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commit f46e473f776f09407092f52568a018392308552b
Author: jiafeng.zhang <zhang...@gmail.com>
AuthorDate: Mon Jul 18 18:15:39 2022 +0800
blog publish
blog publish
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.../flnkcdc-mysql-doris-exactlyonce.md | 1111 ++++++++++++++++++++
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@@ -0,0 +1,707 @@
+---
+{
+ "title": "Apache Doris 整合 FLINK CDC + Iceberg 构建实时湖仓一体的联邦查询",
+ "description": "这篇教程将展示如何使用 Flink CDC + Iceberg + Doris
构建实时湖仓一体的联邦查询分析，Doris
1.1版本提供了Iceberg的支持，本文主要展示Doris和Iceberg怎么使用，同时本教程整个环境是都基于伪分布式环境搭建，大家按照步骤可以一步步完成。完整体验整个搭建操作的过程.",
+ "date": "2022-06-24",
+ "metaTitle": "Apache Doris 整合 FLINK CDC + Iceberg 构建实时湖仓一体的联邦查询",
+ "isArticle": true,
+ "language": "zh-CN",
+ "author": "张家锋",
+ "layout": "Article",
+ "sidebar": true,
+ "zhCategories": "PracticalCases"
+}
+---
+
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements. See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership. The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied. See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+# Apache Doris 整合 FLINK CDC + Iceberg 构建实时湖仓一体的联邦查询
+
+## 1.概览
+
+这篇教程将展示如何使用 Flink CDC + Iceberg + Doris 构建实时湖仓一体的联邦查询分析，Doris
1.1版本提供了Iceberg的支持，本文主要展示Doris和Iceberg怎么使用，同时本教程整个环境是都基于伪分布式环境搭建，大家按照步骤可以一步步完成。完整体验整个搭建操作的过程。
+
+### 1.1 软件环境
+
+本教程的演示环境如下：
+
+1. Centos7
+2. Apahce doris 1.1
+3. Hadoop 3.3.3
+4. hive 3.1.3
+5. Fink 1.14.4
+6. flink-sql-connector-mysql-cdc-2.2.1
+7. Apache Iceber 0.13.2
+8. JDK 1.8.0_311
+9. MySQL 8.0.29
+
+```shell
+wget
https://archive.apache.org/dist/hadoop/core/hadoop-3.3.3/hadoop-3.3.3.tar.gz
+wget
https://archive.apache.org/dist/hive/hive-3.1.3/apache-hive-3.1.3-bin.tar.gz
+wget
https://dlcdn.apache.org/flink/flink-1.14.4/flink-1.14.4-bin-scala_2.12.tgz
+wget
https://search.maven.org/remotecontent?filepath=org/apache/iceberg/iceberg-flink-runtime-1.14/0.13.2/iceberg-flink-runtime-1.14-0.13.2.jar
+wget
https://repository.cloudera.com/artifactory/cloudera-repos/org/apache/flink/flink-shaded-hadoop-3-uber/3.1.1.7.2.9.0-173-9.0/flink-shaded-hadoop-3-uber-3.1.1.7.2.9.0-173-9.0.jar
+```
+
+### 1.2 系统架构
+
+我们整理架构图如下
+
+
+
+1. 首先我们从Mysql数据中使用Flink 通过 Binlog完成数据的实时采集
+2. 然后再Flink 中创建 Iceberg 表，Iceberg的元数据保存在hive里
+3. 最后我们在Doris中创建Iceberg外表
+4. 在通过Doris
统一查询入口完成对Iceberg里的数据进行查询分析，供前端应用调用，这里iceberg外表的数据可以和Doris内部数据或者Doris其他外部数据源的数据进行关联查询分析
+
+Doris湖仓一体的联邦查询架构如下：
+
+
+
+1. Doris 通过 ODBC 方式支持：MySQL，Postgresql，Oracle ，SQLServer
+2. 同时支持 Elasticsearch 外表
+3. 1.0版本支持Hive外表
+4. 1.1版本支持Iceberg外表
+5. 1.2版本支持Hudi 外表
+
+## 2.环境安装部署
+
+### 2.1 安装Hadoop、Hive
+
+```
+tar zxvf hadoop-3.3.3.tar.gz
+tar zxvf apache-hive-3.1.3-bin.tar.gz
+```
+
+配置系统环境变量
+
+```
+export HADOOP_HOME=/data/hadoop-3.3.3
+export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
+export HADOOP_HDFS_HOME=$HADOOP_HOME
+export HIVE_HOME=/data/hive-3.1.3
+export PATH=$PATH:$HADOOP_HOME/bin:$HIVE_HOME/bin:$HIVE_HOME/conf
+```
+
+### 2.2 配置hdfs
+
+#### 2.2.1 core-site.xml
+
+vi etc/hadoop/core-site.xml
+
+```xml
+<configuration>
+ <property>
+ <name>fs.defaultFS</name>
+ <value>hdfs://localhost:9000</value>
+ </property>
+</configuration>
+```
+
+#### 2.2.2 hdfs-site.xml
+
+vi etc/hadoop/hdfs-site.xml
+
+```xml
+ <configuration>
+ <property>
+ <name>dfs.replication</name>
+ <value>1</value>
+ </property>
+ <property>
+ <name>dfs.namenode.name.dir</name>
+ <value>/data/hdfs/namenode</value>
+ </property>
+ <property>
+ <name>dfs.datanode.data.dir</name>
+ <value>/data/hdfs/datanode</value>
+ </property>
+ </configuration>
+```
+
+#### 2.2.3 修改Hadoop启动脚本
+
+sbin/start-dfs.sh
+
+sbin/stop-dfs.sh
+
+在文件开始加上下面的内容
+
+```shell
+HDFS_DATANODE_USER=root
+HADOOP_SECURE_DN_USER=hdfs
+HDFS_NAMENODE_USER=root
+HDFS_SECONDARYNAMENODE_USER=root
+```
+
+sbin/start-yarn.sh
+
+sbin/stop-yarn.sh
+
+在文件开始加上下面的内容
+
+```shell
+YARN_RESOURCEMANAGER_USER=root
+HADOOP_SECURE_DN_USER=yarn
+YARN_NODEMANAGER_USER=root
+```
+
+### 2.3 配置yarn
+
+这里我改变了Yarn的一些端口，因为我是单机环境和Doris 的一些端口冲突。你可以不启动yarn
+
+vi etc/hadoop/yarn-site.xml
+
+```xml
+<property>
+ <name>yarn.resourcemanager.address</name>
+ <value>jiafeng-test:50056</value>
+</property>
+<property>
+ <name>yarn.resourcemanager.scheduler.address</name>
+ <value>jiafeng-test:50057</value>
+</property>
+<property>
+ <name>yarn.resourcemanager.resource-tracker.address</name>
+ <value>jiafeng-test:50058</value>
+</property>
+<property>
+ <name>yarn.resourcemanager.admin.address</name>
+ <value>jiafeng-test:50059</value>
+</property>
+<property>
+ <name>yarn.resourcemanager.webapp.address</name>
+ <value>jiafeng-test:9090</value>
+</property>
+<property>
+ <name>yarn.nodemanager.localizer.address</name>
+ <value>0.0.0.0:50060</value>
+</property>
+<property>
+ <name>yarn.nodemanager.webapp.address</name>
+ <value>0.0.0.0:50062</value>
+</property>
+```
+
+
+
+vi etc/hadoop/mapred-site.xm
+
+```xml
+<property>
+ <name>mapreduce.jobhistory.address</name>
+ <value>0.0.0.0:10020</value>
+</property>
+<property>
+ <name>mapreduce.jobhistory.webapp.address</name>
+ <value>0.0.0.0:19888</value>
+</property>
+<property>
+ <name>mapreduce.shuffle.port</name>
+ <value>50061</value>
+</property>
+```
+
+#### 2.2.4 启动hadoop
+
+```
+sbin/start-all.sh
+```
+
+
+
+### 2.4 配置Hive
+
+#### 2.4.1 创建hdfs目录
+
+```
+hdfs dfs -mkdir -p /user/hive/warehouse
+hdfs dfs -mkdir /tmp
+hdfs dfs -chmod g+w /user/hive/warehouse
+hdfs dfs -chmod g+w /tmp
+```
+
+#### 2.4.2 配置hive-site.xml
+
+```xml
+<?xml version="1.0"?>
+<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
+
+<configuration>
+ <property>
+ <name>javax.jdo.option.ConnectionURL</name>
+
<value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true</value>
+ </property>
+ <property>
+ <name>javax.jdo.option.ConnectionDriverName</name>
+ <value>com.mysql.jdbc.Driver</value>
+ </property>
+ <property>
+ <name>javax.jdo.option.ConnectionUserName</name>
+ <value>root</value>
