如何在kafka jdbc connect源代码中过滤数据库中的表

thtygnil  于 2021-06-06  发布在  Kafka
关注(0)|答案(1)|浏览(389)

我在confluent社区平台中使用kafka connect来保持mysql数据库的同步。源和汇是mysql数据库。它不起作用。
我的情况有些问题：
同一台服务器上的其他数据库中有表，我不想将它们读入kafka，但kafka connect source一直在尝试读取其他数据库。
我想用 org.apache.kafka.connect.json.JsonConverter 在源连接器和接收器连接器中，但接收器连接器无法正确插入。
我想同步多个数据库，不同数据库中的表可能具有相同的表名，如何避免表名冲突和sink连接器正确路由kafka主题，将数据插入到正确的数据库中？mysql同步说明
kafka jdbc源连接器配置文件是：

{
       "name": "br-auths-3910472223-source",
       "config": {
       "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector",

       "key.converter": "org.apache.kafka.connect.json.JsonConverter",
       "key.converter.schemas.enable":"true",
       "value.converter": "org.apache.kafka.connect.json.JsonConverter",
"value.converter.schemas.enable":"true",

"tasks.max": "1",
"connection.url": "jdbc:mysql://localhost:3306/br_auths?user=root&password=123456",
"database.whitelist":"br_auths",
"table.blacklist": "br_auths.__migrationversions,br_auths.auths_service_apps",

"mode": "timestamp",
"timestamp.column.name": "utime",
"validate.non.null": "false",

"incrementing.column.name": "id",
"topic.prefix": "br_auths__"
}
}

kafka jdbc接收器连接器配置文件是：

{
"name": "br-auths-3910472223-sink",
"config": {
    "connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",

    "key.converter": "org.apache.kafka.connect.json.JsonConverter",
    "key.converter.schemas.enable":"true",
    "value.converter": "org.apache.kafka.connect.json.JsonConverter",
    "value.converter.schemas.enable":"true",

    "tasks.max": "1",
    "connection.url": "jdbc:mysql://rm-hp303a0n2vr8970.mysql.huhehaote.rds.aliyuncs.com:3306/dev-br-auths-391047222?user=br_auths&password=@123456",

    "topics": "br_auths__auths_roles,br_auths__auths_user_logins,br_auths__auths_user_roles,br_auths__auths_users,br_auths__auths_user_claims,br_auths__auths_user_tokens,br_auths__auths_role_claims", 

    "auto.create": "true",
    "insert.mode": "upsert",

    "transforms":"dropTopicPrefix",
    "transforms.dropTopicPrefix.type":"org.apache.kafka.connect.transforms.RegexRouter",
    "transforms.dropTopicPrefix.regex":"br_auths__(.*)",
    "transforms.dropTopicPrefix.replacement":"$1" 
}
}

我想为不同的数据库创建几对源和汇连接器，mysql server-a中的数据库a中的一些白名单表可以增量地与mysql server-b中的数据库a同步。
更新1：
我改为连接avro分布式、debezium源连接器和jdbc接收器连接器。源连接器是：

{
   "name":"br-auths-3910472223-source",
   "config":{
       "connector.class": "io.debezium.connector.mysql.MySqlConnector",
       "tasks.max": "1",
       "database.hostname": "localhost",
       "database.port": "3306",
       "database.user": "root",
       "database.password": "br123456",
       "database.useLegacyDatetimeCode": "false",
       "database.server.id": "184",
       "database.server.name": "local3910472223",
       "database.whitelist":"br_auths",
       "database.history.kafka.bootstrap.servers": "localhost:9092",
       "database.history.kafka.topic": "schema-changes.br-auths.local3910472223" ,
       "table.blacklist": "br_auths.__migrationversions,br_auths.auths_service_apps",
       "include.schema.changes": "true",
       "transforms": "route,TimestampConverter",
       "transforms.TimestampConverter.type": "org.apache.kafka.connect.transforms.TimestampConverter$Value",  
       "transforms.TimestampConverter.target.type": "string", 
       "transforms.TimestampConverter.field": "payload.after.ctime", 
       "transforms.TimestampConverter.format": "yyyy-MM-dd HH:mm:ss",
       "transforms.route.type": "org.apache.kafka.connect.transforms.RegexRouter",
       "transforms.route.regex": "([^.]+)\\.([^.]+)\\.([^.]+)",
       "transforms.route.replacement": "$2__$3"  
    }
}

Flume接头为：

{
"name": "br-auths-3910472223-sink",
"config": {
    "connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",
    "tasks.max": "1",
    "connection.url": "jdbc:mysql://rm-hp303a0n2.mysql.huhehaote.rds.aliyuncs.com:3306/dev-br-auths-391047222?useLegacyDatetimeCode=false&user=br_auths&password=123456",
    "dialect.name": "MySqlDatabaseDialect",
    "topics.regex": "br_auths__(.*)",        
    "transforms": "dropTopicPrefix,unwrap",
    "transforms.dropTopicPrefix.type":"org.apache.kafka.connect.transforms.RegexRouter",
    "transforms.dropTopicPrefix.regex":"br_auths__(.*)",
    "transforms.dropTopicPrefix.replacement":"$1",        
    "transforms.unwrap.type": "io.debezium.transforms.UnwrapFromEnvelope",
    "insert.mode": "upsert",
    "pk.fields": "Id",
    "pk.mode": "record_value"
    }
}

