Sink data from RisingWave to ClickHouse
This guide describes how to sink data from RisingWave to ClickHouse using the ClickHouse sink connector in RisingWave.
ClickHouse is a high-performance, column-oriented SQL database management system (DBMS) for online analytical processing (OLAP). For more information about ClickHouse, see ClickHouse official website.
Prerequisites
- Ensure you already have a ClickHouse table that you can sink data to. For additional guidance on creating a table and setting up ClickHouse, refer to this quick start guide.
- Ensure you have an upstream materialized view or source that you can sink data from.
We highly recommend using the deduplication engine, like ReplacingMergeTree, in ClickHouse. This is because it addresses the potential problem of duplicate writes in ClickHouse during RisingWave recovery when primary keys can be duplicated.
Syntax
Parameters
Parameter Names | Description |
---|---|
type | Required. Specify if the sink should be upsert or append-only. If creating an upsert sink, see the Overview on when to define the primary key and Upsert sinks on limitations. |
primary_key | Optional. A string of a list of column names, separated by commas, that specifies the primary key of the ClickHouse sink. |
clickhouse.url | Required. Address of the ClickHouse server that you want to sink data to. Format: http://ip:port . The default port is 8123. |
clickhouse.user | Required. User name for accessing the ClickHouse server. |
clickhouse.password | Required. Password for accessing the ClickHouse server. |
clickhouse.database | Required. Name of the ClickHouse database that you want to sink data to. |
clickhouse.table | Required. Name of the ClickHouse table that you want to sink data to. |
commit_checkpoint_interval | Optional. Commit every N checkpoints (N > 0). Default value is 10. The behavior of this field also depends on the sink_decouple setting:
|
clickhouse.delete.column | Optional. You can run an upsert sink using the ReplacingMergeTree engine. When using the ReplacingMergeTree engine, you can specify the delete column with this parameter. |
Upsert sinks
While RisingWave supports append-only
sinks for all ClickHouse engines, support for upsert
sinks is limited. Additionally, for ReplacingMergeTree engines, an append-only
sink will not insert duplicate data.
RisingWave supports upsert
sinks for the following ClickHouse engines:
- CollapsingMergeTree:
DELETE
operations are transformed intoINSERT with SIGN = -1
. - VersionedCollapsingMergeTree:
DELETE
operations are transformed intoINSERT with SIGN = -1
. - ReplacingMergeTree:
DELETE
operations are transformed intoINSERT with SIGN = 1
.
Examples
This section includes several examples that you can use if you want to quickly experiment with sinking data to ClickHouse.
Create a ClickHouse table (if you do not already have one)
For example, let’s consider creating a basic ClickHouse table with the primary key as seq_id
and the ENGINE set to ReplacingMergeTree
. It’s important to emphasize that without using ReplacingMergeTree
or other deduplication techniques, there is a significant risk of duplicate writes to ClickHouse.
Note that only S3-compatible object store is supported, such as AWS S3 or MinIO.
Create an upstream materialized view or source
The following query creates an append-only source. For more details on creating a source, see CREATE SOURCE.
Another option is to create an upsert table, which supports in-place updates. For more details on creating a table, see CREATE TABLE .
Append-only sink from append-only source
If you have an append-only source and want to create an append-only sink, set type = append-only
in the CREATE SINK
SQL query.
Append-only sink from upsert source
If you have an upsert source and want to create an append-only sink, set type = append-only
and force_append_only = true
. This will ignore delete messages in the upstream, and turn upstream update messages into insert messages.
Upsert sink from upsert source
If you have an upsert source and want to create an upsert sink, set type = upsert
. When the sink type is upsert, be sure to set the primary_key
field to specify the primary key of the downstream ClickHouse table.
Data type mapping
RisingWave Data Type | ClickHouse Data Type |
---|---|
boolean | Bool |
smallint | Int16 or UInt16 |
integer | Int32 or UInt32 |
bigint | Int64 or UInt64 |
real | Float32 |
double precision | Float64 |
decimal | Decimal |
character varying | String |
bytea | Not supported |
date | Date32 |
time without time zone | Not supported |
timestamp | Not supported. Please convert timestamp to timestamptz within RisingWave before sinking. |
timestamptz | DateTime64 |
interval | Not supported |
struct | Nested |
array | Array |
JSONB | Not supported |
In ClickHouse, the Nested
data type doesn’t support multiple levels of nesting. Therefore, when sinking RisingWave’s struct
data to ClickHouse, you need to flatten or restructure the nested data to align with ClickHouse’s requirement.
Before v1.9, when inserting data into a ClickHouse sink, an error would be reported if the values were “nan (not a number)”, “inf (infinity)”, or “-inf (-infinity)“. Since v1.9, we have made a change to this behavior. If the ClickHouse column is nullable, we will insert null values in such cases. If the column is not nullable, we will insert 0
instead.
Please be aware that the range of specific values varies among ClickHouse types and RisingWave types. Refer to the table below for detailed information.
ClickHouse type | RisingWave type | ClickHouse range | RisingWave range |
---|---|---|---|
Date32 | DATE | 1900-01-01 to 2299-12-31 | 0001-01-01 to 9999-12-31 |
DateTime64 | TIMESTAMPTZ | 1900-01-01 00:00:00 to 2299-12-31 23:59:59.99999999 | 0001-01-01 00:00:00 to 9999-12-31 23:59:59 |
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