How can I view spark job status while using Glue Interactive Sessions in JupyterLab

When using AWS Glue Interactive Sessions in JupyterLab, you have a couple of options to monitor your Spark job status:

1. Enable the Apache Spark web UI for your Glue interactive session by using the %%configure cell magic before starting your session:

%%configure { "--enable-spark-ui": "true", "--spark-event-logs-path": "s3://your-bucket-path" }

This configuration will store Spark event logs to your specified S3 location, which you can then view using a Spark history server. Note that AWS Glue interactive sessions do not currently support Spark UI directly in the console, so configuring a Spark history server is recommended.

2. For basic monitoring, Jupyter notebooks provide real-time job status and execution progress information in the notebook interface.

3. For more detailed analysis, you can use the Spark UI to examine specific stages, tasks, and execution plans. The Spark UI is particularly useful for troubleshooting performance issues and optimizing queries, as it allows you to track estimated stages, running tasks, and task timing details.

By enabling the Spark UI, you'll get a comprehensive view of your job's resource utilization and progress, including fine-grained task-level status, I/O details, and shuffle operations.
Sources
Enabling the Apache Spark web UI for AWS Glue jobs - AWS Glue
Develop and monitor a Spark application using existing data in Amazon S3 with Amazon SageMaker Unified Studio | AWS Big Data Blog