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dbt-athena

Installation

  • pip install dbt-athena-community
  • Or pip install git+https://github.com/dbt-athena/dbt-athena.git

Prerequisites

To start, you will need an S3 bucket, for instance my-staging-bucket and an Athena database:

CREATE DATABASE IF NOT EXISTS analytics_dev
COMMENT 'Analytics models generated by dbt (development)'
LOCATION 's3://my-staging-bucket/'
WITH DBPROPERTIES ('creator'='Foo Bar', 'email'='[email protected]');

Notes:

  • Take note of your AWS region code (e.g. us-west-2 or eu-west-2, etc.).
  • You can also use AWS Glue to create and manage Athena databases.

Credentials

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. Checkout DBT profile configuration below for details.

Configuring your profile

A dbt profile can be configured to run against AWS Athena using the following configuration:

Option Description Required? Example
s3_staging_dir S3 location to store Athena query results and metadata Required s3://bucket/dbt/
region_name AWS region of your Athena instance Required eu-west-1
schema Specify the schema (Athena database) to build models into (lowercase only) Required dbt
database Specify the database (Data catalog) to build models into (lowercase only) Required awsdatacatalog
poll_interval Interval in seconds to use for polling the status of query results in Athena Optional 5
aws_profile_name Profile to use from your AWS shared credentials file. Optional my-profile
work_group Identifier of Athena workgroup Optional my-custom-workgroup
num_retries Number of times to retry a failing query Optional 3

Example profiles.yml entry:

athena:
  target: dev
  outputs:
    dev:
      type: athena
      s3_staging_dir: s3://athena-query-results/dbt/
      region_name: eu-west-1
      schema: dbt
      database: awsdatacatalog
      aws_profile_name: my-profile
      work_group: my-workgroup

Additional information

  • threads is supported
  • database and catalog can be used interchangeably

Usage notes

Models

Table Configuration

  • external_location (default=none)
    • The location where Athena saves your table in Amazon S3
    • If none then it will default to {s3_staging_dir}/tables
    • If you are using a static value, when your table/partition is recreated underlying data will be cleaned up and overwritten by new data
  • partitioned_by (default=none)
    • An array list of columns by which the table will be partitioned
    • Limited to creation of 100 partitions (currently)
  • bucketed_by (default=none)
    • An array list of columns to bucket data
  • bucket_count (default=none)
    • The number of buckets for bucketing your data
  • format (default='parquet')
    • The data format for the table
    • Supports ORC, PARQUET, AVRO, JSON, or TEXTFILE
  • write_compression (default=none)
    • The compression type to use for any storage format that allows compression to be specified. To see which options are available, check out CREATE TABLE AS
  • field_delimiter (default=none)
    • Custom field delimiter, for when format is set to TEXTFILE

More information: CREATE TABLE AS

Supported functionality

Support for incremental models:

  • Support two incremental update strategies with partitioned tables: insert_overwrite and append
  • Does not support the use of unique_key

Due to the nature of AWS Athena, not all core dbt functionality is supported. The following features of dbt are not implemented on Athena:

  • Snapshots

Known issues

  • Quoting is not currently supported

    • If you need to quote your sources, escape the quote characters in your source definitions:
    version: 2
    
    sources:
      - name: my_source
        tables:
          - name: first_table
            identifier: "first table"       # Not like that
          - name: second_table
            identifier: "\"second table\""  # Like this
  • Tables, schemas and database should only be lowercase

  • Only supports Athena engine 2

Contributing

This connector works with Python from 3.7 to 3.10.

Getting started

In order to start developing on this adapter clone the repo and run this make command (see Makefile) :

make setup

It will :

  1. Install all dependencies.
  2. Install pre-commit hooks.

Next, configure the environment variables in dev.env to match your Athena development environment.

Running tests

You can run the tests using make:

make run_tests

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