Pinned to a notebook, it determines where relative Files/ and Tables/ paths and Spark SQL table names without a qualifier point. If you switch to another lakehouse or rename it, the session must be restarted.
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In the Ultra Transcenders books
Each book explains Default lakehouse in context, with comparison tables and the common traps.
Terms in this definition
- Notebook
Combines runnable code cells, in Python, SQL, Scala or R, with their results in one interactive Azure Databricks document; it runs on attached compute, and a job can run it as a task.
- WHERE
Limits a SELECT, UPDATE or DELETE to just the rows meeting a condition. Omit it, and the statement hits every row.
- Serverless
Compute tier for single Azure SQL databases that scales automatically, pauses when idle and charges by the second. It is offered in General Purpose and Hyperscale, not Business Critical, and reserved capacity does not apply.
- Event
Table in Log Analytics where entries from Windows event logs are kept.
- SWITCH
Checks one expression against several candidate values, returning whichever result pairs with the match (or a fallback otherwise). Writing SWITCH ( TRUE (), ... ) avoids nested IF chains: whichever condition is first true wins.
- Lakehouse
Fabric storage item in OneLake that holds structured and unstructured content side by side: managed Delta tables go under Tables, other files under Files. Spark is used for processing, and a read-only SQL analytics endpoint allows T-SQL queries.
- RENAME
Gives an existing object in a database, such as a table, a different name; it is a DDL command.
Related terms
- Deployment rules
Settings you configure for each stage of a deployment pipeline, covering data sources, parameters and the default lakehouse, so that content arriving in a stage connects to that stage's own data. Changes apply from the following deployment onwards.
- High concurrency mode
A Fabric Spark mode where notebooks, or notebook activities in pipelines, run by one user with matching default lakehouse, Spark configuration and libraries reuse a single Spark session. They start more quickly and only the session that started it is charged.
- Spark job definition
An item in Fabric that runs Spark work, batch or streaming, from one main file (.py, .jar, .scala, .r and so on) together with optional extra files and arguments passed on the command line. You can trigger it by hand or schedule it, and a default lakehouse must be attached.