Spark-Connect

Summary This blog post is a detailed story about how I ported a popular data quality framework, AWS Deequ, to Spark-Connect. Deequ is a very cool, reliable and scalable framework that allows to compute a lot of metrics, checks and anomaly detection suites on the data using Apache Spark cluster. But the Deequ core is a Scala library that uses a lot of low-level Apache Spark APIs for better performance, so it cannot be run directly on any of Spark-Connect environment....

This blog post presents a very detailed step-by-step guide on how to create a SparkConnect protocol extension in Java and call it from PySpark. It will also cover a topic about how to define all the necessary proto3 messages for it. At the end of this guide you will have a way to interact with Spark JVM from PySpark almost like you can with py4j in a non-connect version.