Athena setup

• Maintained by: dbt Labs
• Authors: dbt Labs
• GitHub repo: dbt-labs/dbt-athena
• PyPI package: dbt-athena-community
• Slack channel: #db-athena
• Supported dbt Core version: v1.3.0 and newer
• dbt Cloud support: Supported
• Minimum data platform version: engine version 2 and 3

Installing dbt-athena-community

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-athena-community

For Athena-specific configuration, please refer to Athena configs.

Connecting to Athena with dbt-athena

This plugin does not accept any credentials directly. Instead, credentials are determined automatically based on AWS CLI/boto3 conventions and stored login info. You can configure the AWS profile name to use via aws_profile_name. Check out the dbt profile configuration below for details.

~/.dbt/profiles.yml

default:
  outputs:
    dev:
      type: athena
      s3_staging_dir: [s3_staging_dir]
      s3_data_dir: [s3_data_dir]
      s3_data_naming: [table_unique] # the type of naming convention used when writing to S3
      region_name: [region_name]
      database: [database name]
      schema: [dev_schema]
      aws_profile_name: [optional profile to use from your AWS shared credentials file.]
      threads: [1 or more]
      num_retries: [0 or more] # number of retries performed by the adapter. Defaults to 5
  target: dev