Learning about dynamic partition pruning
Dynamic partition pruning is a data-skipping technique that can drastically speed up query execution time. Delta lake collects metadata on the partition files it manages so that data can be skipped without the need to access it. This technique is very useful for star schema types of queries as it can dynamically skip partitions and their respective files. Using this technique, we can prune the partitions of a fact table during the join to a dimension table. This is made possible when the filter that's applied to a dimension table to prune its partitions is dynamically applied to the fact table. We will now learn how this technique works by looking at an example. Before we get started, do not forget to spin up the packt-cluster cluster!
In this example, we will demonstrate a star schema model by joining a fact table and a dimension table. A star schema is one of the simplest ways to build a data warehouse. It consists of one or more fact...
