Prerequisites
- Ensure you already have an Iceberg table that you can sink data to. For additional guidance on creating a table and setting up Iceberg, refer to this quickstart guide on creating an Iceberg table.
- Ensure you have an upstream materialized view or source that you can sink data from.
Syntax
Parameters
Basic parameters
Use Amazon S3 Tables with the Iceberg sink
You can configure the RisingWave Iceberg sink connector to use Amazon S3 Tables as its catalog. This setup allows RisingWave to sink data into Iceberg tables managed by the AWS native S3 Tables catalog service. To achieve this, specify therest catalog type within your CREATE SINK statement and include the necessary parameters for SigV4 authentication against the S3 Tables REST API.
Required REST Catalog Parameters for S3 Tables:
Example
CREATE SINK Statement:
source_table into the specified Iceberg table (<your-table-name>) within the <your-database-name> database, using Amazon S3 Tables to manage the table’s metadata.
Data type mapping
RisingWave converts RisingWave data types from/to Iceberg according to the following data type mapping table:Catalog
Iceberg supports these types of catalogs:Storage catalog
The Storage catalog stores all metadata in the underlying file system, such as Hadoop or S3. Currently, we only support S3 as the underlying file system.Example
REST catalog
RisingWave supports the REST catalog, which acts as a proxy to other catalogs like Hive, JDBC, and Nessie catalog. This is the recommended approach to use RisingWave with Iceberg tables.Example
Hive catalog
RisingWave supports the Hive catalog. You need to setcatalog.type to hive to use it.
Example
JDBC catalog
RisingWave supports the JDBC catalog.Example
Glue catalog
RisingWave supports the Glue catalog. You should use AWS S3 if you use the Glue catalog. Below are example codes for using this catalog:Example
Iceberg table format
Currently, RisingWave only supports Iceberg tables in format v2.Examples
This section includes several examples that you can use if you want to quickly experiment with sinking data to Iceberg.Create an Iceberg table (if you do not already have one)
Setcreate_table_if_not_exists to true to automatically create an Iceberg table.
Alternatively, use Spark to create a table. For example, the following spark-sql command creates an Iceberg table named table under the database dev in AWS S3. The table is in an S3 bucket named my-iceberg-bucket in region ap-southeast-1 and under the path path/to/warehouse. The table has the property format-version=2, so it supports the upsert option. There should be a folder named s3://my-iceberg-bucket/path/to/warehouse/dev/table/metadata.
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 .Append-only sink from append-only source
If you have an append-only source and want to create an append-only sink, settype = 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, settype = append-only and force_append_only = true. This will ignore delete messages in the upstream, and to turn upstream update messages into insert messages.
Upsert sink from upsert source
In RisingWave, you can directly sink data as upserts into Iceberg tables.Iceberg sink on GCS
Added in version 2.3.
storage or rest. For more information about gcs.credential, see parameters.