代码收藏家 使用Flink CDC抽取Oracle数据：一份Oracle CDC详细文档
摘要
Flink一般常用的集群模式有 flink on yarn 和standalone模式。
yarn模式需要搭建hadoop集群，该模式主要依靠hadoop的yarn资源调度来实现flink的高可用，达到资源的充分利用和合理分配。一般用于生产环境。
standalone模式主要利用flink自带的分布式集群来提交任务，该模式的优点是不借助其他外部组件，缺点是资源不足需要手动处理。
本文主要以 standalone集群模式为例。
觉得有帮助的话，传播给更多的小伙伴
提示：flinkcdc获取oracle date日期字段的值存在时差而且是long型
一种方法：改java代码new Timestamp((Long) 接收的值 – 8 * 60 * 60 * 1000)
另一种方法：flink-conf.yaml添加（未验证）
env.java.opts.taskmanager: -Duser.timezone=GMT+08
1.项目添加flink依赖
pom.xml
<?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>com.test</groupId>
<artifactId>test-cdc</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<java.version>1.8</java.version>
<maven.compiler.source>${java.version}</maven.compiler.source>
<maven.compiler.target>${java.version}</maven.compiler.target>
<fastjson.vsersion>1.2.68</fastjson.vsersion>
<druid.version>1.2.8</druid.version>
<flink.version>1.14.3</flink.version>
<flinkcdc.vsersion>2.3.0</flinkcdc.vsersion>
<scala.version>2.12</scala.version>
<postgresql.version>42.2.12</postgresql.version>
</properties>
<dependencies>
<dependency>
<groupId>org.postgresql</groupId>
<artifactId>postgresql</artifactId>
<version>${postgresql.version}</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid-spring-boot-starter</artifactId>
<version>${druid.version}</version>
</dependency>
<dependency>
<groupId>com.google.code.gson</groupId>
<artifactId>gson</artifactId>
<version>2.8.9</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-kafka_${scala.version}</artifactId>
<version>${flink.version}</version>
<exclusions>
<exclusion>
<artifactId>kafka-clients</artifactId>
<groupId>org.apache.kafka</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>com.ververica</groupId>
<artifactId>flink-connector-oracle-cdc</artifactId>
<version>${flinkcdc.vsersion}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-jdbc_${scala.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-api-java-bridge_${scala.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<!-- <dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-planner-blink_${scala.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>8.0.15</version>
</dependency>
<dependency>
<groupId>com.oracle.database.jdbc</groupId>
<artifactId>ojdbc10</artifactId>
<version>19.10.0.0</version>
</dependency>
-->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-java_${scala.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients_${scala.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-cep_${scala.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-json</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>${fastjson.vsersion}</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.20</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-logging</artifactId>
<version>2.1.5.RELEASE</version>
</dependency>
<!-- <dependency>-->
<!-- <groupId>org.slf4j</groupId>-->
<!-- <artifactId>slf4j-api</artifactId>-->
<!-- <version>1.7.32</version>-->
<!-- </dependency>-->
<!-- slf4j 内置的简单实现 -->
<!-- <dependency>-->
<!-- <groupId>org.slf4j</groupId>-->
<!-- <artifactId>slf4j-simple</artifactId>-->
<!-- <version>1.7.32</version>-->
<!-- </dependency>-->
<!-- <dependency>-->
<!-- <groupId>ch.qos.logback</groupId>-->
<!-- <artifactId>logback-core</artifactId>-->
<!-- <version>1.2.11</version>-->
<!-- </dependency>-->
<!-- <dependency>-->
<!-- <groupId>ch.qos.logback</groupId>-->
<!-- <artifactId>logback-classic</artifactId>-->
<!-- <version>1.2.11</version>-->
<!-- </dependency>-->
<dependency>