+ </property>
+ <property>
+ <name>javax.jdo.option.ConnectionPassword</name>
+ <value>MyNewPass4!</value>
+ </property>
+ <property>
+ <name>hive.metastore.warehouse.dir</name>
+ <value>/user/hive/warehouse</value>
+ <description>location of default database for the
warehouse</description>
+ </property>
+ <property>
+ <name>hive.metastore.uris</name>
+ <value/>
+ <description>Thrift URI for the remote metastore. Used by
metastore client to connect to remote metastore.</description>
+ </property>
+ <property>
+ <name>javax.jdo.PersistenceManagerFactoryClass</name>
+
<value>org.datanucleus.api.jdo.JDOPersistenceManagerFactory</value>
+ </property>
+ <property>
+ <name>hive.metastore.schema.verification</name>
+ <value>false</value>
+ </property>
+ <property>
+ <name>datanucleus.schema.autoCreateAll</name>
+ <value>true</value>
+ </property>
+</configuration>
+```
+
+#### 2.4.3 配置 hive-env.sh
+
+加入一下内容
+
+```
+HADOOP_HOME=/data/hadoop-3.3.3
+```
+
+#### 2.4.4 hive元数据初始化
+
+```
+schematool -initSchema -dbType mysql
+```
+
+
+
+#### 2.4.5 启动hive metaservice
+
+后台运行
+
+```
+nohup bin/hive --service metaservice 1>/dev/null 2>&1 &
+```
+
+验证
+
+```
+lsof -i:9083
+COMMAND PID USER FD TYPE DEVICE SIZE/OFF NODE NAME
+java 20700 root 567u IPv6 54605348 0t0 TCP *:emc-pp-mgmtsvc (LISTEN)
+```
+
+### 2.5 安装MySQL
+
+具体请参照这里：
+
+[使用 Flink CDC 实现 MySQL 数据实时入 Apache
Doris](https://doris.apache.org/zh-CN/blogs/PracticalCases/flink-cdc-to-doris.html#_4-3-安装配置-mysql)
+
+#### 2.5.1 创建MySQL数据库表并初始化数据
+
+
+
+```sql
+CREATE DATABASE demo;
+USE demo;
+CREATE TABLE userinfo (
+ id int NOT NULL AUTO_INCREMENT,
+ name VARCHAR(255) NOT NULL DEFAULT 'flink',
+ address VARCHAR(1024),
+ phone_number VARCHAR(512),
+ email VARCHAR(255),
+ PRIMARY KEY (`id`)
+)ENGINE=InnoDB ;
+INSERT INTO userinfo VALUES (10001,'user_110','Shanghai','13347420870', NULL);
+INSERT INTO userinfo VALUES (10002,'user_111','xian','13347420870', NULL);
+INSERT INTO userinfo VALUES (10003,'user_112','beijing','13347420870', NULL);
+INSERT INTO userinfo VALUES (10004,'user_113','shenzheng','13347420870', NULL);
+INSERT INTO userinfo VALUES (10005,'user_114','hangzhou','13347420870', NULL);
+INSERT INTO userinfo VALUES (10006,'user_115','guizhou','13347420870', NULL);
+INSERT INTO userinfo VALUES (10007,'user_116','chengdu','13347420870', NULL);
+INSERT INTO userinfo VALUES (10008,'user_117','guangzhou','13347420870', NULL);
+INSERT INTO userinfo VALUES (10009,'user_118','xian','13347420870', NULL);
+```
+
+### 2.6 安装 Flink
+
+```
+tar zxvf flink-1.14.4-bin-scala_2.12.tgz
+```
+
+然后需要将下面的依赖拷贝到Flink安装目录下的lib目录下，具体的依赖的lib文件如下：
+
+
+
+下面将几个Hadoop和Flink里没有的依赖下载地址放在下面
+
+```shell
+wget
https://repo1.maven.org/maven2/com/ververica/flink-sql-connector-mysql-cdc/2.2.1/flink-sql-connector-mysql-cdc-2.2.1.jar
+wget
https://repo1.maven.org/maven2/org/apache/thrift/libfb303/0.9.3/libfb303-0.9.3.jar
+wget
https://search.maven.org/remotecontent?filepath=org/apache/iceberg/iceberg-flink-runtime-1.14/0.13.2/iceberg-flink-runtime-1.14-0.13.2.jar
+wget
https://repository.cloudera.com/artifactory/cloudera-repos/org/apache/flink/flink-shaded-hadoop-3-uber/3.1.1.7.2.9.0-173-9.0/flink-shaded-hadoop-3-uber-3.1.1.7.2.9.0-173-9.0.jar
+```
+
+其他的：
+
+```
+hadoop-3.3.3/share/hadoop/common/lib/commons-configuration2-2.1.1.jar
+hadoop-3.3.3/share/hadoop/common/lib/commons-logging-1.1.3.jar
+hadoop-3.3.3/share/hadoop/tools/lib/hadoop-archive-logs-3.3.3.jar
+hadoop-3.3.3/share/hadoop/common/lib/hadoop-auth-3.3.3.jar
+hadoop-3.3.3/share/hadoop/common/lib/hadoop-annotations-3.3.3.jar
+hadoop-3.3.3/share/hadoop/common/hadoop-common-3.3.3.jar
+adoop-3.3.3/share/hadoop/hdfs/hadoop-hdfs-3.3.3.jar
+hadoop-3.3.3/share/hadoop/client/hadoop-client-api-3.3.3.jar
+hive-3.1.3/lib/hive-exec-3.1.3.jar
+hive-3.1.3/lib/hive-metastore-3.1.3.jar
+hive-3.1.3/lib/hive-hcatalog-core-3.1.3.jar
+```
+
+#### 2.6.1 启动Flink
+
+```
+bin/start-cluster.sh
+```
+
+启动后的界面如下：
+
+
+
+#### 2.6.2 进入 Flink SQL Client
+
+```
+ bin/sql-client.sh embedded
+```
+
+
+
+开启 checkpoint，每隔3秒做一次 checkpoint
+
+Checkpoint 默认是不开启的，我们需要开启 Checkpoint 来让 Iceberg 可以提交事务。 并且，mysql-cdc 在 binlog
读取阶段开始前，需要等待一个完整的 checkpoint 来避免 binlog 记录乱序的情况。
+
+>注意：
+>
+>这里是演示环境，checkpoint的间隔设置比较短，线上使用，建议设置为3-5分钟一次checkpoint。
+
+```sql
+Flink SQL> SET execution.checkpointing.interval = 3s;
+[INFO] Session property has been set.
+```
+
+#### 2.6.3 创建Iceberg Catalog
+
+```sql
+CREATE CATALOG hive_catalog WITH (
+ 'type'='iceberg',
+ 'catalog-type'='hive',
+ 'uri'='thrift://localhost:9083',
+ 'clients'='5',
+ 'property-version'='1',
+ 'warehouse'='hdfs://localhost:8020/user/hive/warehouse'
+);
+```
+
+查看catalog
+
+```sql
+Flink SQL> show catalogs;
++-----------------+
+| catalog name |
++-----------------+
+| default_catalog |
+| hive_catalog |
++-----------------+
+2 rows in set
+```
+
+
+
+#### 2.6.4 创建 Mysql CDC 表
+
+```sql
+ CREATE TABLE user_source (
+ database_name STRING METADATA VIRTUAL,
+ table_name STRING METADATA VIRTUAL,
+ `id` DECIMAL(20, 0) NOT NULL,
+ name STRING,
+ address STRING,
+ phone_number STRING,
+ email STRING,
+ PRIMARY KEY (`id`) NOT ENFORCED
+ ) WITH (
+ 'connector' = 'mysql-cdc',
+ 'hostname' = 'localhost',
+ 'port' = '3306',
+ 'username' = 'root',
+ 'password' = 'MyNewPass4!',
+ 'database-name' = 'demo',
+ 'table-name' = 'userinfo'
+ );
+```
+
+查询CDC表:
+
+```sql
+select * from user_source;
+```
+
+
+
+#### 2.6.5 创建Iceberg表
+
+```sql
+---查看catalog
+show catalogs;
+---使用catalog
+use catalog hive_catalog;
+--创建数据库
+CREATE DATABASE iceberg_hive;
+--使用数据库
+use iceberg_hive;
+
+```
+
+##### 2.6.5.1 创建表
+
+```
+CREATE TABLE all_users_info (
+ database_name STRING,
+ table_name STRING,
+ `id` DECIMAL(20, 0) NOT NULL,
+ name STRING,
+ address STRING,
+ phone_number STRING,
+ email STRING,
+ PRIMARY KEY (database_name, table_name, `id`) NOT ENFORCED
+ ) WITH (
+ 'catalog-type'='hive'
+ );
+```
+
+从CDC表里插入数据到Iceberg表里
+
+```sql
+use catalog default_catalog;
+
