• Databricks
  • Databricks
  • View Azure Databricks documentation Azure docs
  • View Azure Databricks documentation Azure docs
  • Support
  • Feedback
  • Try Databricks
  • Help Center
  • Documentation
  • Knowledge Base
  • Forums
  • Training
Databricks Knowledge Base
  • Databricks administration
  • AWS infrastructure
  • Business intelligence tools
  • Clusters
  • Data management
  • Data sources
  • Databricks File System (DBFS)
  • Developer tools
  • Delta Lake
  • Jobs
  • Job execution
    • Increase the number of tasks per stage
    • Maximum execution context or notebook attachment limit reached
    • Set executor log level
    • Serialized task is too large
  • Libraries
  • Machine learning
  • Metastore
  • Metrics
  • Notebooks
  • Security and permissions
  • Streaming
  • Visualizations
  • Python with Apache Spark
  • R with Apache Spark
  • Scala with Apache Spark
  • SQL with Apache Spark

Updated Mar 31, 2020

Send us feedback

  • Documentation
  • Job execution

Job execution

These articles can help you tune and troubleshoot Spark job execution.

  • Increase the number of tasks per stage
  • Maximum execution context or notebook attachment limit reached
  • Set executor log level
  • Serialized task is too large

© Databricks 2020. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.

Send us feedback | Privacy Policy | Terms of Use