Issues running Spark Notebook

Hi um4ndr ,

Thanks for reaching out to the Microsoft fabric community forum.

Livy sessions and their statements are not persistent forever.
If your notebook is idle or takes too long to execute a cell, the statement might expire or be cleaned up before it's accessed again.
Network Latency or Disruption:
A brief network glitch between your environment and the Livy server might cause this.
Race Condition or Resource Unavailability:If many users/notebooks are sharing a Spark pool or compute cluster, Livy might not process requests reliably under load.
If your notebook is connecting to a Spark pool that was stopped or in cold start, the first requests might fail before the backend is ready.
workaround:
As you already noticed, waiting and retrying later worked  this supports the idea of a temporary availability or latency issue.
Suggested fixes
Increase Livy timeout settings (if configurable):
Look for options like livy.server.session.timeout and livy.server.statement.timeout (in Azure or Fabric, these might be set via notebook/session config).
Ensure retries are not too fast:
If your retry mechanism is immediate, try adding a delay (e.g., exponential backoff) between retries.
Use smaller, quicker Spark jobs for first cell:
Add a small warm-up job (e.g., spark.range(10).count()) at the beginning to keep the session active and ensure cluster readiness.
Cluster autoscaling or pool warm-up:
If using Azure Synapse / Fabric, make sure your Spark pool is kept warm if needed, or pre-allocate resources to reduce cold start delays.
Check backend service health (Livy logs / Fabric logs):
If this is a recurring issue, consider looking into cluster logs or raising a ticket with Microsoft if you're using Fabric.
Run a lightweight job to keep session active
spark.range(1, 10).count()

Handle Livy Errors on Apache Spark in Synapse - Azure Synapse Analytics | Microsoft Learn

Spark Livy Session Timeout Issue - Microsoft Q&A

Submit Spark session jobs using the Livy API - Microsoft Fabric | Microsoft Learn

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Best regards,
LakshmiNarayana.