Tuning Queries Using Caching
When you are dealing with massive amounts of data, getting quick results is essential for smooth operations. Azure offers a range of tools to help speed up queries, and one powerful method is caching. Think of caching as keeping frequently used information close at hand for faster access. In this section, you will dive into how you can use caching in Synapse Spark and Synapse SQL to make your queries run faster and your data analysis more efficient. You will cover why caching matters, how to set it up in Synapse SQL or Synapse Spark, and how it works alongside other optimization techniques, such as indexing. With caching, you can dramatically improve query speeds, reduce delays, and make your data analysis experience much smoother.
Caching is an optimization technique used in both Apache Spark (which includes Synapse Spark) and Databricks Spark to improve the performance of iterative or interactive workloads by storing intermediate data in memory, which...
