// enable checkpointenv.enableCheckpointing(10000);DataStreamSource<String> cdcSource = env.fromSource(mySqlSource, WatermarkStrategy.noWatermarks(), "MySQL CDC Source");SingleOutputStreamOperator<String> process = cdcSource.process(new ProcessFunction<String, String>() {@Overridepublic void processElement(String row, ProcessFunction<String, String>.Context context, Collector<String> collector) throws Exception {JSONObject rowJson = JSON.parseObject(row);String op = rowJson.getString("op");JSONObject source = rowJson.getJSONObject("source");String table = source.getString("table");}});cdcSource.print("message=:");env.execute("flinkCdc Read message");}}

2.2.4 运行结果

如图所示，已经写入库的结果通过connect获取，增量数据通过binlog获取；

注意：表中的历史数据过多，全量读取的时候将会内存溢出。