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Gain a deeper understanding of Spark by learning about its APIs, architecture, and common use cases. This statistics and data analysis course will cover material relevant to both data engineers and data scientists. You’ll learn how Spark efficiently transfers data across the network via its shuffle, details of memory management, optimizations to reduce compute costs, and more. Learners will see several use cases for Spark and will work to solve a variety of real-world problems using public datasets. After taking this course, you should have a thorough understanding of how Spark works and how you can best utilize its APIs to write efficient, scalable code. You’ll also learn about a wide variety of Spark’s APIs, including the APIs in Spark Streaming. Categories:
Starts :
2016-09-21 |
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AlternativesIf you know any alternatives, please let us know. PrerequisitesIf you can suggest any prerequisite, please let us know. Certification Exams-- there are no exams to get certification after this course --If your company does certification for those who completed this course then register your company as certification vendor and add your exams to the Exams Directory. | ||
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