• Azure Databricks documentation | Microsoft Docs
• Ten Simple Databricks Notebook Tips & Tricks for Data Scientists – The Databricks Blog
• Secret scopes – Azure Databricks | Microsoft Docs

Databricks on AWS

• Databricks documentation | Databricks on AWS
• Runs CLI | Databricks on AWS
• Databricks File System (DBFS) | Databricks on AWS
• Databricks for SQL developers | Databricks on AWS
• Databricks SQL | Databricks on AWS
• Databricks ODBC and JDBC drivers | Databricks on AWS
• Authentication using Databricks personal access tokens | Databricks on AWS
• Developer tools and guidance | Databricks on AWS
• DBeaver integration with Databricks | Databricks on AWS
• Databricks Utilities | Databricks on AWS
• Secrets | Databricks on AWS
• Databricks SQL Connector for Python | Databricks on AWS
• Databricks for Python developers | Databricks on AWS

DROP DATABASE

• DROP DATABASE | Databricks on AWS

While usage of SCHEMA and DATABASE is interchangeable, SCHEMA is preferred.

Related articles

• CREATE SCHEMA
• DESCRIBE SCHEMA
• DROP SCHEMA
• SHOW SCHEMAS

DROP VIEW (Databricks SQL)

• DROP VIEW (Databricks SQL) | Databricks on AWS

DROP VIEW [ IF EXISTS ] view_name

Related articles

• CREATE VIEW
• ALTER VIEW
• SHOW VIEWS
• CREATE SCHEMA
• DROP SCHEMA

Other

ดูเวอร์ชันของ Databricks Runtime

• Checking the version of Databricks Runtime in Azure – Stack Overflow

%scala
dbutils.notebook.getContext.tags("sparkVersion")
// res1: String = 10.4.x-scala2.12

%python
spark.conf.get("spark.databricks.clusterUsageTags.sparkVersion")
# '10.4.x-scala2.12'