A 3-day bug hunt on a 3-person team costs up to β¬7,200 in lost engineering time. This workshop teaches you to prevent that β unit tests, data tests, and integration tests for PySpark and Databricks Lakeflow, including Spark Declarative Pipelines.
Without any explicit definition, Spark SQL won't partition any data, i.e. all rows will be processed by one executor. It's not optimal since Spark was designed to parallel and distributed processing.
The most popular partitioning strategy divides the dataset by the hash computed from one or more values of the record. However other partitioning strategies exist as well and one of them is range partitioning implemented in Apache Spark SQL with repartitionByRange method, described in this post.
