This document covers the incremental content beyond what is contained in the repository's CONTRIBUTING.md. You are strongly encouraged to start there first if you are reading this for the first time.
dbt-spark uses dagger to orchestrate its test suite.
This launches a virtual container or containers to test against.
dagger will be installed as part of running hatch run setup.
Note
dbt-spark has not yet been configured to install dbt-adpaters and dbt-tests-adapter as local, editable packages.
dbt-spark can test against multiple implementations, or "profile"s:
`--profile`: required, this is the kind of spark connection to test against
_options_:
- "apache_spark"
- "spark_session"
- "spark_http_odbc"
- "databricks_sql_endpoint"
- "databricks_cluster"
- "databricks_http_cluster"
To test against Apache Spark:
# run all tests for the apache_spark profile
$ hatch run integration-tests --profile "apache_spark"
# run tests for the apache_spark profile for a specific module
$ hatch --profile "apache_spark" --test-path tests/functional/adapter/test_basic.py
# run a specific test for the apache_spark profile
$ hatch --profile "apache_spark" --test-path tests/functional/adapter/test_basic.py::TestSimpleMaterializationsSpark::test_base