+insert into hive_catalog.iceberg_hive.all_users_info select * from user_source;
+```
+
+在web界面可以看到任务的运行情况
+
+
+
+然后停掉任务，我们去查询iceberg表
+
+```sql
+select * from hive_catalog.iceberg_hive.all_users_info
+```
+
+可以看到下面的结果
+
+
+
+我们去hdfs上可以看到hive目录下的数据及对应的元数据
+
+
+
+
+
+我们也可以通过Hive建好Iceberg表，然后通过Flink将数据插入到表里
+
+下载Iceberg Hive运行依赖
+
+```
+ wget
https://repo1.maven.org/maven2/org/apache/iceberg/iceberg-hive-runtime/0.13.2/iceberg-hive-runtime-0.13.2.jar
+```
+
+在hive shell下执行：
+
+```
+SET engine.hive.enabled=true;
+SET iceberg.engine.hive.enabled=true;
+SET iceberg.mr.catalog=hive;
+ add jar /path/to/iiceberg-hive-runtime-0.13.2.jar;
+```
+
+创建表
+
+```sql
+CREATE EXTERNAL TABLE iceberg_hive(
+ `id` int,
+ `name` string)
+STORED BY 'org.apache.iceberg.mr.hive.HiveIcebergStorageHandler'
+LOCATION 'hdfs://localhost:8020/user/hive/warehouse/iceber_db/iceberg_hive'
+TBLPROPERTIES (
+ 'iceberg.mr.catalog'='hadoop',
+'iceberg.mr.catalog.hadoop.warehouse.location'='hdfs://localhost:8020/user/hive/warehouse/iceber_db/iceberg_hive'
+ );
+```
+
+然后再Flink SQL Client下执行下面语句将数据插入到Iceber表里
+
+```sql
+INSERT INTO hive_catalog.iceberg_hive.iceberg_hive values(2, 'c');
+INSERT INTO hive_catalog.iceberg_hive.iceberg_hive values(3, 'zhangfeng');
+```
+
+查询这个表
+
+```sql
+select * from hive_catalog.iceberg_hive.iceberg_hive
+```
+
+可以看到下面的结果
+
+
+
+## 3. Doris 查询 Iceberg
+
+Apache Doris 提供了 Doris 直接访问 Iceberg 外部表的能力，外部表省去了繁琐的数据导入工作，并借助 Doris 本身的 OLAP
的能力来解决 Iceberg 表的数据分析问题：
+
+1. 支持 Iceberg 数据源接入Doris
+2. 支持 Doris 与 Iceberg 数据源中的表联合查询，进行更加复杂的分析操作
+
+### 3.1安装Doris
+
+这里我们不在详细讲解Doris的安装，如果你不知道怎么安装Doris请参照官方文档：[快速入门](https://doris.apache.org/zh-CN/docs/get-starting/get-starting.html#环境准备)
+
+### 3.2 创建Iceberg外表
+
+```
+CREATE TABLE `all_users_info`
+ENGINE = ICEBERG
+PROPERTIES (
+"iceberg.database" = "iceberg_hive",
+"iceberg.table" = "all_users_info",
+"iceberg.hive.metastore.uris" = "thrift://localhost:9083",
+"iceberg.catalog.type" = "HIVE_CATALOG"
+);
+```
+
+#### 参数说明：
+
+- ENGINE 需要指定为 ICEBERG
+- PROPERTIES 属性：
+ - `iceberg.hive.metastore.uris`：Hive Metastore 服务地址
+ - `iceberg.database`：挂载 Iceberg 对应的数据库名
+ - `iceberg.table`：挂载 Iceberg 对应的表名，挂载 Iceberg database 时无需指定。
+ - `iceberg.catalog.type`：Iceberg 中使用的 catalog 方式，默认为
`HIVE_CATALOG`，当前仅支持该方式，后续会支持更多的 Iceberg catalog 接入方式。
+
+```sql
+mysql> CREATE TABLE `all_users_info`
+ -> ENGINE = ICEBERG
+ -> PROPERTIES (
+ -> "iceberg.database" = "iceberg_hive",
+ -> "iceberg.table" = "all_users_info",
+ -> "iceberg.hive.metastore.uris" = "thrift://localhost:9083",
+ -> "iceberg.catalog.type" = "HIVE_CATALOG"
+ -> );
+Query OK, 0 rows affected (0.23 sec)
+
+mysql> select * from all_users_info;
++---------------+------------+-------+----------+-----------+--------------+-------+
+| database_name | table_name | id | name | address | phone_number |
email |
++---------------+------------+-------+----------+-----------+--------------+-------+
+| demo | userinfo | 10004 | user_113 | shenzheng | 13347420870 |
NULL |
+| demo | userinfo | 10005 | user_114 | hangzhou | 13347420870 |
NULL |
+| demo | userinfo | 10002 | user_111 | xian | 13347420870 |
NULL |
+| demo | userinfo | 10003 | user_112 | beijing | 13347420870 |
NULL |
+| demo | userinfo | 10001 | user_110 | Shanghai | 13347420870 |
NULL |
+| demo | userinfo | 10008 | user_117 | guangzhou | 13347420870 |
NULL |
+| demo | userinfo | 10009 | user_118 | xian | 13347420870 |
NULL |
+| demo | userinfo | 10006 | user_115 | guizhou | 13347420870 |
NULL |
+| demo | userinfo | 10007 | user_116 | chengdu | 13347420870 |
NULL |
++---------------+------------+-------+----------+-----------+--------------+-------+
+9 rows in set (0.18 sec)
+```
+
+### 3.3 同步挂在
+
+当 Iceberg 表 Schema 发生变更时，可以通过 `REFRESH` 命令手动同步，该命令会将 Doris 中的 Iceberg 外表删除重建。
+
+```
+-- 同步 Iceberg 表
+REFRESH TABLE t_iceberg;
+
+-- 同步 Iceberg 数据库
+REFRESH DATABASE iceberg_test_db;
+```
+
+### 3.4 Doris 和 Iceberg 数据类型对应关系
+
+支持的 Iceberg 列类型与 Doris 对应关系如下表：
+
+| Iceberg | Doris | 描述 |
+| :-------: | :------: | :--------------------------------: |
+| BOOLEAN | BOOLEAN | |
+| INTEGER | INT | |
+| LONG | BIGINT | |
+| FLOAT | FLOAT | |
+| DOUBLE | DOUBLE | |
+| DATE | DATE | |
+| TIMESTAMP | DATETIME | Timestamp 转成 Datetime 会损失精度 |
+| STRING | STRING | |
+| UUID | VARCHAR | 使用 VARCHAR 来代替 |
+| DECIMAL | DECIMAL | |
+| TIME | - | 不支持 |
+| FIXED | - | 不支持 |
+| BINARY | - | 不支持 |
+| STRUCT | - | 不支持 |
+| LIST | - | 不支持 |
+| MAP | - | 不支持 |
+
+### 3.5 注意事项
+
+- Iceberg 表 Schema 变更**不会自动同步**，需要在 Doris 中通过 `REFRESH` 命令同步 Iceberg 外表或数据库。
+- 当前默认支持的 Iceberg 版本为 0.12.0，0.13.x，未在其他版本进行测试。后续后支持更多版本。
+
+### 3.6 Doris FE 配置
+
+下面几个配置属于 Iceberg 外表系统级别的配置，可以通过修改 `fe.conf` 来配置，也可以通过 `ADMIN SET CONFIG` 来配置。
+
+- `iceberg_table_creation_strict_mode`
+
+ 创建 Iceberg 表默认开启 strict mode。
+ strict mode 是指对 Iceberg 表的列类型进行严格过滤，如果有 Doris 目前不支持的数据类型，则创建外表失败。
+
+- `iceberg_table_creation_interval_second`
+
+ 自动创建 Iceberg 表的后台任务执行间隔，默认为 10s。
+
+- `max_iceberg_table_creation_record_size`
+
+ Iceberg 表创建记录保留的最大值，默认为 2000. 仅针对创建 Iceberg 数据库记录。
+
+## 4. 总结
+
+这里Doris On
Iceberg我们只演示了Iceberg单表的查询，你还可以联合Doris的表，或者其他的ODBC外表，Hive外表，ES外表等进行联合查询分析，通过Doris对外提供统一的查询分析入口。
+
+自此我们完整从搭建Hadoop，hive、flink 、Mysql、Doris 及Doris On
Iceberg的使用全部介绍完了，Doris朝着数据仓库和数据融合的架构演进，支持湖仓一体的联邦查询，给我们的开发带来更多的便利，更高效的开发，省去了很多数据同步的繁琐工作，快快来体验吧。
\ No newline at end of file
diff --git a/blogs/zh-CN/PracticalCases/flnkcdc-mysql-doris-exactlyonce.md
b/blogs/zh-CN/PracticalCases/flnkcdc-mysql-doris-exactlyonce.md
new file mode 100644
index 0000000000..552c5bf440
--- /dev/null
+++ b/blogs/zh-CN/PracticalCases/flnkcdc-mysql-doris-exactlyonce.md
@@ -0,0 +1,1111 @@
+---
+{
+ "title": "Doris Connector 结合 Flink CDC 实现 MySQL 分库分表 Exactly Once精准接入",
+ "description": "本篇文档我们就演示怎么基于Flink CDC 并结合 Apache Doris Flink Connector 及
Doris Stream Load的两阶段提交，实现MySQL数据库分库分表实时高效的接入到 Apache Doris 数据仓库中进行分析.",
+ "date": "2022-07-18",
+ "metaTitle": "Doris Connector 结合 Flink CDC 实现 MySQL 分库分表 Exactly Once精准接入",
