Github dbt Package (Docs)

What does this dbt package do?

Produces modeled tables that leverage Github data from Fivetran's connector in the format described by this ERD and builds off of the output from our github source package.
Provides insight into GitHub issues and pull requests by enhancing these core objects with commonly used metrics.
Produces metrics tables, which increase understanding of your team's velocity over time. Metrics are available on a daily, weekly, monthly, and quarterly level.
Generates a comprehensive data dictionary of your source and modeled github data through the dbt docs site.

The following table provides a detailed list of all tables materialized within this package by default.

TIP: See more details about these tables in the package's dbt docs site.

Table	Description
github__issues	Each record represents a GitHub issue, enriched with data about its assignees, milestones, and time comparisons.
github__pull_requests	Each record represents a GitHub pull request, enriched with data about its repository, reviewers, and durations between review requests, merges and reviews.
github__daily_metrics	Each record represents a single day and repository, enriched with metrics about PRs and issues that were created and closed during that period.
github__weekly_metrics	Each record represents a single week and repository, enriched with metrics about PRs and issues that were created and closed during that period.
github__monthly_metrics	Each record represents a single month and repository, enriched with metrics about PRs and issues that were created and closed during that period.
github__quarterly_metrics	Each record represents a single quarter and repository, enriched with metrics about PRs and issues that were created and closed during that period.

How do I use the dbt package?

Step 1: Prerequisites

To use this dbt package, you must have the following:

At least one Fivetran Github connector syncing data into your destination.
A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

Databricks Dispatch Configuration

If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your dbt_project.yml. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils then the dbt-labs/dbt_utils packages respectively.

dispatch:
  - macro_namespace: dbt_utils
    search_order: ['spark_utils', 'dbt_utils']

Step 2: Install the package

Include the following github package version in your packages.yml file.

TIP: Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.

packages:
  - package: fivetran/github
    version: [">=0.8.0", "<0.9.0"] # we recommend using ranges to capture non-breaking changes automatically

Do NOT include the github_source package in this file. The transformation package itself has a dependency on it and will install the source package as well.

Step 3: Define database and schema variables

By default, this package runs using your destination and the github schema. If this is not where your Github data is (for example, if your github schema is named github_fivetran), add the following configuration to your root dbt_project.yml file:

vars:
  github_source:
    github_database: your_database_name
    github_schema: your_schema_name

Step 4: Disable models for non-existent sources

Your Github connector might not sync every table that this package expects. If your syncs exclude certain tables, it is because you either don't use that functionality in Github or have actively excluded some tables from your syncs.

If you do not have the REPO_TEAM table synced, add the following variable to your dbt_project.yml file:

vars:
    github__using_repo_team: false # by default this is assumed to be true

Note: This package only integrates the above variable. If you'd like to disable other models, please create an issue specifying which ones.

(Optional) Step 5: Additional configurations

Expand/collapse configurations

Change the build schema

By default, this package builds the Github staging models within a schema titled (<target_schema> + _github_source) and your Github modeling models within a schema titled (<target_schema> + _github) in your destination. If this is not where you would like your Github data to be written to, add the following configuration to your root dbt_project.yml file:

models:
    github_source:
      +schema: my_new_schema_name # leave blank for just the target_schema
    github:
      +schema: my_new_schema_name # leave blank for just the target_schema

Change the source table references

If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:

IMPORTANT: See this project's dbt_project.yml variable declarations to see the expected names.

vars:
    github_<default_source_table_name>_identifier: your_table_name

(Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™

Expand for more details

Fivetran offers the ability for you to orchestrate your dbt project through Fivetran Transformations for dbt Core™. Learn how to set up your project for orchestration through Fivetran in our Transformations for dbt Core setup guides.

Does this package have dependencies?

This dbt package is dependent on the following dbt packages. These dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.

IMPORTANT: If you have any of these dependent packages in your own packages.yml file, we highly recommend that you remove them from your root packages.yml to avoid package version conflicts.

packages:
    - package: fivetran/fivetran_utils
      version: [">=0.4.0", "<0.5.0"]

    - package: dbt-labs/dbt_utils
      version: [">=1.0.0", "<2.0.0"]

    - package: fivetran/github_source
      version: [">=0.8.0", "<0.9.0"]
    
    - package: dbt-labs/spark_utils
      version: [">=0.3.0", "<0.4.0"]

How is this package maintained and can I contribute?

Package Maintenance

The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.

Contributions

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.

We highly encourage and welcome contributions to this package. Check out this dbt Discourse article on the best workflow for contributing to a package.

Are there any resources available?

If you have questions or want to reach out for help, see the GitHub Issue section to find the right avenue of support for you.
If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our Feedback Form.