By Rishi Yadav
- This publication comprises recipes on how you can use Apache Spark as a unified compute engine
- Cover find out how to attach a variety of resource platforms to Apache Spark
- Covers quite a few components of computing device studying together with supervised/unsupervised studying & advice engines
While Apache Spark 1.x received loads of traction and adoption within the early years, Spark 2.x supplies striking advancements within the parts of API, schema know-how, functionality, dependent Streaming, and simplifying construction blocks to construct greater, quicker, smarter, and extra available tremendous facts functions. This e-book uncovers a lot of these good points within the kind of established recipes to research and mature huge and intricate units of data.
Starting with fitting and configuring Apache Spark with numerous cluster managers, you are going to learn how to manage improvement environments. extra on, you may be brought to operating with RDDs, DataFrames and Datasets to function on schema conscious info, and real-time streaming with quite a few assets similar to Twitter circulation and Apache Kafka. additionally, you will paintings via recipes on laptop studying, together with supervised studying, unsupervised studying & advice engines in Spark.
Last yet no longer least, the ultimate few chapters delve deeper into the techniques of graph processing utilizing GraphX, securing your implementations, cluster optimization, and troubleshooting.
What you are going to learn
- Install and configure Apache Spark with a number of cluster managers & on AWS
- Set up a improvement surroundings for Apache Spark together with Databricks Cloud notebook
- Find out the right way to function on info in Spark with schemas
- Get to grips with real-time streaming analytics utilizing Spark Streaming & based Streaming
- Master supervised studying and unsupervised studying utilizing MLlib
- Build a suggestion engine utilizing MLlib
- Graph processing utilizing GraphX and GraphFrames libraries
- Develop a collection of universal purposes or undertaking forms, and suggestions that resolve advanced vast facts 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 mammoth facts and public cloud traits. Rishi was once venerated as one in every of Silicon Valley's forty lower than forty in 2014. He earned his bachelor's measure from the distinguished Indian Institute of expertise, Delhi, in 1998.
About 12 years in the past, Rishi begun InfoObjects, a firm that is helping data-driven companies achieve new insights into information. InfoObjects combines the ability of open resource and massive info to unravel enterprise demanding situations for its consumers and has a distinct specialise in Apache Spark. the corporate has been at the Inc. 5000 checklist 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
- Getting began with Apache Spark
- Developing functions with Spark
- Spark SQL
- Working with exterior information Sources
- Spark Streaming
- Getting begun with desktop Learning
- Supervised studying with MLlib – Regression
- Supervised studying with MLlib – Classification
- Unsupervised learning
- Recommendations utilizing Collaborative Filtering
- Graph Processing utilizing GraphX and GraphFrames
- Optimizations and function Tuning
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Additional info for Apache Spark 2.x Cookbook
Apache Spark 2.x Cookbook by Rishi Yadav