dbt-duckdb 1.2.3

The duckdb adapter plugin for dbt (data build tool)

dbt-duckdb

Installation

This project is hosted on PyPI, so you should be able to install it and the necessary dependencies via:

pip3 install dbt-duckdb

The latest supported version targets dbt-core 1.2.x and duckdb version 0.5.0 (but should also work with 0.4.0 and 0.3.2!)

Configuring your profile

DuckDB is an embedded database, similar to SQLite, but designed for OLAP-style analytics instead of OLTP. The only configuration parameter that is required in your profile (in addition to type: duckdb) is the path field, which should refer to a path on your local filesystem where you would like the DuckDB database file (and it's associated write-ahead log) to be written. You can also specify the schema parameter if you would like to use a schema besides the default (which is called main).

Prior to version 1.2.1, dbt-duckdb was limited to a single dbt execution thread; in version 1.2.1 this constraint was lifted and now dbt-duckdb can run with as many threads as you can throw at it.

There is also a database field defined in the DuckDBCredentials class for consistency with the parent Credentials class, but it defaults to main and setting it to be something else will likely cause strange things to happen that I cannot fully predict, so, ya know, don't do that.

As of version 1.2.3, you can load any supported DuckDB extensions by listing them in the extensions field in your profile. You can also set any additional DuckDB configuration options via the settings field, including options that are supported in any loaded extensions. For example, to be able to connect to S3 and read/write Parquet files using an AWS access key and secret, your profile would look something like this:

default:
  outputs:
    dev:
      path: /tmp/dbt_test.db
      schema: analytics
      type: duckdb
      threads: 4
      extensions:
        - httpfs
        - parquet
      settings:
        s3_region: my-aws-region
        s3_access_key_id: "{{ env_var('S3_ACCESS_KEY_ID') }}"
        s3_secret_access_key: "{{ env_var('S3_SECRET_ACCESS_KEY') }}"
  target: dev

Developer Workflow

If you need to add features to dbt-duckdb itself, use this workflow to get started:

$ git clone https://github.com/jwills/dbt-duckdb.git
$ cd dbt-duckdb
$ "hack on stuff for awhile"
$ pip3 install .
$ pytest tests/