+ "isArticle": true,
+ "language": "zh-CN",
+ "author": "张家锋",
+ "layout": "Article",
+ "sidebar": true,
+ "zhCategories": "PracticalCases"
+}
+---
+
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements. See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership. The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied. See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+# Doris Connector 结合 Flink CDC 实现 MySQL 分库分表 Exactly Once精准接入
+
+## 1. 概述
+
+在实际业务系统中为了解决单表数据量大带来的各种问题，我们通常采用分库分表的方式对库表进行拆分，以达到提高系统的吞吐量。
+
+但是这样给后面数据分析带来了麻烦，这个时候我们通常试将业务数据库的分库分表同步到数据仓库时，将这些分库分表的数据，合并成一个库，一个表。便于我们后面的数据分析
+
+本篇文档我们就演示怎么基于Flink CDC 并结合 Apache Doris Flink Connector 及 Doris Stream
Load的两阶段提交，实现MySQL数据库分库分表实时高效的接入到 Apache Doris 数据仓库中进行分析。
+
+### 1.1 什么是CDC
+
+CDC是（`Change Data Capture 变更数据获取`）的简称。
+
+核心思想是，监测并捕获数据库的变动（包括数据 或
数据表的插入INSERT、更新UPDATE、删除DELETE等），将这些变更按发生的顺序完整记录下来，写入到消息中间件中以供其他服务进行订阅及消费。
+
+CDC 技术应用场景也非常广泛，包括：
+
+● **数据分发**，将一个数据源分发给多个下游，常用于业务解耦、微服务。
+
+● **数据集成**，将分散异构的数据源集成到数据仓库中，消除数据孤岛，便于后续的分析。
+
+● **数据迁移**，常用于数据库备份、容灾等。
+
+### 1.2 为什么选择Flink CDC
+
+Flink CDC 基于数据库日志的Change Data Caputre 技术，实现了全量和增量的一体化读取能力，并借助 Flink
优秀的管道能力和丰富的上下游生态，支持捕获多种数据库的变更，并将这些变更实时同步到下游存储。
+
+目前，Flink CDC 的上游已经支持了 MySQL、MariaDB、PG、Oracle、MongoDB
、Oceanbase、TiDB、SQLServer等数据库。
+
+Flink CDC 的下游则更加丰富，支持写入 Kafka、Pulsar 消息队列，也支持写入 Hudi、Iceberg
、Doris等，支持写入各种数据仓库及数据湖中。
+
+同时，通过 Flink SQL 原生支持的 Changelog 机制，可以让 CDC 数据的加工变得非常简单。用户可以通过 SQL
便能实现数据库全量和增量数据的清洗、打宽、聚合等操作，极大地降低了用户门槛。 此外， Flink DataStream API
支持用户编写代码实现自定义逻辑，给用户提供了深度定制业务的自由度
+
+Flink CDC
技术的核心是支持将表中的全量数据和增量数据做实时一致性的同步与加工，让用户可以方便地获每张表的实时一致性快照。比如一张表中有历史的全量业务数据，也有增量的业务数据在源源不断写入，更新。Flink
CDC 会实时抓取增量的更新记录，实时提供与数据库中一致性的快照，如果是更新记录，会更新已有数据。如果是插入记录，则会追加到已有数据，整个过程中，Flink
CDC 提供了一致性保障，即不重不丢。
+
+FLink CDC 如下优势：
+
+- Flink 的算子和 SQL 模块更为成熟和易用
+- Flink 作业可以通过调整算子并行度的方式，轻松扩展处理能力
+- Flink 支持高级的状态后端（State Backends），允许存取海量的状态数据
+- Flink 提供更多的 Source 和 Sink 等生态支持
+- Flink 有更大的用户基数和活跃的支持社群，问题更容易解决
+- Flink 的开源协议允许云厂商进行全托管的深度定制，而 Kafka Streams 只能自行部署和运维
+
+而且 Flink Table / SQL 模块将数据库表和变动记录流（例如 CDC 的数据流）看做是同一事物的两面，因此内部提供的 Upsert
消息结构（`+I` 表示新增、`-U` 表示记录更新前的值、`+U` 表示记录更新后的值，`-D` 表示删除）可以与 Debezium
等生成的变动记录一一对应。
+
+### 1.3 什么是Apache Doris
+
+Apache Doris是一个现代化的MPP分析型数据库产品。仅需亚秒级响应时间即可获得查询结果，有效地支持实时数据分析。Apache
Doris的分布式架构非常简洁，易于运维，并且可以支持10PB以上的超大数据集。
+
+Apache Doris可以满足多种数据分析需求，例如固定历史报表，实时数据分析，交互式数据分析和探索式数据分析等。令您的数据分析工作更加简单高效！
+
+### 1.4 Two-phase commit
+
+#### 1.4.1 什么是 two-phase commit （2PC）
+
+在分布式系统中，为了让每个节点都能够感知到其他节点的事务执行状况，需要引入一个中心节点来统一处理所有节点的执行逻辑，这个中心节点叫做协调者（coordinator），被中心节点调度的其他业务节点叫做参与者（participant）。
+
+2PC将分布式事务分成了两个阶段，两个阶段分别为提交请求（投票）和提交（执行）。协调者根据参与者的响应来决定是否需要真正地执行事务，具体流程如下。
+
+##### 提交请求（投票）阶段
+
+1. 协调者向所有参与者发送prepare请求与事务内容，询问是否可以准备事务提交，并等待参与者的响应。
+2. 参与者执行事务中包含的操作，并记录undo日志（用于回滚）和redo日志（用于重放），但不真正提交。
+3. 参与者向协调者返回事务操作的执行结果，执行成功返回yes，否则返回no。
+
+##### 提交（执行）阶段
+
+分为成功与失败两种情况。
+
+- 若所有参与者都返回yes，说明事务可以提交：
+
+1. 协调者向所有参与者发送commit请求。
+2. 参与者收到commit请求后，将事务真正地提交上去，并释放占用的事务资源，并向协调者返回ack。
+3. 协调者收到所有参与者的ack消息，事务成功完成。
+
+- 若有参与者返回no或者超时未返回，说明事务中断，需要回滚：
+
+1. 协调者向所有参与者发送rollback请求。
+2. 参与者收到rollback请求后，根据undo日志回滚到事务执行前的状态，释放占用的事务资源，并向协调者返回ack。
+3. 协调者收到所有参与者的ack消息，事务回滚完成。
+
+### 1.4 Flink 2PC
+
+Flink作为流式处理引擎，自然也提供了对exactly once语义的保证。端到端的exactly
once语义，是输入、处理逻辑、输出三部分协同作用的结果。Flink内部依托检查点机制和轻量级分布式快照算法ABS保证exactly
once。而要实现精确一次的输出逻辑，则需要施加以下两种限制之一：幂等性写入（idempotent write）、事务性写入（transactional
write）。
+
+##### 预提交阶段的流程
+
+
+
+每当需要做checkpoint时，JobManager就在数据流中打入一个屏障（barrier），作为检查点的界限。屏障随着算子链向下游传递，每到达一个算子都会触发将状态快照写入状态后端的动作。当屏障到达Kafka
sink后，通过KafkaProducer.flush()方法刷写消息数据，但还未真正提交。接下来还是需要通过检查点来触发提交阶段
+
+##### 提交阶段流程
+
+
+
+只有在所有检查点都成功完成这个前提下，写入才会成功。这符合前文所述2PC的流程，其中JobManager为协调者，各个算子为参与者（不过只有sink一个参与者会执行提交）。一旦有检查点失败，notifyCheckpointComplete()方法就不会执行。如果重试也不成功的话，最终会调用abort()方法回滚事务
+
+### 1.5 Doris Flink Connector 2PC
+
+#### 1.5.1 Stream load
+
+Stream load 是Apache Doris 提供的一个同步的导入方式，用户通过发送 HTTP 协议发送请求将本地文件或数据流导入到 Doris
中。Stream load 同步执行导入并返回导入结果。用户可直接通过请求的返回体判断本次导入是否成功。
+
+Stream load 主要适用于导入本地文件，或通过程序导入数据流中的数据。
+
+使用方法，用户通过Http Client 进行操作，也可以使用Curl命令进行
+
+```shell
+curl --location-trusted -u user:passwd [-H ""...] -T data.file -H
"label:label" -XPUT http://fe_host:http_port/api/{db}/{table}/_stream_load
+```
+
+这里为了是防止用户重复导入相同的数据，使用了导入任务标识label。**强烈推荐用户同一批次数据使用相同的
label。这样同一批次数据的重复请求只会被接受一次，保证了 At-Most-Once**
+
+#### 1.5.2 Stream load 2PC
+
+Aapche Doris 最早的Stream Load 是没有两阶段提交的，导入数据的时候直接通过 Stream Load 的 http
接口完成数据导入，只有成功和失败。
+
+1. 这种在正常情况下是没有问题的，在分布式环境下可能为因为某一个导入任务是失败导致两端数据不一致的情况，特别是在Doris Flink
Connector里，之前的Doris Flink Connector
数据导入失败需要用户自己控制，做异常处理，比如如果导入失败之后，将数据保存到指定的地方（例如Kafka），然后人工手动处理。
+2. 如果Flink
Job因为其他为题突然挂掉，这样会造成部分数据成功，部分数据失败，而且失败的数据因为没有checkpoint，重新启动Job也没办法重新消费失败的数据，造成两端数据不一致
+
+为了解决上面的这些问题，保证两端数据一致性，我们实现了Doris Stream Load 2PC，原理如下：
+
+1. 提交分成两个阶段
+2. 第一阶段，提交数据写入任务，这个时候数据写入成功后，数据状态是不可见的，事务状态是PRECOMMITTED
+3. 数据写入成功之后，用户触发Commit操作，将事务状态变成VISIBLE，这个时候数据可以查询到
+4. 如果用户要方式这一批数据只需要通过事务ID，对事务触发abort操作，这批数据将会被自动删除掉
+
+#### 1.5.3 Stream load 2PC使用方式
+
+1. 在be.conf中配置`disable_stream_load_2pc=false`（重启生效）
+2. 并且 在 HEADER 中声明 `two_phase_commit=true` 。
+
+
+
+发起预提交：
+
+```
+curl --location-trusted -u user:passwd -H "two_phase_commit:true" -T test.txt
http://fe_host:http_port/api/{db}/{table}/_stream_load
+```
+
+触发事务Commit操作
+
+```
+curl -X PUT --location-trusted -u user:passwd -H "txn_id:18036" -H
"txn_operation:commit" http://fe_host:http_port/api/{db}/_stream_load_2pc
+```
+
+对事物触发abort操作
+
+```
+curl -X PUT --location-trusted -u user:passwd -H "txn_id:18037" -H
"txn_operation:abort" http://fe_host:http_port/api/{db}/_stream_load_2pc
+```
+
+
+
+### 1.6 Doris Flink Connector 2PC
+
+我们之前提供了Doris Flink Connector ，支持对Doris表数据的读，Upsert、delete（Unique
key模型），但是存在可能因为Job失败或者其他异常情况导致两端数据不一致的问题。
+
+为了解决这些问题，我们基于FLink 2PC 和Doris Stream Load 2PC对Doris
Connector进行了改造升级，保证两端exactly once。
+
+1. 我们会在内存中维护读写的buffer，在启动的时候，开启写入，并异步的提交，期间通过http
chunked的方式持续的将数据写入到BE，直到Checkpoint的时候，停止写入，这样做的好处是避免用户频繁提交http带来的开销，Checkpoint完成后会开启下一阶段的写入
+2.
