Rockset setup
Vendor-supported plugin
Certain core functionality may vary. If you would like to report a bug, request a feature, or contribute, you can check out the linked repository and open an issue.
- Maintained by: Rockset, Inc.
- Authors: Rockset, Inc.
- GitHub repo: rockset/dbt-rockset   
- PyPI package: dbt-rockset
- Slack channel: #dbt-rockset
- Supported dbt Core version: v0.19.2 and newer
- dbt Cloud support: Not Supported
- Minimum data platform version: ?
Installing dbt-rockset
Use pip to install the adapter. Before 1.8, installing the adapter would automatically install dbt-core and any additional dependencies. Beginning in 1.8, installing an adapter does not automatically install dbt-core. This is because adapters and dbt Core versions have been decoupled from each other so we no longer want to overwrite existing dbt-core installations.
Use the following command for installation:
Configuring dbt-rockset
For Rockset-specific configuration, please refer to Rockset configs.
Connecting to Rockset with dbt-rockset
The dbt profile for Rockset is very simple and contains the following fields:
profiles.yml
rockset:
  target: dev
  outputs:
    dev:
      type: rockset
      workspace: [schema]
      api_key: [api_key]
      api_server: [api_server] # (Default is api.rs2.usw2.rockset.com)
Materializations
| Type | Supported? | Details | 
|---|---|---|
| view | YES | Creates a view. | 
| table | YES | Creates a collection. | 
| ephemeral | YES | Executes queries using CTEs. | 
| incremental | YES | Creates a collection if it doesn't exist, and then writes results to it. | 
Caveats
- unique_keyis not supported with incremental, unless it is set to _id, which acts as a natural- unique_keyin Rockset anyway.
- The tablematerialization is slower in Rockset than most due to Rockset's architecture as a low-latency, real-time database. Creating new collections requires provisioning hot storage to index and serve fresh data, which takes about a minute.
- Rockset queries have a two-minute timeout. Any model which runs a query that takes longer to execute than two minutes will fail.
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