Have you ever faced slow or inefficient Spark jobs in Databricks? Data spilling is one of the main problems behind delays in big data processing, and in this session, we’ll explore what data spilling is, why it happens, and how it impacts the performance of your jobs. No matter if you’re a beginner or an experienced Spark user, this session will get you on track to follow up on the content provided at the same time as valuable insights are shared.

You will understand the concept of data spilling and how to identify it, exploring optimization techniques, including memory tuning and partition configuration, and more.