However, you have multiple options to access and work with query history information:

1. Databricks UI:

• The most straightforward way is to use the built-in Query History section in the sidebar of the Databricks SQL workspace. This provides an interface to view query details, filter by various criteria, and even access execution plans for performance analysis.

2. Query History API:

• Databricks offers a REST API (Query History API) that allows you to fetch query history data programmatically. You can build custom dashboards, integrate with external tools, or perform more advanced analysis.
• Refer to the API documentation for details: https://docs.databricks.com/api/workspace/queryhistory.

3. Steampipe (for Databricks SQL):

• If you are using Databricks SQL, you can leverage the databricks_sql_query_history table provided by the Steampipe plugin. This gives you a SQL-like interface to query the history data.
• You can find information about the table and its usage here: https://hub.steampipe.io/plugins/turbot/databricks/tables/databricks_sql_query_history.

Important Considerations:

• Retention Period: The query history in Databricks is typically retained for a limited period (e.g., 30 days). If you need to store the data for longer durations, make sure to factor this in.
• Serverless Compute: If you use serverless compute in Databricks, the query history will also include queries run on that infrastructure.