- Releases Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- SQL Developer Guide
- Python Developer Guide
- ETL Developer Guide
- FAQ
- Contact Us
- Releases Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- SQL Developer Guide
- Python Developer Guide
- ETL Developer Guide
- FAQ
- Contact Us
Overview
A ClickHouse data sink can write data to ClickHouse.
Note
The engine of ClickHouse data sink tables must be CollapsingMergeTree.
Mapping of common data types
For the data types supported by ClickHouse, see ClickHouse Data Types. The table below lists some of the common data types and their counterparts in Flink.
Flink | ClickHouse |
VARCHAR | String/FixedString(N) |
STRING | String/FixedString(N) |
BOOLEAN | There isn't a dedicated ClickHouse type for boolean. You can use UInt8 to store boolean data, limiting the valid values to 0 and 1, or use the string type, limiting the valid values to true and false. |
DECIMAL | Decimal32(S)/Decimal64(S)/Decimal128(S) |
TINYINT | Int8 |
SMALLINT | Int16 |
INTEGER | Int32 |
BIGINT | Int64 |
FLOAT | Float32 |
DOUBLE | Float64 |
DATE | Date |
TIMESTAMP | DateTime |
TIMESTAMP WITH LOCAL TIME ZONE | DateTime. Example: DateTime64(3, 'Asia/Shanghai'). |
Notes
Primary key
To ensure that update and delete operations are synced as expected, make sure you define the primary key correctly using the CREATE TABLE statement.
Collapsed fields
The CollapsingMergeTree engine of ClickHouse adds the logic of rows collapsing to data parts merge algorithm. You can specify collapsed fields using
ENGINE = CollapsingMergeTree(Sign) when creating a table. To learn more, see the ClickHouse document.WITH parameters
ClickHouse data sinks are developed based on the data warehouse ClickHouse. The two have identical WITH parameters. For details, see ClickHouse.
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