Flattening Nested Data in Spark with the Explode Function When working with big data, it’s common to encounter nested data structures like arrays or maps. These structures are useful for storing complex relationships but can be challenging to work with during analysis or when storing data in a tabular format. Enter Spark’s explode function—a simple…
Streamlining ETL Pipelines: Dynamically Calculating Yesterday’s Date As a data engineer, one of the most common tasks is building ETL pipelines that process data from the previous day. While it may seem simple to manually enter a date before running the pipeline, this approach is both inefficient and error-prone. A small mistake, such as entering…
Databricks continues to innovate and enhance the data engineering experience, and their recent introduction of SQL parameters is no exception. This simple yet powerful feature can revolutionize the way you write and interact with SQL code. Here’s everything you need to know about SQL parameters and how they can streamline your workflows. What Are SQL…
