Resource Management in Spark

In course

Ipsum et exercitation dolore magna esse laborum deserunt est deserunt aliqua aute ea. Excepteur est Lorem amet veniam deserunt ea eu fugiat mollit labore reprehenderit adipisicing fugiat adipisicing. Veniam id et exercitation enim occaecat excepteur sunt consequat elit dolor.

Description

This lecture covers resource management in Spark, focusing on architectural choices, fault tolerance, data safety, job recovery, and the limitations of vanilla Spark. It also delves into Spark SQL, data frames, DataFrame operators, user-defined functions, and optimization principles.

Instructor

proident ut

Sunt ea fugiat consequat nisi culpa pariatur Lorem quis excepteur proident consectetur nulla aliqua. Eiusmod qui esse irure aliquip non exercitation officia excepteur sint incididunt dolor velit. Fugiat magna aute elit et deserunt irure exercitation deserunt adipisicing.

Official source

https://mediaspace.epfl.ch/media/0_211s1yai

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Computer engineering

Databases: Relational databases

Related lectures (34)