Databricks is a unified analytics platform built on Apache Spark, providing data engineering, data science, and machine learning capabilities in the cloud. Use the Python Connector for SQL warehouses and clusters.
Installation
Required packages: apache-superset[databricks]
pip install apache-superset[databricks]Drivers
Databricks Python Connector (Recommended)Recommended
Hive Connector (Interactive Clusters)
ODBC (SQL Endpoints)
databricks-dbapi (Legacy)
PyPI Package:
databricks-sql-connectordatabricks://token:{access_token}@{host}:{port}?http_path={http_path}&catalog={catalog}&schema={schema}Official Databricks connector. Best for SQL warehouses and clusters.
Supported Features
JOINsSubqueriesDynamic SchemaCatalog SupportDynamic CatalogSSH TunnelingQuery CancellationFile UploadUser ImpersonationCost EstimationSQL Validation
Feature Score: 70/201
Time Grains
Common Time Grains:
SECONDMINUTEHOURDAYWEEKMONTHQUARTERYEAR
Extended Time Grains:
FIVE_SECONDSTHIRTY_SECONDSFIVE_MINUTESTEN_MINUTESFIFTEEN_MINUTESTHIRTY_MINUTESHALF_HOURSIX_HOURSWEEK_STARTING_SUNDAYWEEK_STARTING_MONDAYWEEK_ENDING_SATURDAYWEEK_ENDING_SUNDAYQUARTER_YEAR
Help improve this documentation by editing the engine spec: