Advanced Apache Spark for Data Scientists and Developers
- 3.5
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Brief Introduction
Apache SparkDescription
Apache Spark is an open source data processing engine. Spark is designed to provide fast processing of large datasets, and high performance for a wide range of analytics applications. Unlike MapReduce, Spark enables in-memory cluster computing which greatly improves the speed of iterative algorithms and interactive data mining tasks.
Adastra Academy’s Advanced Apache Spark includes illuminating video lectures, thorough application examples, a guide to install the NetBeans Integrated Development Environment, and quizzes. Through this course, you will learn about Spark’s four built-in libraries - SparkStreaming, DataFrames (SparkSQL), MLlib and GraphX - and how to develop, build, tune, and debug Spark applications. The course exercises will enable you to become proficient at creating fully functional real-world applications using the Apache Spark libraries. Unlike other courses, we give you the guided and ground-up approach to learning Spark that you need in order to become an expert.
Requirements
- Requirements
- Completed a introductory Apache Spark course. Adastra Academy's Introduction to Apache Spark for Developers and Engineers recommended.
- A beginner to intermediate understanding of the Scala programming language. Adastra Academy's Scala in Practice recommended.
- A basic understanding of Apache Hadoop and Big Data
Adastra Academy
3.5 Raiting
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