在这个Checkpoint期间，可能是多个task任务同时在写一张表的数据，这些我们都会在这个Checkpoint期间对应一个全局的label，在checkpoint的时候将这个label对应的写入数据的事务进行统一的一次提交，将数据状态变成可见，
+3. 如果失败 Flink 在重启的时候会对这些数据通过checkpoint进行回放。
+4. 这样就可以保证Doris两端数据的一致
+
+## 2. 系统架构
+
+下面我们通过一个完整示例来看怎么去通过Doris Flink Connector最新版本（支持两阶段提交），来完成整合Flink
CDC实现MySQL分库分表实时采集入库
+
+
+
+
+
+1. 这里我们通过Flink CDC 来完成MySQL分库分表数据通过
+2. 然后通过Doris Flink Connector来完成数据的入库
+3. 最后利用Doris的高并发、高性能的OLAP分析计算能力对外提供数据服务
+
+## 3. MySQL 安装配置
+
+### 3.1 安装MySQL
+
+快速使用Docker安装配置Mysql，具体参照下面的连接
+
+https://segmentfault.com/a/1190000021523570
+
+### 3.2 开启Mysql binlog
+
+进入 Docker 容器修改/etc/my.cnf 文件，在 [mysqld] 下面添加以下内容，
+
+```text
+log_bin=mysql_bin
+binlog-format=Row
+server-id=1
+```
+
+然后重启Mysql
+
+```text
+systemctl restart mysqld
+```
+
+### 3.3 准备数据
+
+这里演示我们准备了两个库emp_1,emp_2,每个库下面各种主备了两张表employees_1，employees_2。并给出了一下初始化数据
+
+```sql
+CREATE DATABASE emp_1;
+ USE emp_1;
+CREATE TABLE employees_1 (
+ emp_no INT NOT NULL,
+ birth_date DATE NOT NULL,
+ first_name VARCHAR(14) NOT NULL,
+ last_name VARCHAR(16) NOT NULL,
+ gender ENUM ('M','F') NOT NULL,
+ hire_date DATE NOT NULL,
+ PRIMARY KEY (emp_no)
+);
+
+INSERT INTO `employees_1` VALUES
(10001,'1953-09-02','Georgi','Facello','M','1986-06-26'),
+(10002,'1964-06-02','Bezalel','Simmel','F','1985-11-21'),
+(10003,'1959-12-03','Parto','Bamford','M','1986-08-28'),
+(10004,'1954-05-01','Chirstian','Koblick','M','1986-12-01'),
+(10005,'1955-01-21','Kyoichi','Maliniak','M','1989-09-12'),
+(10006,'1953-04-20','Anneke','Preusig','F','1989-06-02'),
+(10007,'1957-05-23','Tzvetan','Zielinski','F','1989-02-10'),
+(10008,'1958-02-19','Saniya','Kalloufi','M','1994-09-15'),
+(10009,'1952-04-19','Sumant','Peac','F','1985-02-18'),
+(10010,'1963-06-01','Duangkaew','Piveteau','F','1989-08-24'),
+(10011,'1953-11-07','Mary','Sluis','F','1990-01-22'),
+(10012,'1960-10-04','Patricio','Bridgland','M','1992-12-18'),
+(10013,'1963-06-07','Eberhardt','Terkki','M','1985-10-20'),
+(10014,'1956-02-12','Berni','Genin','M','1987-03-11'),
+(10015,'1959-08-19','Guoxiang','Nooteboom','M','1987-07-02'),
+(10016,'1961-05-02','Kazuhito','Cappelletti','M','1995-01-27'),
+(10017,'1958-07-06','Cristinel','Bouloucos','F','1993-08-03'),
+(10018,'1954-06-19','Kazuhide','Peha','F','1987-04-03'),
+(10019,'1953-01-23','Lillian','Haddadi','M','1999-04-30'),
+(10020,'1952-12-24','Mayuko','Warwick','M','1991-01-26'),
+(10021,'1960-02-20','Ramzi','Erde','M','1988-02-10'),
+(10022,'1952-07-08','Shahaf','Famili','M','1995-08-22'),
+(10023,'1953-09-29','Bojan','Montemayor','F','1989-12-17'),
+(10024,'1958-09-05','Suzette','Pettey','F','1997-05-19'),
+(10025,'1958-10-31','Prasadram','Heyers','M','1987-08-17'),
+(10026,'1953-04-03','Yongqiao','Berztiss','M','1995-03-20'),
+(10027,'1962-07-10','Divier','Reistad','F','1989-07-07'),
+(10028,'1963-11-26','Domenick','Tempesti','M','1991-10-22'),
+(10029,'1956-12-13','Otmar','Herbst','M','1985-11-20'),
+(10030,'1958-07-14','Elvis','Demeyer','M','1994-02-17'),
+(10031,'1959-01-27','Karsten','Joslin','M','1991-09-01'),
+(10032,'1960-08-09','Jeong','Reistad','F','1990-06-20'),
+(10033,'1956-11-14','Arif','Merlo','M','1987-03-18'),
+(10034,'1962-12-29','Bader','Swan','M','1988-09-21'),
+(10035,'1953-02-08','Alain','Chappelet','M','1988-09-05'),
+(10036,'1959-08-10','Adamantios','Portugali','M','1992-01-03');
+
+CREATE TABLE employees_2 (
+ emp_no INT NOT NULL,
+ birth_date DATE NOT NULL,
+ first_name VARCHAR(14) NOT NULL,
+ last_name VARCHAR(16) NOT NULL,
+ gender ENUM ('M','F') NOT NULL,
+ hire_date DATE NOT NULL,
+ PRIMARY KEY (emp_no)
+);
+
+INSERT INTO `employees_2` VALUES
(10037,'1963-07-22','Pradeep','Makrucki','M','1990-12-05'),
+(10038,'1960-07-20','Huan','Lortz','M','1989-09-20'),
+(10039,'1959-10-01','Alejandro','Brender','M','1988-01-19'),
+(10040,'1959-09-13','Weiyi','Meriste','F','1993-02-14'),
+(10041,'1959-08-27','Uri','Lenart','F','1989-11-12'),
+(10042,'1956-02-26','Magy','Stamatiou','F','1993-03-21'),
+(10043,'1960-09-19','Yishay','Tzvieli','M','1990-10-20'),
+(10044,'1961-09-21','Mingsen','Casley','F','1994-05-21'),
+(10045,'1957-08-14','Moss','Shanbhogue','M','1989-09-02'),
+(10046,'1960-07-23','Lucien','Rosenbaum','M','1992-06-20'),
+(10047,'1952-06-29','Zvonko','Nyanchama','M','1989-03-31'),
+(10048,'1963-07-11','Florian','Syrotiuk','M','1985-02-24'),
+(10049,'1961-04-24','Basil','Tramer','F','1992-05-04'),
+(10050,'1958-05-21','Yinghua','Dredge','M','1990-12-25'),
+(10051,'1953-07-28','Hidefumi','Caine','M','1992-10-15'),
+(10052,'1961-02-26','Heping','Nitsch','M','1988-05-21'),
+(10053,'1954-09-13','Sanjiv','Zschoche','F','1986-02-04'),
+(10054,'1957-04-04','Mayumi','Schueller','M','1995-03-13');
+
+
+CREATE DATABASE emp_2;
+
+USE emp_2;
+
+CREATE TABLE employees_1 (
+ emp_no INT NOT NULL,
+ birth_date DATE NOT NULL,
+ first_name VARCHAR(14) NOT NULL,
+ last_name VARCHAR(16) NOT NULL,
+ gender ENUM ('M','F') NOT NULL,
+ hire_date DATE NOT NULL,
+ PRIMARY KEY (emp_no)
+);
+
+
+INSERT INTO `employees_1` VALUES
(10055,'1956-06-06','Georgy','Dredge','M','1992-04-27'),
+(10056,'1961-09-01','Brendon','Bernini','F','1990-02-01'),
+(10057,'1954-05-30','Ebbe','Callaway','F','1992-01-15'),
+(10058,'1954-10-01','Berhard','McFarlin','M','1987-04-13'),
+(10059,'1953-09-19','Alejandro','McAlpine','F','1991-06-26'),
