Apache Paimon 使用 MySQL CDC 获取数据

猫猫爱吃小鱼粮2024-03-16 15:38

Paimon支持使用（CDC）同步来自不同数据库的更改，此功能需要Flink及其CDC连接器。

准备 CDC Bundled Jar 依赖

复制代码 
flink-sql-connector-mysql-cdc-*.jar

同步表

在Flink DataStream中或通过flink run使用MySqlSyncTableAction，可以将MySQL中的一个或多个表同步到一个Paimon表中。

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_table
    --warehouse <warehouse-path> \
    --database <database-name> \
    --table <table-name> \
    [--partition_keys <partition_keys>] \
    [--primary_keys <primary-keys>] \
    [--type_mapping <option1,option2...>] \
    [--computed_column <'column-name=expr-name(args[, ...])'> [--computed_column ...]] \
    [--metadata_column <metadata-column>] \
    [--mysql_conf <mysql-cdc-source-conf> [--mysql_conf <mysql-cdc-source-conf> ...]] \
    [--catalog_conf <paimon-catalog-conf> [--catalog_conf <paimon-catalog-conf> ...]] \
    [--table_conf <paimon-table-sink-conf> [--table_conf <paimon-table-sink-conf> ...]]
Configuration Description
--warehouse The path to Paimon warehouse.
--database The database name in Paimon catalog.
--table The Paimon table name.
--partition_keys The partition keys for Paimon table. If there are multiple partition keys, connect them with comma, for example "dt,hh,mm".
--primary_keys The primary keys for Paimon table. If there are multiple primary keys, connect them with comma, for example "buyer_id,seller_id".
--type_mapping It is used to specify how to map MySQL data type to Paimon type. Supported options:"tinyint1-not-bool": maps MySQL TINYINT(1) to TINYINT instead of BOOLEAN."to-nullable": ignores all NOT NULL constraints (except for primary keys). This is used to solve the problem that Flink cannot accept the MySQL 'ALTER TABLE ADD COLUMN column type NOT NULL DEFAULT x' operation."to-string": maps all MySQL types to STRING."char-to-string": maps MySQL CHAR(length)/VARCHAR(length) types to STRING."longtext-to-bytes": maps MySQL LONGTEXT types to BYTES."bigint-unsigned-to-bigint": maps MySQL BIGINT UNSIGNED, BIGINT UNSIGNED ZEROFILL, SERIAL to BIGINT. You should ensure overflow won't occur when using this option.
--computed_column The definitions of computed columns. The argument field is from MySQL table field name. See here for a complete list of configurations.
--metadata_column --metadata_column is used to specify which metadata columns to include in the output schema of the connector. Metadata columns provide additional information related to the source data, for example: --metadata_column table_name,database_name,op_ts. See its document for a complete list of available metadata.
--mysql_conf The configuration for Flink CDC MySQL sources. Each configuration should be specified in the format "key=value". hostname, username, password, database-name and table-name are required configurations, others are optional. See its document for a complete list of configurations.
--catalog_conf The configuration for Paimon catalog. Each configuration should be specified in the format "key=value". See here for a complete list of catalog configurations.
--table_conf The configuration for Paimon table sink. Each configuration should be specified in the format "key=value". See here for a complete list of table configurations.

如果指定的Paimon表不存在，将自动创建该表。它的模式将从所有指定的MySQL表中派生出来。如果Paimon表已经存在，其模式将与所有指定MySQL表的模式进行比较。

示例1：将表同步到一个Paimon表中

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_table \
    --warehouse hdfs:///path/to/warehouse \
    --database test_db \
    --table test_table \
    --partition_keys pt \
    --primary_keys pt,uid \
    --computed_column '_year=year(age)' \
    --mysql_conf hostname=127.0.0.1 \
    --mysql_conf username=root \
    --mysql_conf password=123456 \
    --mysql_conf database-name='source_db' \
    --mysql_conf table-name='source_table1|source_table2' \
    --catalog_conf metastore=hive \
    --catalog_conf uri=thrift://hive-metastore:9083 \
    --table_conf bucket=4 \
    --table_conf changelog-producer=input \
    --table_conf sink.parallelism=4

如上示例所示，mysql_conf的表名支持正则表达式，以监控满足正则表达式的多个表。所有表的模式将合并到一个Paimon表模式中。

示例2：将分片同步到一个Paimon表中

可以使用正则表达式设置"数据库名称"来捕获多个数据库。典型的场景是，表"source_table"被拆分为数据库"source_db1"，"source_db2"...，然后将所有"source_table"的数据同步到一个Paimon表中。

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_table \
    --warehouse hdfs:///path/to/warehouse \
    --database test_db \
    --table test_table \
    --partition_keys pt \
    --primary_keys pt,uid \
    --computed_column '_year=year(age)' \
    --mysql_conf hostname=127.0.0.1 \
    --mysql_conf username=root \
    --mysql_conf password=123456 \
    --mysql_conf database-name='source_db.+' \
    --mysql_conf table-name='source_table' \
    --catalog_conf metastore=hive \
    --catalog_conf uri=thrift://hive-metastore:9083 \
    --table_conf bucket=4 \
    --table_conf changelog-producer=input \
    --table_conf sink.parallelism=4

