Apache Spark is a lightning-fast unified analytics engine for big data and machine learning. Since its release, Apache Spark has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at a massive scale. It has quickly become the largest open-source community in big data. So, mastering Apache Spark opens a wide range of professional opportunities.
This course covers some advanced topics and concepts such as Spark 3 architecture and memory management, AQE, DPP, broadcast, accumulators, and multithreading in Spark 3 along with common job interview questions and answers. The objective of this course is to prepare you for advanced certification topics.
By the end of this course, you will have learned some advanced topics and concepts that are asked for in the Databricks Spark Certification or Spark job interviews. This will not only help you develop advanced skills in Apache Spark but also crack your job interviews.
Learn AQE, DPP, Broadcast in Spark 3
Explore Spark 3 architecture
Understand memory management in Spark 3
Learn Spark AQE Dynamic Join Optimization
Explore accumulators and multithreading in Spark
Discover Spark Dynamic Partition Pruning
Before proceeding with the course, you will need basic knowledge of Spark programming in Python – PySpark.