+(10060,'1961-10-15','Breannda','Billingsley','M','1987-11-02'),
+(10061,'1962-10-19','Tse','Herber','M','1985-09-17'),
+(10062,'1961-11-02','Anoosh','Peyn','M','1991-08-30'),
+(10063,'1952-08-06','Gino','Leonhardt','F','1989-04-08'),
+(10064,'1959-04-07','Udi','Jansch','M','1985-11-20'),
+(10065,'1963-04-14','Satosi','Awdeh','M','1988-05-18'),
+(10066,'1952-11-13','Kwee','Schusler','M','1986-02-26'),
+(10067,'1953-01-07','Claudi','Stavenow','M','1987-03-04'),
+(10068,'1962-11-26','Charlene','Brattka','M','1987-08-07'),
+(10069,'1960-09-06','Margareta','Bierman','F','1989-11-05'),
+(10070,'1955-08-20','Reuven','Garigliano','M','1985-10-14'),
+(10071,'1958-01-21','Hisao','Lipner','M','1987-10-01'),
+(10072,'1952-05-15','Hironoby','Sidou','F','1988-07-21'),
+(10073,'1954-02-23','Shir','McClurg','M','1991-12-01'),
+(10074,'1955-08-28','Mokhtar','Bernatsky','F','1990-08-13'),
+(10075,'1960-03-09','Gao','Dolinsky','F','1987-03-19'),
+(10076,'1952-06-13','Erez','Ritzmann','F','1985-07-09'),
+(10077,'1964-04-18','Mona','Azuma','M','1990-03-02'),
+(10078,'1959-12-25','Danel','Mondadori','F','1987-05-26'),
+(10079,'1961-10-05','Kshitij','Gils','F','1986-03-27'),
+(10080,'1957-12-03','Premal','Baek','M','1985-11-19'),
+(10081,'1960-12-17','Zhongwei','Rosen','M','1986-10-30'),
+(10082,'1963-09-09','Parviz','Lortz','M','1990-01-03'),
+(10083,'1959-07-23','Vishv','Zockler','M','1987-03-31'),
+(10084,'1960-05-25','Tuval','Kalloufi','M','1995-12-15');
+
+
+CREATE TABLE employees_2(
+ emp_no INT NOT NULL,
+ birth_date DATE NOT NULL,
+ first_name VARCHAR(14) NOT NULL,
+ last_name VARCHAR(16) NOT NULL,
+ gender ENUM ('M','F') NOT NULL,
+ hire_date DATE NOT NULL,
+ PRIMARY KEY (emp_no)
+);
+
+INSERT INTO `employees_2` VALUES
(10085,'1962-11-07','Kenroku','Malabarba','M','1994-04-09'),
+(10086,'1962-11-19','Somnath','Foote','M','1990-02-16'),
+(10087,'1959-07-23','Xinglin','Eugenio','F','1986-09-08'),
+(10088,'1954-02-25','Jungsoon','Syrzycki','F','1988-09-02'),
+(10089,'1963-03-21','Sudharsan','Flasterstein','F','1986-08-12'),
+(10090,'1961-05-30','Kendra','Hofting','M','1986-03-14'),
+(10091,'1955-10-04','Amabile','Gomatam','M','1992-11-18'),
+(10092,'1964-10-18','Valdiodio','Niizuma','F','1989-09-22'),
+(10093,'1964-06-11','Sailaja','Desikan','M','1996-11-05'),
+(10094,'1957-05-25','Arumugam','Ossenbruggen','F','1987-04-18'),
+(10095,'1965-01-03','Hilari','Morton','M','1986-07-15'),
+(10096,'1954-09-16','Jayson','Mandell','M','1990-01-14'),
+(10097,'1952-02-27','Remzi','Waschkowski','M','1990-09-15'),
+(10098,'1961-09-23','Sreekrishna','Servieres','F','1985-05-13'),
+(10099,'1956-05-25','Valter','Sullins','F','1988-10-18'),
+(10100,'1953-04-21','Hironobu','Haraldson','F','1987-09-21'),
+(10101,'1952-04-15','Perla','Heyers','F','1992-12-28'),
+(10102,'1959-11-04','Paraskevi','Luby','F','1994-01-26'),
+(10103,'1953-11-26','Akemi','Birch','M','1986-12-02'),
+(10104,'1961-11-19','Xinyu','Warwick','M','1987-04-16'),
+(10105,'1962-02-05','Hironoby','Piveteau','M','1999-03-23'),
+(10106,'1952-08-29','Eben','Aingworth','M','1990-12-19'),
+(10107,'1956-06-13','Dung','Baca','F','1994-03-22'),
+(10108,'1952-04-07','Lunjin','Giveon','M','1986-10-02'),
+(10109,'1958-11-25','Mariusz','Prampolini','F','1993-06-16'),
+(10110,'1957-03-07','Xuejia','Ullian','F','1986-08-22'),
+(10111,'1963-08-29','Hugo','Rosis','F','1988-06-19'),
+(10112,'1963-08-13','Yuichiro','Swick','F','1985-10-08'),
+(10113,'1963-11-13','Jaewon','Syrzycki','M','1989-12-24'),
+(10114,'1957-02-16','Munir','Demeyer','F','1992-07-17'),
+(10115,'1964-12-25','Chikara','Rissland','M','1986-01-23'),
+(10116,'1955-08-26','Dayanand','Czap','F','1985-05-28');
+```
+
+## 4. Doris 安装配置
+
+这里我们以单机版为例
+
+首先下载doris 1.0
release版本：[**https://dlcdn.apache.org/doris/1.0/1.0.0-incubating/apache-doris-1.0.0-incubating-bin.tar.gz**](https://dlcdn.apache.org/doris/1.0/1.0.0-incubating/apache-doris-1.0.0-incubating-bin.tar.gz)
+
+解压到指定目录
+
+```
+tar zxvf apache-doris-1.0.0-incubating-bin.tar.gz -C doris-1.0
+```
+
+解压后的目录结构是这样：
+
+```
+.
+├── apache_hdfs_broker
+│ ├── bin
+│ ├── conf
+│ └── lib
+├── be
+│ ├── bin
+│ ├── conf
+│ ├── lib
+│ ├── log
+│ ├── minidump
+│ ├── storage
+│ └── www
+├── derby.log
+├── fe
+│ ├── bin
+│ ├── conf
+│ ├── doris-meta
+│ ├── lib
+│ ├── log
+│ ├── plugins
+│ ├── spark-dpp
+│ ├── temp_dir
+│ └── webroot
+└── udf
+ ├── include
+ └── lib
+```
+
+
+
+配置fe和be
+
+```
+cd doris-1.0
+# 配置 fe.conf 和 be.conf,这两个文件分别在fe和be的conf目录下
+打开这个 priority_networks
+修改成自己的IP地址，注意这里是CIDR方式配置IP地址
+例如我本地的IP是172.19.0.12，我的配置如下：
+priority_networks = 172.19.0.0/24
+
+######
+在be.conf配置文件最后加上下面这个配置
+disable_stream_load_2pc=false
+```
+
+1. 注意这里默认只需要修改 `fe.conf` 和 `be.conf` 同样的上面这个配置就行了
+2. 默认fe元数据的目录在 `fe/doris-meta` 目录下
+3. be的数据存储在 `be/storage` 目录下
+
+启动 FE
+
+```
+sh fe/bin/start_fe.sh --daemon
+```
+
+启动BE
+
+```
+sh be/bin/start_be.sh --daemon
+```
+
+MySQL命令行连接FE，这里新安装的Doris集群默认用户是root和admin，密码是空
+
+```sql
+mysql -uroot -P9030 -h127.0.0.1
+Welcome to the MySQL monitor. Commands end with ; or \g.
+Your MySQL connection id is 41
+Server version: 5.7.37 Doris version trunk-440ad03
+
+Copyright (c) 2000, 2022, Oracle and/or its affiliates.
+
+Oracle is a registered trademark of Oracle Corporation and/or its
+affiliates. Other names may be trademarks of their respective
+owners.
