Summary
In this chapter, we learned about several optimization techniques concerning Databricks Delta Lake. We started with file compaction and clustering techniques and ended with techniques for efficient data skipping. These optimization techniques play a crucial role in making querying and data engineering workloads in Databricks quicker and more efficient.
In the next chapter, we will learn about another set of Spark optimization techniques related to Spark core. We will develop a theoretical understanding of these optimizations and write code to understand their practical usage in different scenarios.
