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OMS Documentation What is OMS Community Edition? Terms OMS Community Edition HA Overview Hierarchical functional system Basic components Limitations Data migration process Data synchronization process Deployment modes System and network requirements Memory and disk requirements Prepare the environment Deploy OMS Community Edition on a single node Deploy OMS Community Edition on multiple nodes in a single region Deploy OMS Community Edition on multiple nodes in multiple regions Integrate the OIDC protocol into OMS Community Edition to implement SSO Scale out OMS Community Edition Check the deployment Deploy a time-series database (Optional) Log on to the console of OMS Community Edition Overview Configure user information Change your logon password Log off Overview Migrate data from a MySQL database to OceanBase Database Community Edition Migrate data from OceanBase Database Community Edition to a MySQL database Migrate data from HBase to OBKV Migrate data between instances of OceanBase Database Community Edition Migrate data in active-active disaster recovery scenarios Migrate data from a TiDB database to OceanBase Database Community Edition Migrate data from a PostgreSQL database to OceanBase Database Community Edition View the details of a data migration project Change the name of a data migration project View and modify migration objects Manage computing platforms Use tags to manage data migration projects Perform batch operations on data migration projects Download and import settings of migration objects Start and pause a data migration project Release and delete a data migration project DML filtering DDL synchronization Configure matching rules for migration objects Wildcard rules Rename a database table Use SQL conditions to filter data Create and update a heartbeat table Schema migration mechanisms Schema migration operations Set an incremental synchronization timestamp Supported DDL operations in incremental migration from OceanBase Community Edition to a MySQL database and limits Supported DDL operations in incremental migration between MySQL tenants of OceanBase Database Data synchronization overview Create a project to synchronize data from OceanBase Database Community Edition to a Kafka instance Create a project to synchronize data from OceanBase Database Community Edition to a RocketMQ instance View details of a data synchronization project Change the name of a data synchronization project View and modify synchronization objects Use tags to manage data synchronization projects Perform batch operations on data synchronization projects Download and import the settings of synchronization objects Start and pause a data synchronization project Release and delete a data synchronization project DML filtering DDL synchronization Rename a topic Use SQL conditions to filter data Column filtering Data formats Create an OceanBase-CE data source Create a MySQL data source Create a TiDB data source Create a Kafka data source Create a RocketMQ data source Create a PostgreSQL data source Create an HBase data source View data source information Copy a data source Edit a data source Delete a data source Create a database user User privileges Enable binlogs for the MySQL database O&M overview Go to the overview page View server information Update the quota View server logs View O&M tasks Skip a task or subtask Retry a task or subtask Overview Manage users Manage departments View project alerts View system alerts Manage alert settings
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What are the strategies for ensuring the message order in incremental data synchronization to Kafka

Last Updated:2024-04-18 03:40:56  Updated
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This topic describes the strategies for ensuring the message order for OceanBase Migration Service (OMS) to synchronize incremental data from a database to Kafka.

OMS 3.3.0 or later allows you to set the partition.mode parameter in the config.yaml file to one_partition or hash, which specifies the partitioning strategy for pushing messages to Kafka. In OMS V3.3.0 or later, you can set Partitioning Rules to One or Hash when you create a project to synchronize data to Kafka.

  • One indicates that all data is delivered to queue 0 on the destination Kafka instance. In this case, data delivered to queue 0 on the destination is aggregated by transaction. The synchronization of data of a transaction starts only after the synchronization of data of the previous transaction is completed. The transaction order and change order within a transaction are guaranteed.

    The advantage of this synchronization strategy is that the message order is fully guaranteed. The disadvantage is that only a single partition on the destination is used. The maximum throughput of the data synchronization project is subject to the throughput of a single Kafka queue.

  • Hash indicates that the data in the source is modular hashed based on the value of Sharding Columns, or the primary key or non-empty unique key of the table when the sharding column is unspecified, and the data is distributed and concurrently written to multiple queues on the destination Kafka instance.

    With this partitioning rule, data changes with the same sharding column value in the table are synchronized to the same queue on the destination Kafka instance. This ensures that the data changes are in exact order as they are committed in the source database. Data changes with different sharding column values may be delivered to different queues on the destination, because their hash values may differ. In this case, the data consumption sequence in the downstream may differ from the sequence in which they are committed in the source database. In other words, although a data change to table A occurs before a data change to table B, the change to table B may be written to the destination end before the change to table A.

    The advantage of this strategy is that multiple queues on the destination are used, which improves the maximum throughput of the link while ensuring the change order within each data entry.

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