+
+Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
+
+mysql> show frontends;
++--------------------------------+-------------+-------------+----------+-----------+---------+----------+----------+------------+------+-------+-------------------+---------------------+----------+--------+---------------+------------------+
+| Name | IP | EditLogPort | HttpPort |
QueryPort | RpcPort | Role | IsMaster | ClusterId | Join | Alive |
ReplayedJournalId | LastHeartbeat | IsHelper | ErrMsg | Version |
CurrentConnected |
++--------------------------------+-------------+-------------+----------+-----------+---------+----------+----------+------------+------+-------+-------------------+---------------------+----------+--------+---------------+------------------+
+| 172.19.0.12_9010_1654681464955 | 172.19.0.12 | 9010 | 8030 | 9030
| 9020 | FOLLOWER | true | 1690644599 | true | true | 381106
| 2022-06-22 18:13:34 | true | | trunk-440ad03 | Yes
|
++--------------------------------+-------------+-------------+----------+-----------+---------+----------+----------+------------+------+-------+-------------------+---------------------+----------+--------+---------------+------------------+
+1 row in set (0.01 sec)
+
+```
+
+将BE节点加入到集群中
+
+```
+mysql>alter system add backend "172.19.0.12:9050";
+```
+
+这里是你自己的IP地址
+
+查看BE
+
+```sql
+mysql> show backends;
++-----------+-----------------+-------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------------------------+--------+---------------+-------------------------------------------------------------------------------------------------------------------------------+
+| BackendId | Cluster | IP | HeartbeatPort | BePort |
HttpPort | BrpcPort | LastStartTime | LastHeartbeat | Alive |
SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity |
AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | Tag
| ErrMsg | Version | Status
|
++-----------+-----------------+-------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------------------------+--------+---------------+-------------------------------------------------------------------------------------------------------------------------------+
+| 10002 | default_cluster | 172.19.0.12 | 9050 | 9060 | 8040
| 8060 | 2022-06-22 12:51:58 | 2022-06-22 18:15:34 | true | false
| false | 4369 | 328.686 MB | 144.083 GB |
196.735 GB | 26.76 % | 26.76 % | {"location" : "default"} | |
trunk-440ad03 | {"lastSuccessReportTabletsTime":"2022-06-22
18:15:05","lastStreamLoadTime":-1,"isQueryDisabled":false,"isLoadDisabled":false}
|
++-----------+-----------------+-------------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------------------------+--------+---------------+-------------------------------------------------------------------------------------------------------------------------------+
+1 row in set (0.00 sec)
+```
+
+Doris单机版安装完成
+
+## 5. Flink安装配置
+
+### 5.1 下载安装Flink1.14.4
+
+```
+wget
https://dlcdn.apache.org/flink/flink-1.14.4/flink-1.14.5-bin-scala_2.12.tgz
+tar zxvf flink-1.14.4-bin-scala_2.12.tgz
+```
+
+然后需要将下面的依赖拷贝到Flink安装目录下的lib目录下，具体的依赖的lib文件如下：
+
+```
+wget
https://jiafeng-1308700295.cos.ap-hongkong.myqcloud.com/flink-doris-connector-1.14_2.12-1.0.0-SNAPSHOT.jar
+wget
https://repo1.maven.org/maven2/com/ververica/flink-sql-connector-mysql-cdc/2.2.1/flink-sql-connector-mysql-cdc-2.2.1.jar
+```
+
+启动Flink
+
+```
+bin/start-cluster.sh
+```
+
+启动后的界面如下：
+
+
+
+
+
+## 6. 开始同步数据到Doris
+
+### 6.1 创建Doris数据库及表
+
+```sql
+create database demo;
+use demo;
+CREATE TABLE all_employees_info (
+ emp_no int NOT NULL,
+ birth_date date,
+ first_name varchar(20),
+ last_name varchar(20),
+ gender char(2),
+ hire_date date,
+ database_name varchar(50),
+ table_name varchar(200)
+)
+UNIQUE KEY(`emp_no`, `birth_date`)
+DISTRIBUTED BY HASH(`birth_date`) BUCKETS 1
+PROPERTIES (
+"replication_allocation" = "tag.location.default: 1"
+);
+```
+
+### 6.2 进入Flink SQL Client
+
+```
+ bin/sql-client.sh embedded
+```
+
+
+
+开启 checkpoint，每隔10秒做一次 checkpoint
+
+Checkpoint 默认是不开启的，我们需要开启 Checkpoint 来让 Iceberg 可以提交事务。
+
+Source在启动时会扫描全表，将表按照主键分成多个chunk。并使用增量快照算法逐个读取每个chunk的数据。作业会周期性执行Checkpoint，记录下已经完成的chunk。当发生Failover时，只需要继续读取未完成的chunk。当chunk全部读取完后，会从之前获取的Binlog位点读取增量的变更记录。Flink作业会继续周期性执行Checkpoint，记录下Binlog位点，当作业发生Failover，便会从之前记录的Binlog位点继续处理，从而实现Exactly
Once语义
+
+```
+SET execution.checkpointing.interval = 10s;
+```
+
+>注意： 这里是演示，生产环境建议checkpoint间隔60秒
+
+### 6.3 创建MySQL CDC表
+
+在Flink SQL Client 下执行下面的 SQL
+
+```sql
+CREATE TABLE employees_source (
+ database_name STRING METADATA VIRTUAL,
+ table_name STRING METADATA VIRTUAL,
+ emp_no int NOT NULL,
+ birth_date date,
+ first_name STRING,
+ last_name STRING,
+ gender STRING,
+ hire_date date,
+ PRIMARY KEY (`emp_no`) NOT ENFORCED
+ ) WITH (
+ 'connector' = 'mysql-cdc',
+ 'hostname' = 'localhost',
+ 'port' = '3306',
+ 'username' = 'root',
+ 'password' = 'MyNewPass4!',
+ 'database-name' = 'emp_[0-9]+',
+ 'table-name' = 'employees_[0-9]+'
+ );
+```
+
+1. 'database-name' = 'emp_[0-9]+'： 这里是使用了正则表达式，同时连接多个库
+2. 'table-name' = 'employees_[0-9]+'：这里是使用了正则表达式，同时连接多个表
+
+查询CDC表，我们可以看到下面的数据，标识一切正常
+
+```sql
+select * from employees_source limit 10;
+```
+
+
+
+### 6.4 创建 Doris Sink 表
+
+```sql
+CREATE TABLE cdc_doris_sink (
+ emp_no int ,
+ birth_date STRING,
+ first_name STRING,
+ last_name STRING,
+ gender STRING,
+ hire_date STRING,
+ database_name STRING,
+ table_name STRING
+)
+WITH (
+ 'connector' = 'doris',
+ 'fenodes' = '172.19.0.12:8030',
+ 'table.identifier' = 'demo.all_employees_info',
+ 'username' = 'root',
+ 'password' = '',
+ 'sink.properties.two_phase_commit'='true',
+ 'sink.label-prefix'='doris_demo_emp_001'
+);
+```
+
+参数说明：
+
+1. connector ： 指定连接器是doris
+2. fenodes：doris FE节点IP地址及http port
+3. table.identifier ： Doris对应的数据库及表名
+4. username：doris用户名
+5. password：doris用户密码
+6. sink.properties.two_phase_commit：指定使用两阶段提交，这样在stream load的时候，会在http
header里加上 `two_phase_commit:true` ，不然会失败
+7. sink.label-prefix ： 这个是在两阶段提交的时候必须要加的一个参数，才能保证两端数据一致性，否则会失败
+8. 其他参数参考官方文档
https://doris.apache.org/zh-CN/docs/ecosystem/flink-doris-connector.html
+
+这个时候查询Doris sink表是没有数据的
+
+ ```sql
+ select * from cdc_doris_sink;
+ ```
+
+
+
+### 6.5 将数据插入到Doris表里
+
+执行下面的SQL：
+
+```sql
+insert into cdc_doris_sink
(emp_no,birth_date,first_name,last_name,gender,hire_date,database_name,table_name)
+select emp_no,cast(birth_date as string) as birth_date
,first_name,last_name,gender,cast(hire_date as string) as hire_date
,database_name,table_name from employees_source;
+```
+
+然后我们可以看到Flink WEB UI上的任务运行信息
+
+
+
+
+
+这里我们可以看看TaskManager的日志信息，会发现这里是使用两阶段提交的，而且数据是通过http
chunked方式不断朝BE端进行传输的，知道Checkpoint，才会停止。Checkpoint完成后会继续下一个任务的提交。
+
+```log
+2022-06-22 19:04:01,350 INFO
io.debezium.relational.history.DatabaseHistoryMetrics [] - Started
database history recovery
+2022-06-22 19:04:01,350 INFO
io.debezium.relational.history.DatabaseHistoryMetrics [] - Finished
database history recovery of 0 change(s) in 0 ms
+2022-06-22 19:04:01,351 INFO io.debezium.util.Threads
[] - Requested thread factory for connector MySqlConnector, id =
mysql_binlog_source named = binlog-client
+2022-06-22 19:04:01,352 INFO
io.debezium.connector.mysql.MySqlStreamingChangeEventSource [] - Skip 0 events
on streaming start
+2022-06-22 19:04:01,352 INFO
io.debezium.connector.mysql.MySqlStreamingChangeEventSource [] - Skip 0 rows
on streaming start
+2022-06-22 19:04:01,352 INFO io.debezium.util.Threads
[] - Creating thread
debezium-mysqlconnector-mysql_binlog_source-binlog-client
+2022-06-22 19:04:01,374 INFO io.debezium.util.Threads
[] - Creating thread
debezium-mysqlconnector-mysql_binlog_source-binlog-client
+2022-06-22 19:04:01,381 INFO
io.debezium.connector.mysql.MySqlStreamingChangeEventSource [] - Connected to
MySQL binlog at localhost:3306, starting at MySqlOffsetContext
[sourceInfoSchema=Schema{io.debezium.connector.mysql.Source:STRUCT},
sourceInfo=SourceInfo [currentGtid=null,
currentBinlogFilename=mysql_bin.000005, currentBinlogPosition=211725,
currentRowNumber=0, serverId=0, sourceTime=null, threadId=-1,
currentQuery=null, tableIds=[], databaseName=null], partition={server=mysql_bi
[...]