同步数据库

通过在Flink DataStream或通过flink run使用MySqlSyncDatabaseAction，可以将整个MySQL数据库同步到一个Paimon数据库中。

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_database
    --warehouse <warehouse-path> \
    --database <database-name> \
    [--ignore_incompatible <true/false>] \
    [--merge_shards <true/false>] \
    [--table_prefix <paimon-table-prefix>] \
    [--table_suffix <paimon-table-suffix>] \
    [--including_tables <mysql-table-name|name-regular-expr>] \
    [--excluding_tables <mysql-table-name|name-regular-expr>] \
    [--mode <sync-mode>] \
    [--metadata_column <metadata-column>] \
    [--type_mapping <option1,option2...>] \
    [--mysql_conf <mysql-cdc-source-conf> [--mysql_conf <mysql-cdc-source-conf> ...]] \
    [--catalog_conf <paimon-catalog-conf> [--catalog_conf <paimon-catalog-conf> ...]] \
    [--table_conf <paimon-table-sink-conf> [--table_conf <paimon-table-sink-conf> ...]]
Configuration Description
--warehouse The path to Paimon warehouse.
--database The database name in Paimon catalog.
--ignore_incompatible It is default false, in this case, if MySQL table name exists in Paimon and their schema is incompatible,an exception will be thrown. You can specify it to true explicitly to ignore the incompatible tables and exception.
--merge_shards It is default true, in this case, if some tables in different databases have the same name, their schemas will be merged and their records will be synchronized into one Paimon table. Otherwise, each table's records will be synchronized to a corresponding Paimon table, and the Paimon table will be named to 'databaseName_tableName' to avoid potential name conflict.
--table_prefix The prefix of all Paimon tables to be synchronized. For example, if you want all synchronized tables to have "ods_" as prefix, you can specify "--table_prefix ods_".
--table_suffix The suffix of all Paimon tables to be synchronized. The usage is same as "--table_prefix".
--including_tables It is used to specify which source tables are to be synchronized. You must use '|' to separate multiple tables.Because '|' is a special character, a comma is required, for example: 'a|b|c'.Regular expression is supported, for example, specifying "--including_tables test|paimon.*" means to synchronize table 'test' and all tables start with 'paimon'.
--excluding_tables It is used to specify which source tables are not to be synchronized. The usage is same as "--including_tables". "--excluding_tables" has higher priority than "--including_tables" if you specified both.
--mode It is used to specify synchronization mode. Possible values:"divided" (the default mode if you haven't specified one): start a sink for each table, the synchronization of the new table requires restarting the job."combined": start a single combined sink for all tables, the new table will be automatically synchronized.
--metadata_column --metadata_column is used to specify which metadata columns to include in the output schema of the connector. Metadata columns provide additional information related to the source data, for example: --metadata_column table_name,database_name,op_ts. See its document for a complete list of available metadata.
--type_mapping It is used to specify how to map MySQL data type to Paimon type. Supported options:"tinyint1-not-bool": maps MySQL TINYINT(1) to TINYINT instead of BOOLEAN."to-nullable": ignores all NOT NULL constraints (except for primary keys). This is used to solve the problem that Flink cannot accept the MySQL 'ALTER TABLE ADD COLUMN column type NOT NULL DEFAULT x' operation."to-string": maps all MySQL types to STRING."char-to-string": maps MySQL CHAR(length)/VARCHAR(length) types to STRING."longtext-to-bytes": maps MySQL LONGTEXT types to BYTES."bigint-unsigned-to-bigint": maps MySQL BIGINT UNSIGNED, BIGINT UNSIGNED ZEROFILL, SERIAL to BIGINT. You should ensure overflow won't occur when using this option.
--mysql_conf The configuration for Flink CDC MySQL sources. Each configuration should be specified in the format "key=value". hostname, username, password, database-name and table-name are required configurations, others are optional. See its document for a complete list of configurations.
--catalog_conf The configuration for Paimon catalog. Each configuration should be specified in the format "key=value". See here for a complete list of catalog configurations.
--table_conf The configuration for Paimon table sink. Each configuration should be specified in the format "key=value". See here for a complete list of table configurations.

只有带有主键的表才会同步。

对于要同步的每个MySQL表，如果相应的Paimon表不存在，将自动创建该表。它的模式将从所有指定的MySQL表中派生出来。如果Paimon表已经存在，其模式将与所有指定MySQL表的模式进行比较。

示例1：同步整个数据库

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_database \
    --warehouse hdfs:///path/to/warehouse \
    --database test_db \
    --mysql_conf hostname=127.0.0.1 \
    --mysql_conf username=root \
    --mysql_conf password=123456 \
    --mysql_conf database-name=source_db \
    --catalog_conf metastore=hive \
    --catalog_conf uri=thrift://hive-metastore:9083 \
    --table_conf bucket=4 \
    --table_conf changelog-producer=input \
    --table_conf sink.parallelism=4

