Apache Spark: Deep Dive into internal architecture

Join me as we dive into Apache Spark, a data analytics system introduced in a 2010 paper from Berkeley.

Spark is a favorite among software engineers, data scientists, and machine learning engineers. It provides a single platform on top of multiple specialized systems like GraphX, MLlib, and Discretized Streams.

In this video, we see how Spark's in-memory processing outpaces traditional MapReduce, achieving up to 1000x speed improvements, and explore its scalability, performance, and integration with technologies like Kubernetes.

The core principles behind Spark's design are general-purpose data analytics, fault tolerance, and pluggability with various cluster managers and data sources.

This video is for all engineers who want to understand Spark's architecture and use cases.

00:00 What is Apache Spark?
01:56 Key Features
02:50 High-Level Design
06:30 Data Flow
09:44 Conclusion
10:13 Interesting News!

References:
Spark Paper: https://people.csail.mit.edu/matei/papers/2012/nsdi_spark.pdf
Older Paper: https://people.csail.mit.edu/matei/papers/2010/hotcloud_spark.pdf
Mesos Paper: https://www.usenix.org/legacy/event/nsdi11/tech/full_papers/Hindman.pdf
InterviewReady: http://interviewready.io/resources/

Courses:
System Design Simplified Course: https://interviewready.io/course-page/system-design-course
Low-Level Design Course: https://interviewready.io/course-page/low-level-design-course

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