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spark-cli

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Manages Fabric Spark work, including notebook cell code with %%configure, %%sql, PySpark and notebookutils, named notebook runs, Livy sessions, triage of failed or OOM notebook and pipeline Spark runs, and the Materialized Lake View (MLV) lifecycle. Load it before writing MLV SQL, since CREATE MATERIALIZED LAKE VIEW and its CONSTRAINT clause are Fabric-only. KQL materialized views belong to eventhouse-cli.

When to use

• notebook cell code
• named notebook runs
• Livy sessions
• Spark failure triage
• Materialized Lake View lifecycle
• MLV SQL writing
• MLV scheduling and refreshing
• MLV monitoring and diagnosis

When not to use

• KQL materialized views
• Eventhouse requests
• plain read-only T-SQL against a Warehouse
• plain read-only T-SQL against a Lakehouse SQL endpoint

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