The Apache Spark Application Performance Tuning course teaches you how to optimize Apache Spark applications for better performance, scalability, and efficiency. This course covers various aspects of tuning Spark applications, including memory management, resource allocation, and data serialization.
No, this course is designed for intermediate and advanced level learners with prior knowledge of Apache Spark and Scala/Python programming.
You will need a computer with a minimum of 8GB RAM and Linux/MacOS operating system. You will also need to install Apache Spark and Scala/Python on
Spark application performance tuning can significantly improve the efficiency and scalability of Spark applications, enabling them to process larger datasets faster and with lower resource consumption. This can result in lower costs and faster time-to-insight for data-driven applications.
Participants should have prior experience with Apache Spark and basic knowledge of distributed systems, data processing, and programming in either Scala or Python.
This course covers a range of topics related to Spark application performance tuning, including memory management, data serialization, caching, shuffle optimization, parallelism, and troubleshooting performance issues.
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