Apache Spark 2.x Cookbook by Rishi Yadav PDF

By Rishi Yadav

Key Features

  • This ebook comprises recipes on find out how to use Apache Spark as a unified compute engine
  • Cover tips to attach a number of resource structures to Apache Spark
  • Covers quite a few components of computing device studying together with supervised/unsupervised studying & suggestion engines

Book Description

While Apache Spark 1.x won loads of traction and adoption within the early years, Spark 2.x promises striking advancements within the components of API, schema know-how, functionality, established Streaming, and simplifying development blocks to construct larger, quicker, smarter, and extra available tremendous information functions. This publication uncovers most of these positive aspects within the type of dependent recipes to investigate and mature huge and complicated units of data.

Starting with fitting and configuring Apache Spark with a variety of cluster managers, you are going to discover ways to organize improvement environments. additional on, you may be brought to operating with RDDs, DataFrames and Datasets to function on schema conscious facts, and real-time streaming with quite a few assets equivalent to Twitter circulate and Apache Kafka. additionally, you will paintings via recipes on computing device studying, together with supervised studying, unsupervised studying & suggestion engines in Spark.

Last yet no longer least, the ultimate few chapters delve deeper into the strategies of graph processing utilizing GraphX, securing your implementations, cluster optimization, and troubleshooting.

What you'll learn

  • Install and configure Apache Spark with quite a few cluster managers & on AWS
  • Set up a improvement surroundings for Apache Spark together with Databricks Cloud notebook
  • Find out tips to function on facts in Spark with schemas
  • Get to grips with real-time streaming analytics utilizing Spark Streaming & established Streaming
  • Master supervised studying and unsupervised studying utilizing MLlib
  • Build a suggestion engine utilizing MLlib
  • Graph processing utilizing GraphX and GraphFrames libraries
  • Develop a suite of universal purposes or venture varieties, and suggestions that clear up advanced large information problems

About the Author

Rishi Yadav has 19 years of expertise in designing and constructing company purposes. he's an open resource software program specialist and advises American businesses on sizeable facts and public cloud developments. Rishi used to be commemorated as certainly one of Silicon Valley's forty less than forty in 2014. He earned his bachelor's measure from the celebrated Indian Institute of expertise, Delhi, in 1998.

About 12 years in the past, Rishi begun InfoObjects, an organization that is helping data-driven companies achieve new insights into facts. InfoObjects combines the ability of open resource and large info to unravel enterprise demanding situations for its consumers and has a unique specialise in Apache Spark. the corporate has been at the Inc. 5000 record of the quickest turning out to be businesses for six years in a row. InfoObjects has additionally been named the easiest position to paintings within the Bay region in 2014 and 2015.

Rishi is an open resource contributor and energetic blogger.

Table of Contents

  1. Getting all started with Apache Spark
  2. Developing purposes with Spark
  3. Spark SQL
  4. Working with exterior info Sources
  5. Spark Streaming
  6. Getting began with computer Learning
  7. Supervised studying with MLlib – Regression
  8. Supervised studying with MLlib – Classification
  9. Unsupervised learning
  10. Recommendations utilizing Collaborative Filtering
  11. Graph Processing utilizing GraphX and GraphFrames
  12. Optimizations and function Tuning

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