+2022-06-22 19:04:01,381 INFO io.debezium.util.Threads
[] - Creating thread
debezium-mysqlconnector-mysql_binlog_source-binlog-client
+2022-06-22 19:04:01,381 INFO
io.debezium.connector.mysql.MySqlStreamingChangeEventSource [] - Waiting for
keepalive thread to start
+2022-06-22 19:04:01,497 INFO
io.debezium.connector.mysql.MySqlStreamingChangeEventSource [] - Keepalive
thread is running
+2022-06-22 19:04:08,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:04:08,321 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6963,
+ "Label": "doris_demo_001_0_1",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 634,
+ "NumberLoadedRows": 634,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 35721,
+ "LoadTimeMs": 9046,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9041,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:04:08,321 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:04:08,321 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_2
+2022-06-22 19:04:08,321 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:04:08,325 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 1
+2022-06-22 19:04:08,329 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6963] commit successfully."
+}
+2022-06-22 19:04:18,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:04:18,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6964,
+ "Label": "doris_demo_001_0_2",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9988,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9983,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:04:18,310 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:04:18,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_3
+2022-06-22 19:04:18,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:04:18,312 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 2
+2022-06-22 19:04:18,317 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6964] commit successfully."
+}
+2022-06-22 19:04:28,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:04:28,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6965,
+ "Label": "doris_demo_001_0_3",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9998,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9993,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:04:28,308 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:04:28,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_4
+2022-06-22 19:04:28,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:04:28,311 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 3
+2022-06-22 19:04:28,316 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6965] commit successfully."
+}
+2022-06-22 19:04:38,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:04:38,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6966,
+ "Label": "doris_demo_001_0_4",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9999,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9994,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:04:38,308 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:04:38,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_5
+2022-06-22 19:04:38,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:04:38,311 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 4
+2022-06-22 19:04:38,317 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6966] commit successfully."
+}
+2022-06-22 19:04:48,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:04:48,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6967,
+ "Label": "doris_demo_001_0_5",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 10000,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9996,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:04:48,310 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:04:48,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_6
+2022-06-22 19:04:48,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:04:48,312 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 5
+2022-06-22 19:04:48,317 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6967] commit successfully."
+}
+2022-06-22 19:04:58,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:04:58,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6968,
+ "Label": "doris_demo_001_0_6",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9998,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9993,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:04:58,308 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:04:58,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_7
+2022-06-22 19:04:58,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:04:58,311 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 6
+2022-06-22 19:04:58,316 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6968] commit successfully."
+}
+2022-06-22 19:05:08,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:05:08,309 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6969,
+ "Label": "doris_demo_001_0_7",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9999,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9995,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:05:08,309 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:05:08,309 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_8
+2022-06-22 19:05:08,309 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:05:08,311 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 7
+2022-06-22 19:05:08,316 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6969] commit successfully."
+}
+2022-06-22 19:05:18,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:05:18,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6970,
+ "Label": "doris_demo_001_0_8",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9999,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9993,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:05:18,308 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:05:18,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_9
+2022-06-22 19:05:18,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:05:18,311 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 8
+2022-06-22 19:05:18,317 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6970] commit successfully."
+}
+2022-06-22 19:05:28,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:05:28,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6971,
+ "Label": "doris_demo_001_0_9",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 10000,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9996,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:05:28,310 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:05:28,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_10
+2022-06-22 19:05:28,310 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:05:28,315 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 9
+2022-06-22 19:05:28,320 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6971] commit successfully."
+}
+2022-06-22 19:05:38,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:05:38,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6972,
+ "Label": "doris_demo_001_0_10",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 0,
+ "NumberLoadedRows": 0,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 0,
+ "LoadTimeMs": 9998,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 9992,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:05:38,308 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:05:38,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_11
+2022-06-22 19:05:38,308 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:05:38,311 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 10
+2022-06-22 19:05:38,316 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6972] commit successfully."
+}
+2022-06-22 19:05:48,303 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
stopped.
+2022-06-22 19:05:48,315 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - load Result {
+ "TxnId": 6973,
+ "Label": "doris_demo_001_0_11",
+ "TwoPhaseCommit": "true",
+ "Status": "Success",
+ "Message": "OK",
+ "NumberTotalRows": 520,
+ "NumberLoadedRows": 520,
+ "NumberFilteredRows": 0,
+ "NumberUnselectedRows": 0,
+ "LoadBytes": 29293,
+ "LoadTimeMs": 10005,
+ "BeginTxnTimeMs": 0,
+ "StreamLoadPutTimeMs": 0,
+ "ReadDataTimeMs": 0,
+ "WriteDataTimeMs": 10001,
+ "CommitAndPublishTimeMs": 0
+}
+
+2022-06-22 19:05:48,315 INFO org.apache.doris.flink.sink.writer.RecordBuffer
[] - start buffer data, read queue size 0, write queue size 3
+2022-06-22 19:05:48,315 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - stream load
started for doris_demo_001_0_12
+2022-06-22 19:05:48,315 INFO
org.apache.doris.flink.sink.writer.DorisStreamLoad [] - start execute
load
+2022-06-22 19:05:48,322 INFO
org.apache.flink.streaming.runtime.operators.sink.AbstractStreamingCommitterHandler
[] - Committing the state for checkpoint 11
+2022-06-22 19:05:48,327 INFO
org.apache.doris.flink.sink.committer.DorisCommitter [] - load result {
+ "status": "Success",
+ "msg": "transaction [6973] commit successfully."
+}
+```
+
+
+
+### 6.6 查询Doris 数据
+
+这里我是插入了636条数据，
+
+```sql
+mysql> select count(1) from all_employees_info ;
++----------+
+| count(1) |
++----------+
+| 634 |
++----------+
+1 row in set (0.01 sec)
+
+mysql> select * from all_employees_info limit 20;
++--------+------------+------------+-------------+--------+------------+---------------+-------------+
+| emp_no | birth_date | first_name | last_name | gender | hire_date |
database_name | table_name |
++--------+------------+------------+-------------+--------+------------+---------------+-------------+
+| 10001 | 1953-09-02 | Georgi | Facello | M | 1986-06-26 | emp_1
| employees_1 |
+| 10002 | 1964-06-02 | Bezalel | Simmel | F | 1985-11-21 | emp_1
| employees_1 |
+| 10003 | 1959-12-03 | Parto | Bamford | M | 1986-08-28 | emp_1
| employees_1 |
+| 10004 | 1954-05-01 | Chirstian | Koblick | M | 1986-12-01 | emp_1
| employees_1 |
+| 10005 | 1955-01-21 | Kyoichi | Maliniak | M | 1989-09-12 | emp_1
| employees_1 |
+| 10006 | 1953-04-20 | Anneke | Preusig | F | 1989-06-02 | emp_1
| employees_1 |
+| 10007 | 1957-05-23 | Tzvetan | Zielinski | F | 1989-02-10 | emp_1
| employees_1 |
+| 10008 | 1958-02-19 | Saniya | Kalloufi | M | 1994-09-15 | emp_1
| employees_1 |
+| 10009 | 1952-04-19 | Sumant | Peac | F | 1985-02-18 | emp_1
| employees_1 |
+| 10010 | 1963-06-01 | Duangkaew | Piveteau | F | 1989-08-24 | emp_1
| employees_1 |
+| 10011 | 1953-11-07 | Mary | Sluis | F | 1990-01-22 | emp_1
| employees_1 |
+| 10012 | 1960-10-04 | Patricio | Bridgland | M | 1992-12-18 | emp_1
| employees_1 |
+| 10013 | 1963-06-07 | Eberhardt | Terkki | M | 1985-10-20 | emp_1
| employees_1 |
+| 10014 | 1956-02-12 | Berni | Genin | M | 1987-03-11 | emp_1
| employees_1 |
+| 10015 | 1959-08-19 | Guoxiang | Nooteboom | M | 1987-07-02 | emp_1
| employees_1 |
+| 10016 | 1961-05-02 | Kazuhito | Cappelletti | M | 1995-01-27 | emp_1
| employees_1 |
+| 10017 | 1958-07-06 | Cristinel | Bouloucos | F | 1993-08-03 | emp_1
| employees_1 |
+| 10018 | 1954-06-19 | Kazuhide | Peha | F | 1987-04-03 | emp_1
| employees_1 |
+| 10019 | 1953-01-23 | Lillian | Haddadi | M | 1999-04-30 | emp_1
| employees_1 |
+| 10020 | 1952-12-24 | Mayuko | Warwick | M | 1991-01-26 | emp_1
| employees_1 |
++--------+------------+------------+-------------+--------+------------+---------------+-------------+
+20 rows in set (0.00 sec)
+```
+
+### 6.7 测试删除
+
+```sql
+mysql> use emp_2;
+Reading table information for completion of table and column names
+You can turn off this feature to get a quicker startup with -A
+
+Database changed
+mysql> show tables;
++-----------------+
+| Tables_in_emp_2 |
++-----------------+
+| employees_1 |
+| employees_2 |
++-----------------+
+2 rows in set (0.00 sec)
+
+mysql> delete from employees_2 where emp_no in (12013,12014,12015);
+Query OK, 3 rows affected (0.01 sec)
+```
+
+验证Doris数据删除
+
+```sql
+mysql> select count(1) from all_employees_info ;
++----------+
+| count(1) |
++----------+
+| 631 |
++----------+
+1 row in set (0.01 sec)
+```
+
+
+
+## 7. 总结
+
+本问主要介绍了FLink CDC分库分表怎么实时同步，并结合Apache Doris Flink Connector最新版本整合的Flink 2PC 和
Doris Stream Load 2PC的机制及整合原理，使用方法等。
+
+希望能给大家带来一点帮助。
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