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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: Not 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
0