A simple way to troubleshoot a slow Spark job using Spark UI is:

1. Check task duration

   • A few very slow tasks → Likely data skew.

   • Most tasks are slow → Likely cluster resource or execution issue.

2. Check Spark UI metrics

   • Large differences in shuffle read/task size → Data skew.

   • High spill, high GC time, or OOM errors → Memory pressure.

3. Choose the right fix

   • Data skew → Repartition, salting, or enable AQE.

   • Small lookup table → Use a broadcast join.

   • Memory issues → Increase executor memory or optimize partitions.

4. Validate the result

   • Compare Spark UI before and after the change.

   • Confirm lower task time, less spill, lower GC, and balanced task sizes.

Rule of thumb: A few slow tasks usually mean data skew. Slow performance across all tasks usually means memory or resource limitations.