Sink data from RisingWave to ClickHouse

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.

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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.

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Syntax

CREATE SINK [ IF NOT EXISTS ] sink_name
[FROM sink_from | AS select_query]
WITH (
   connector='clickhouse',
   connector_parameter = 'value', ...
);

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Parameters

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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 into INSERT with SIGN = -1.
• VersionedCollapsingMergeTree: DELETE operations are transformed into INSERT with SIGN = -1.
• ReplacingMergeTree: DELETE operations are transformed into INSERT with SIGN = 1.

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Supported table engines

RisingWave supports the following table engines of ClickHouse:

• MergeTree
• ReplacingMergeTree
• SummingMergeTree
• AggregatingMergeTree
• CollapsingMergeTree
• VersionedCollapsingMergeTree
• GraphiteMergeTree
• ReplicatedMergeTree
• ReplicatedReplacingMergeTree
• ReplicatedSummingMergeTree
• ReplicatedAggregatingMergeTree
• ReplicatedCollapsingMergeTree
• ReplicatedVersionedCollapsingMergeTree
• ReplicatedGraphiteMergeTree
• SharedMergeTree
• SharedReplacingMergeTree
• SharedSummingMergeTree
• SharedAggregatingMergeTree
• SharedCollapsingMergeTree
• SharedVersionedCollapsingMergeTree
• SharedGraphiteMergeTree

Among these, engines prefixed with “Shared” are exclusively available in ClickHouse Cloud and are premium features in RisingWave. They provide enhanced capabilities for distributed deployments, automatic replication, and improved resource management. For more information about it, see MergeTree Engine Family .

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Examples

This section includes several examples that you can use if you want to quickly experiment with sinking data to ClickHouse.

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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 TABLE demo_test(
    seq_id Int32,
    user_id Int32,
    user_name String
) ENGINE = ReplacingMergeTree
PRIMARY KEY (seq_id);

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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.

CREATE SOURCE s1_source (
    seq_id integer,
    user_id integer,
    user_name varchar)
WITH (
    connector ='datagen',
    fields.seq_id.kind ='sequence',
    fields.seq_id.start ='1',
    fields.seq_id.end ='10000000',
    fields.user_id.kind ='random',
    fields.user_id.min ='1',
    fields.user_id.max ='10000000',
    fields.user_name.kind ='random',
    fields.user_name.length ='10',
    datagen.rows.per.second ='20000'
 ) FORMAT PLAIN ENCODE JSON;

Another option is to create an upsert table, which supports in-place updates. For more details on creating a table, see CREATE TABLE .

CREATE TABLE s1_table (
    seq_id integer,
    user_id integer,
    user_name varchar)
WITH (
    connector ='datagen',
    fields.seq_id.kind ='sequence',
    fields.seq_id.start ='1',
    fields.seq_id.end ='10000000',
    fields.user_id.kind ='random',
    fields.user_id.min ='1',
    fields.user_id.max ='10000000',
    fields.user_name.kind ='random',
    fields.user_name.length ='10',
    datagen.rows.per.second ='20000'
 ) FORMAT PLAIN ENCODE JSON;

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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.

CREATE SINK s1_sink FROM t1_table
WITH (
    connector = 'clickhouse',
    type = 'append-only',
    clickhouse.url = '${CLICKHOUSE_URL}',
    clickhouse.user = '${CLICKHOUSE_USER}',
    clickhouse.password = '${CLICKHOUSE_PASSWORD}',
    clickhouse.database = 'default',
    clickhouse.table='demo_test'
);

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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.

CREATE SINKs1_sink FROM t1_table
WITH (
    connector = 'clickhouse',
    type = 'append-only',
    clickhouse.url = '${CLICKHOUSE_URL}',
    clickhouse.user = '${CLICKHOUSE_USER}',
    clickhouse.password = '${CLICKHOUSE_PASSWORD}',
    clickhouse.database = 'default',
    clickhouse.table='demo_test'
);

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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.

CREATE SINK s1_sink FROM s1_table
WITH (
    connector = 'clickhouse',
    type = 'upsert',
    primary_key = 'seq_id',
    clickhouse.url = '${CLICKHOUSE_URL}',
    clickhouse.user = '${CLICKHOUSE_USER}',
    clickhouse.password = '${CLICKHOUSE_PASSWORD}',
    clickhouse.database = 'default',
    clickhouse.table='demo_test'
);

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Data type mapping

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.