The Upsolver adapter plugin for dbt
Project description
dbt-upsolver
Using Upsolver udapter for dbt
What is Upsolver
Upsolver enables you to use familiar SQL syntax to quickly build and deploy data pipelines, powered by a stream processing engine designed for cloud data lakes.
SQLake
SQLake is Upsolvers new UI and SQL console allowing to execute commands and monitor pipelines in the UI. It also includes freee trial and access to variety of examples and tutorials.
What is dbt
dbt is a transformation workflow that helps you get more work done while producing higher quality results.
What is dbt Core
dbt Core is an open-source tool that enables data teams to transform data using analytics engineering best practices. You can install and use dbt Core on the command line.
Getting started
Install dbt-upsolver adapter :
pip install dbt-upsolver
Make sure the adapter is installed:
dbt --version
Expect to see:
Core:
- installed: <version>
- latest: <version>
Plugins:
- upsolver: <version>
Register Upsolver account
To register just navigate to SQL Lake Sign Up form. You'll have access to SQL workbench with examples and tutorials after completing the registration.
Create API token
After login navigate to "Settings" and then to "API Tokens" You will need API token and API Url to access Upsolver programatically. Settings -> API Tokens -> Generate Then click "Generate" new token and save it for future use.
Get your user name, database and schema
For user name navigate to Settings -> User details and copy user name For database and schema navigate to Worksheets and click New. You will find database name and schema(catalog) name under Entities panel
Create new dbt-upsolver project
dbt init <project_name>
Prompt:
Which database would you like to use? [1] upsolver
Enter a number:
api_url (your api_url): https://mt-api-prod.upsolver.com
token (your token): <token>
user (dev username): <username>
database (default database): <database>
schema (default schema): <schema>
threads (1 or more) [1]: <number>
profiles.yml should look like this:
profiles.yml location is something like /Users//.dbt/profiles.yml
project_name:
target: dev
outputs:
dev:
api_url: https://mt-api-prod.upsolver.com
database: ...
schema: ...
threads: 1
token: ...
type: upsolver
user: ...
Check connection
dbt debug
Run all models
dbt run
Run the specific model
dbt run --select <model name>
Supported dbt commands:
- dbt init
- dbt debug
- dbt run
- dbt compile
!not supported Upsolver feature Delete data from target table
Further reading
Projects samples examples Upsolver sqlake documentation Upsolver sqlake documentation
Project details
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