示例2：同步数据库下新添加的表

首先，假设Flink作业是在数据库source_db下同步表[产品、用户、地址]。

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_database \
    --warehouse hdfs:///path/to/warehouse \
    --database test_db \
    --mysql_conf hostname=127.0.0.1 \
    --mysql_conf username=root \
    --mysql_conf password=123456 \
    --mysql_conf database-name=source_db \
    --catalog_conf metastore=hive \
    --catalog_conf uri=thrift://hive-metastore:9083 \
    --table_conf bucket=4 \
    --table_conf changelog-producer=input \
    --table_conf sink.parallelism=4 \
    --including_tables 'product|user|address'

然后，希望该Job也同步包含历史数据的表[order, custom]。可以通过从之前的Job快照中恢复，从而重用作业的现有状态来实现这一点。恢复的Job将首先快照新添加的表，然后自动从上一个位置继续读取changelog。

从以前的快照恢复并添加新表进行同步的命令如下所示：

复制代码 
<FLINK_HOME>/bin/flink run \
    --fromSavepoint savepointPath \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_database \
    --warehouse hdfs:///path/to/warehouse \
    --database test_db \
    --mysql_conf hostname=127.0.0.1 \
    --mysql_conf username=root \
    --mysql_conf password=123456 \
    --mysql_conf database-name=source_db \
    --catalog_conf metastore=hive \
    --catalog_conf uri=thrift://hive-metastore:9083 \
    --table_conf bucket=4 \
    --including_tables 'product|user|address|order|custom'

注意：可以设置--mode combined启动，自动不同新增加的表而无需重启Job。

示例3：同步和合并多个碎片

假设有多个数据库分片db1，db2，...每个数据库都有表tbl1，tbl2，...，可以同步所有的db.+.tbl.+到表test_db.tbl1, test_db.tbl2 ...。

复制代码 
<FLINK_HOME>/bin/flink run \
    /path/to/paimon-flink-action-0.7.0-incubating.jar \
    mysql_sync_database \
    --warehouse hdfs:///path/to/warehouse \
    --database test_db \
    --mysql_conf hostname=127.0.0.1 \
    --mysql_conf username=root \
    --mysql_conf password=123456 \
    --mysql_conf database-name='db.+' \
    --catalog_conf metastore=hive \
    --catalog_conf uri=thrift://hive-metastore:9083 \
    --table_conf bucket=4 \
    --table_conf changelog-producer=input \
    --table_conf sink.parallelism=4 \
    --including_tables 'tbl.+'

通过将数据库名称设置为正则表达式，同步作业将捕获匹配数据库下的所有表，并将同名的表合并到一个表中。

设置--merge_shards false，以防止合并分片。同步表将被命名为"databaseName_tableName"，以避免潜在的名称冲突。

常见问题

  1. 从MySQL中提取的数据汉字乱码
  • 在flink-conf.yaml设置env.java.opts: -Dfile.encoding=UTF-8（自Flink-1.17以来，该选项已更改为env.java.opts.all）。
相关推荐
遇到困难睡大觉哈哈8 分钟前
Git推送错误解决方案：`rejected -＞ master (fetch first)`
大数据·git·elasticsearch
Roam-G17 分钟前
Elasticsearch 证书问题解决
大数据·elasticsearch·jenkins
深蓝易网35 分钟前
为什么制造企业需要用MES管理系统升级改造车间
大数据·运维·人工智能·制造·devops
THRUSTER1111137 分钟前
MySQL-- 函数（单行函数）：数值函数， 字符串函数
数据库·mysql·函数·navicat·单行函数
橙序研工坊43 分钟前
MySQL的进阶语法7（索引-B+Tree 、Hash、聚集索引 、二级索引（回表查询）、索引的使用及设计原则
数据库·sql·mysql
青云交1 小时前
Java 大视界 -- Java 大数据在智能电网电力市场交易数据分析与策略制定中的关键作用（162）
java·大数据·数据分析·交易策略·智能电网·java 大数据·电力市场交易
宝哥大数据1 小时前
Flink内存模型--flink1.19.1
大数据·flink
Bonnie_12151 小时前
07-MySQL-事务的隔离级别以及底层原理
数据库·mysql
一个天蝎座 白勺 程序猿1 小时前
大数据（4.5）Hive聚合函数深度解析：从基础统计到多维聚合的12个生产级技巧
大数据·hive·hadoop
爱编程的王小美2 小时前
用户行为分析系统开发文档
大数据
热门推荐
01我决定放弃搞 Java 了02DeepSeek各版本说明与优缺点分析03如何在WPS和Word/Excel中直接使用DeepSeek功能04本地化部署AI知识库：基于Ollama+DeepSeek+AnythingLLM保姆级教程05苍穹外卖面试总结06从零安装 LLaMA-Factory 微调 Qwen 大模型成功及所有的坑07RAG 实践- Ollama+RagFlow 部署本地知识库08DeepSeek R1本地化部署 Ollama + Chatbox 打造最强 AI 工具09如何本地部署AI智能体平台，带你手搓一个AI Agent10Android下HWC以及drm_hwcomposer普法(上)