Spark Performance Tuning
Master the art of Spark Performance Tuning and Data Engineering in this comprehensive Apache Spark tutorial! Data skew is a common issue in big data processing, leading to performance bottlenecks by overloading some nodes while underutilizing others. This video dives deep into a practical example of data skew and demonstrates how to optimize Spark performance by using a technique called 'Salting'. Salting involves adding some randomness to the values before computing the hash for partitioning, thus distributing the data more evenly across partitions and reducing skew. With clear step-by-step explanations, you'll learn how to apply salting in practice, understand the concept behind it, and ultimately improve your data engineering skills.
📄 Complete Code on GitHub: github.com/afaqueahmad7117/sp...
🎥 Full Spark Performance Tuning Playlist: • Apache Spark Performan...
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Chapters:
00:00 Salting Concept
07:06 Applying Salting In Joins
12:53 Code Examples For Salting In Joins
16:56 Applying Salting In Aggregations
27:57 Code Examples For Salting In Aggregations
#dataengineering #apachespark #outofmemoryerror #bigdata #salting #dataskew #sparkperformancetuning #sparkoptimization
Негізгі бет How Salting Can Reduce Data Skew By 99%
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