<groupId>org.springframework</groupId>
<artifactId>spring-context</artifactId>
<version>5.3.22</version>
<scope>compile</scope>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>2.12.7.1</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>
</project>
2.oracle开启日志归档
sqlplus / as sysdba
启用日志归档
alter system set db_recovery_file_dest_size = 10G;
alter system set db_recovery_file_dest = '/home/oracle/oracle-data-test' scope=spfile;
shutdown immediate;
startup mount;
alter database archivelog;
alter database open;
检查日志归档是否开启
archive log list;
为捕获的数据库启用补充日志记录,以便数据更改捕获更改的数据库行之前的状态,下面说明了如何在数据库级别进行配置。
ALTER DATABASE ADD SUPPLEMENTAL LOG DATA;
创建表空间
CREATE TABLESPACE logminer_tbs DATAFILE '/home/oracle/logminer_tbs.dbf' SIZE 25M REUSE AUTOEXTEND ON MAXSIZE UNLIMITED;
创建用户flinkcdc绑定表空间LOGMINER_TBS
CREATE USER flinkcdc IDENTIFIED BY flinkcdc DEFAULT TABLESPACE LOGMINER_TBS QUOTA UNLIMITED ON LOGMINER_TBS;
授予flinkcdc用户dba的权限
grant connect,resource,dba to flinkcdc;
并授予权限
GRANT CREATE SESSION TO flinkcdc;
GRANT SELECT ON V_$DATABASE to flinkcdc;
GRANT FLASHBACK ANY TABLE TO flinkcdc;
GRANT SELECT ANY TABLE TO flinkcdc;
GRANT SELECT_CATALOG_ROLE TO flinkcdc;
GRANT EXECUTE_CATALOG_ROLE TO flinkcdc;
GRANT SELECT ANY TRANSACTION TO flinkcdc;
GRANT EXECUTE ON SYS.DBMS_LOGMNR TO flinkcdc;
GRANT SELECT ON V_$LOGMNR_CONTENTS TO flinkcdc;
GRANT CREATE TABLE TO flinkcdc;
GRANT LOCK ANY TABLE TO flinkcdc;
GRANT ALTER ANY TABLE TO flinkcdc;
GRANT CREATE SEQUENCE TO flinkcdc;
GRANT EXECUTE ON DBMS_LOGMNR TO flinkcdc;
GRANT EXECUTE ON DBMS_LOGMNR_D TO flinkcdc;
GRANT SELECT ON V_$LOG TO flinkcdc;
GRANT SELECT ON V_$LOG_HISTORY TO flinkcdc;
GRANT SELECT ON V_$LOGMNR_LOGS TO flinkcdc;
GRANT SELECT ON V_$LOGMNR_CONTENTS TO flinkcdc;
GRANT SELECT ON V_$LOGMNR_PARAMETERS TO flinkcdc;
GRANT SELECT ON V_$LOGFILE TO flinkcdc;
GRANT SELECT ON V_$ARCHIVED_LOG TO flinkcdc;
GRANT SELECT ON V_$ARCHIVE_DEST_STATUS TO flinkcdc;
修改以下表让其支持增量日志
ALTER TABLE test.table1 SUPPLEMENTAL LOG DATA (ALL) COLUMNS;
ALTER TABLE test.table2 ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS;
ALTER TABLE test.table3 ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS;
3.Flink集群搭建
| 版本类型 | 版本号 |
|---|---|
| 项目版本 | flink1.14.3、scala2.12、flinkoraclecdc2.3.0 |
| flink集群版本 | flink1.14.3 |
| hostname | ip | 配置 |
|---|---|---|
| yy1 | 10.201.1.1 | StandaloneSessionClusterEntrypoint、Taskmanager |
| yy2 | 10.201.1.2 | Taskmanager |
| yy3 | 10.201.1.3 | Taskmanager |
3.1 Flink下载安装并配置
1） 登录linux
2） cd /usr/local/
3） wget https://archive.apache.org/dist/flink/flink-1.14.3/flink-1.14.3-bin-scala_2.12.tgz
4） tar –zxvf flink-1.14.3-bin-scala_2.12.tgz
5） cd flink-1.14.3/conf
6） vi flink-conf.yaml
注意：冒号后面有个空格
jobmanager.rpc.address: yy1
# 这个参数比较重要，这个是总内存
jobmanager.memory.process.size: 10gb
# taskmanager大小
taskmanager.memory.process.size: 3gb
# 打开注释，并修改保存点存储目录
# 配置hdfs目录，一般用于搭建了hadoop集群
#state.savepoint.dir: hdfs://yz1:9000/flink/cdc
#存储目录设为服务器本地
state.checkpoints.dir: file:///bigdata/checkpoints
state.savepoints.dir: file:///bigdata/savepoints
#设置检查点保存的数据 默认是一个，增加下面
#state.checkpoints.num-retained: 3
# 修改slot的个数
taskmanager.numberOfTaskSlots: 3
#如果不想用flink默认目录/temp 可以自己配置如下并打开
# io.tmp.dirs: /data1/flink/tmp
# env.pid.dir: /data1/flink/env
# web.tmpdir: /data1/flink/tmp
#上传的jar包目录，这样不用每次都上传
#web.upload.dir: /data1/flink/jar
7）修改masters和workers 文件
masters内容：
yy1:8081
workers内容:
yy1
yy2
yy3
8）复制到其他节点
scp -rq flink-1.14.3 yy2:/usr/local
scp -rq flink-1.14.3 yy3:/usr/local
9）每个节点上建立flink-1.14.3目录的链接（每个节点操作）