avro消息转换为json，如下所示：

{
    "schema": {
        "type": "struct",
        "fields": [
            {
                "type": "struct",
                "fields": [
                    {
                        "type": "string",
                        "optional": false,
                        "field": "Id"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "UserId"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "RoleId"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "APPID"
                    },
                    {
                        "type": "int32",
                        "optional": false,
                        "default": 0,
                        "field": "IsDeleted"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "name": "io.debezium.time.Timestamp",
                        "version": 1,
                        "default": 0,
                        "field": "ctime"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "name": "io.debezium.time.Timestamp",
                        "version": 1,
                        "default": 0,
                        "field": "utime"
                    }
                ],
                "optional": true,
                "name": "local3910472223.br_auths.auths_user_roles.Value",
                "field": "before"
            },
            {
                "type": "struct",
                "fields": [
                    {
                        "type": "string",
                        "optional": false,
                        "field": "Id"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "UserId"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "RoleId"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "APPID"
                    },
                    {
                        "type": "int32",
                        "optional": false,
                        "default": 0,
                        "field": "IsDeleted"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "name": "io.debezium.time.Timestamp",
                        "version": 1,
                        "default": 0,
                        "field": "ctime"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "name": "io.debezium.time.Timestamp",
                        "version": 1,
                        "default": 0,
                        "field": "utime"
                    }
                ],
                "optional": true,
                "name": "local3910472223.br_auths.auths_user_roles.Value",
                "field": "after"
            },
            {
                "type": "struct",
                "fields": [
                    {
                        "type": "string",
                        "optional": true,
                        "field": "version"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "name"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "field": "server_id"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "field": "ts_sec"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "gtid"
                    },
                    {
                        "type": "string",
                        "optional": false,
                        "field": "file"
                    },
                    {
                        "type": "int64",
                        "optional": false,
                        "field": "pos"
                    },
                    {
                        "type": "int32",
                        "optional": false,
                        "field": "row"
                    },
                    {
                        "type": "boolean",
                        "optional": true,
                        "default": false,
                        "field": "snapshot"
                    },
                    {
                        "type": "int64",
                        "optional": true,
                        "field": "thread"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "db"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "table"
                    },
                    {
                        "type": "string",
                        "optional": true,
                        "field": "query"
                    }
                ],
                "optional": false,
                "name": "io.debezium.connector.mysql.Source",
                "field": "source"
            },
            {
                "type": "string",
                "optional": false,
                "field": "op"
            },
            {
                "type": "int64",
                "optional": true,
                "field": "ts_ms"
            }
        ],
        "optional": false,
        "name": "local3910472223.br_auths.auths_user_roles.Envelope"
    },
    "payload": {
        "before": null,
        "after": {
            "Id": "DB4DA841364860D112C3C76BDCB36635",
            "UserId": "0000000000",
            "RoleId": "5b7e5f9b4bc00d89c4cf96ae",
            "APPID": "br.region2",
            "IsDeleted": 0,
            "ctime": 1550138524000,
            "utime": 1550138524000
        },
        "source": {
            "version": "0.8.3.Final",
            "name": "local3910472223",
            "server_id": 0,
            "ts_sec": 0,
            "gtid": null,
            "file": "mysql-bin.000003",
            "pos": 64606,
            "row": 0,
            "snapshot": true,
            "thread": null,
            "db": "br_auths",
            "table": "auths_user_roles",
            "query": null
        },
        "op": "c",
        "ts_ms": 1550568556614
    }
}

使用mysql datetime类型的列被序列化为一个大整数，jdbc接收器连接器试图插入mysql datetime列，但失败了。
所以我写了 transforms.TimestampConverter 但ctime、utime列没有更改。怎么了？

mysqlapache-kafkaapache-kafka-connectmysql-connector

1条答案

按热度按时间
vs91vp4v

vs91vp4v1#

如果您想保持数据库的同步，那么jdbc源连接器并不是最好的——您需要使用适当的基于日志的cdc，对于mysql，您可以使用debezium获得它。更多细节在这里。
如果你对这些数据不做任何其他事情，你需要Kafka吗？专用的mysql复制工具更合适吗？
你的具体问题。这篇文章将解决你的许多问题。特别地：
同一台服务器上的其他数据库中有表，我不想将它们读入kafka，但kafka connect source一直在尝试读取其他数据库。
结合使用 table.whitelist , table.blacklist ，和 schema.pattern 按要求。如果不能用一个连接器匹配整个图案，则需要使用多个连接器来实现所需的设置。
我想在源连接器和接收器连接器中都使用org.apache.kafka.connect.json.jsonconverter，但接收器连接器无法正确插入。
如果你不解释“不能正确插入”，很难回答这个问题。一般来说，我会使用avro，因为它有更丰富的模式支持和更高效的消息（没有嵌入式模式，模式存储在模式注册表中）。请参阅此处了解更多详细信息。
我想同步多个数据库，不同数据库中的表可能具有相同的表名，如何避免表名冲突和sink连接器正确路由kafka主题，将数据插入到正确的数据库中？
您将需要使用 topic.prefix 在源连接器上标记来自特定源的主题，然后进行单个消息转换 RegexRouter （正如您已经发现的）在源连接器和/或接收器连接器中进一步操作主题名称。您可能需要使用多个接收器连接器 topics.regex 选择要路由到特定数据库的特定主题。

赞(0）分享  回复(0）举报  2021-06-06
我来回答

相关问题

    查看更多

    热门标签

    更多
    JavaquerypythonNode开发语言requestUtil数据库Table后端算法LoggerMessageElementParser

    最新问答

    更多
    • 蜀ICP备2022004421号-2 NULL123 https://www.null123.com © All rights reserved
    • 本站内容来源互联网,如果侵犯您的权益请联系我们删除, 联系方式：448109455@qq.com