OpenSource ClickHouse

Preparation and Constraints

• Network requirements

  The OpenSource ClickHouse data source can communicate with CDM. This ensures smooth data transmission. For details, see Enabling Network Connectivity.

• Required permissions
  • Read permission: To enable database users of DataArts Migration to read data from OpenSource ClickHouse, you need to assign the users the read-only permission or at least the SELECT permission of ClickHouse.
  • Write permission: To enable database users of DataArts Migration to write data to OpenSource ClickHouse, you need to assign the users the write permission or at least the INSERT, CREATE TABLE, and DELETE permissions.
• Enabling ports

  ClickHouse JDBC port (8123): Port 8123 allows DataArts Migration to connect to ClickHouse through JDBC.

Supported Data Types

Supported Migration Scenarios

DataArts Migration supports the following modes for synchronizing on-premises data:

• Single table synchronization

  DataArts Migration supports table/file synchronization in data ingestion into a data lake or data migration to the cloud.

• Database and table shard synchronization

  DataArts Migration supports synchronization of data from multiple databases and tables in data ingestion into a data lake or data migration to the cloud.

• Entire DB migration

  DataArts Migrations supports synchronization of data from an on-premises database in data ingestion into a data lake or data migration to the cloud.

Database and table shard synchronization and entire DB migration are not supported in all regions. The following table lists the supported OpenSource ClickHouse migration scenarios.

Core Capabilities

• Connection configuration

  Configuration Item	Supported	Description
  SSL encryption	√	SSL encryption ensures secure data transmission.
  Connection configuration optimization	√	Connection configuration such as connectTimeout can be optimized to improve connection performance.

• Read capabilities

  Configuration Item	Supported	Description
  Shard concurrency	√	Horizontal sharding based on primary keys or common fields and multi-thread concurrent extraction significantly improve the throughput and efficiency.
  Dirty data processing	√	Abnormal data can be written to the dirty data bucket to prevent job failures caused by a small amount of abnormal data.
  Custom fields	√	You can add computed columns, constant columns, or masking functions for tasks to meet personalized service requirements.
  Incremental read	√	Where conditions can be used to deliver query requests for incremental data reading.
  Stream and batch reading	Batch reading	Data can be read from a large static dataset in batches and then centrally processed.

• Write capabilities

  Configuration Item	Supported	Description
  Pre- and post-import processing	√	Operations such as preSql can clean and process data before and after data import.
  Concurrent write	√	Concurrent write improves efficiency.
  Optimization of the number of written rows	√	You can set the number of rows written by each request in the connection to properly control the amount of data to be transmitted. This improves performance and prevents a transmission delay or the system from being overloaded when there is a large amount of data.
  Dirty data processing	x	Abnormal data cannot be written to the dirty data bucket to prevent job failures caused by a small amount of abnormal data.

Creating a Data Source

Create a data source in Management Center. For details, see Configuring Data Connection Parameters.

Creating an Offline Data Migration Job

Create an OpenSource ClickHouse migration job in DataArts Factory. For details, see Creating an Offline Processing Migration Job.

Best Practices

Configuring ClickHouse Connection Properties