ln -s flink-1.14.3 flink
10）配置flink的环境变量(每个节点操作)
vi /etc/profile
#配置如下
export JAVA_HOME=/usr/local/jdk18
export FLINK_HOME=/usr/local/flink
export JRE_HOME=$JAVA_HOME/jre
export CLASS_PATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:$JRE_HOME/lib
export PATH=$PATH:$JAVA_HOME/bin:$JRE_HOME/bin:$FLINK_HOME/bin
11）使其修改生效（每个节点操作）
source /etc/profile
12）在master节点上启动flink集群
start-cluster.sh
13）打开flink任务管理界面
http://10.201.1.1:8081
14)在界面提交任务
15）效果图
4. Flink 提交任务的常用命令
4.1 stantalone模式
flink run –m [ip]:[端口] -p[并行数] -c[main方法所在类的全路径] [jar文件的绝对路径]
flink run -m 10.201.1.1:8090 -p 1 -c com.test.TestStudent /bigdata/testCDC-1.0-SNAPSHOT-jar-with-dependencies.jar
stantalone 模式下savepoint,取消任务的同时savepoint
flink cancel -s 282c334dd9dc9ae04c3d6cbe1bfdf8f2
暂停任务的同时savepoint
flink savepoint 282c334dd9dc9ae04c3d6cbe1bfdf8f2
4.2 flink on yarn模式
flink run -t yarn-per-job -c com.test.TestStudent /bigdata/testCDC-1.0-SNAPSHOT-jar-with-dependencies.jar
Flink on yarn 模式下savepoint
flink savepoint 8f1d21525dc3bebf22f9c3a617326142 hdfs:///flink/cdc -yid application_1657250519562_0007
从保存点恢复
$ bin/flink run -s :savepointPath [:runArgs]
flink run -s hdfs:///flink/cdc/savepoint-a4f769-58ee3095ee02
5.完成
6.问题汇总
1）报错信息：ERROR: Attempting to operate on hdfs namenode as root
ERROR: but there is no HDFS_NAMENODE_USER defined. Aborting operation.
Starting datanodes
ERROR: Attempting to operate on hdfs datanode as root
ERROR: but there is no HDFS_DATANODE_USER defined. Aborting operation.
Starting secondary namenodes [hadoop]
ERROR: Attempting to operate on hdfs secondarynamenode as root
ERROR: but there is no HDFS_SECONDARYNAMENODE_USER defined. Aborting operation.
2018-07-16 05:45:04,628 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform… using builtin-java classes where applicable
Starting resourcemanager
ERROR: Attempting to operate on yarn resourcemanager as root
ERROR: but there is no YARN_RESOURCEMANAGER_USER defined. Aborting operation.
Starting nodemanagers
ERROR: Attempting to operate on yarn nodemanager as root
ERROR: but there is no YARN_NODEMANAGER_USER defined. Aborting operation.
解决：
vi /etc/profile 加入以下信息，然后source /etc/profile
export HDFS_NAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=root
export HDFS_JOURNALNODE_USER=root
export HDFS_ZKFC_USER=root
export HADOOP_CLASSPATH=hadoop classpath
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
2）报错信息：java.lang.IllegalStateException: Trying to access closed classloader.
Please check if you store classloaders directly or indirectly in static fields.
If the stacktrace suggests that the leak occurs in a third party library and cannot be fixed immediately,
you can disable this check with the configuration ‘classloader.check-leaked-classloader’.
解决：
修改flink配置文件：vi flink-conf.yaml
增加：classloader.check-leaked-classloader: false
3）File /tmp/logs/root/logs-tfile/application_1656991740104_0001 does not exist.
File /tmp/logs/root/bucket-logs-tfile/0001/application_1656991740104_0001 does not exist.
Can not find any log file matching the pattern: [ALL] for the application: application_1656991740104_0001
Can not find the logs for the application: application_1656991740104_0001 with the appOwner: root
解决：
yarn-site.xml 增加以下
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
4）报错信息：DebeziumException: Supplemental logging not properly configured. Use: ALTER DATABASE ADD SUPPLEMENTAL LOG DATA
解决：
ALTER TABLE 表名 ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS;
ALTER DATABASE ADD SUPPLEMENTAL LOG DATA;
