Spark Big Data Tutorials Learning Books
Blog: GestiSoft
Spark Big Data Tutorials (Training) Learning Books :- Apache Spark is an open sourced big data analysis framework, built first in 2009 in Berkeley’s AMPLab. The framework became open sourced in the next year; that’s in 2010.
Spark has many advantages compared to other frameworks like Storm and Hadoop. Every experienced data scientist suggests using Spark over others. The significant reason is nothing but its speed, ease of access and efficiency.
Spark runs ten times faster on disk and a whopping 100 times faster on memory. You can develop applications in Python, Scala, and Java with it.
Spark has many awesome features. If you are interested in learning Spark Big Data Analysis, you just landed on the right spot. Your wandering for Apache Spark tutorials ends right here.
- Spark Big Data Tutorial Books
Spark Big Data Tutorials Learning Books
This article is written to help you referring some useful books for learning Spark Big Data.
#1. Learning Spark: Lightning- Fast Big Data Analysis
‘Learning Spark: Lightning- Fast Big Data Analysis’ is a good introductory book for you if you are a beginner. It is written by Holden Karau.
I checked the availability of this book on Amazon. The good part is that you can get a Kindle edition also if you are an e- book lover. The book costs around 500 INR for each of the editions.
Among all, this book has got some positive reviews, which show the usefulness of it. The author took great effort in bringing every topic distinguishably. The lessons range from basic to advanced.
Though the book is in English, you won’t find it difficult to grasp even complicated ideas. Why because everything is explained in simple language.
Examples are given in three programming languages, Scala, Java and Python. As I already said, this is an introductory book. SO don’t expect concepts in detail. Another downside I observed is, the book uses Spark version 1.2.x. But 1.3.x version is already available.
#2. Advanced Analytics with Spark
The first book may not suit you. In such a scenario, you can use this book. It’s something that brings you to the next level of Spark Big Data Analysis.
I couldn’t find even a single negative review of this book on Amazon.in. Advanced Analytics with Spark is written by four data scientists. They are Sandy Ryza, Uri Laserson, Sean Owen and Josh Wills. All of them are Cloudera data engineers.
They start with the introduction of Spark and its ecosystem. Then the book progresses to patterns that apply common techniques like anomaly detection, collaborative filtering, and classification.
I recommend you to go with this book only if you have elementary ideas of machine languages and data analysis. You should also be aware of programming languages like Java, Scala, and Python (or at least one of them).
The patterns included in this book are
Recommending music and the Audioscrobbler dataset
Predicting forest cover with decision trees
Anomaly detection in network traffic with K-means clustering
Understanding Wikipedia with Latent Semantic Analysis
Analyzing co-occurrence networks with GraphX
Geospatial and temporal data analysis on the New York City Taxi Trips data
Estimating financial risk through Monte Carlo simulation
Analyzing genomics data and the BDG project
Analyzing neuroimaging data with PySpark and Thunder
#3. Machine Learning with Spark – Tackle Big Data with Powerful Spark Machine Learning Algorithms
This is a giant book just like the name. You need to invest some good bucks to get your hands on it. On Amazon, the paperback edition costs Rs. 4000 while the Kindle edition costs only Rs. 562. So, if you have an Android device, do download Amazon Kindle and buy the Kindle edition, instead of buying the first option. The content you will get with both the options is the same.
The book is written by Nick Pentreath. He guides you through the basics and complex concepts of Apache Spark. Also, you will be able to develop your first Spark program in Python, Scala and Java.
It is also possible to set up and configure a development environment for Spark on your local computer. This book enables you to do that too.
The basic techniques used in this book are dimensionality reduction, classification, clustering, regression and recommender systems.
If you want more insights on this book, refer to the table of content given below.
Table of Content
Getting Up and Running with Spark
Designing a Machine Learning System
Obtaining, Processing and Preparing Data with Spark
Building a Recommendation Engine with Spark
Building a Classification Model with Spark
Building a Regression Model with Spark
Building a Clustering Model with Spark
Dimensionality Reduction with Spark
Advanced Text Processing with Spark
Real-Time Machine Learning with Spark Streaming
Choose One NOW
I have given you three books, which I find useful to you. I did not give a random list.
Go to the purchasing page with the buying links at the bottom of every section, have an idea about what they deal with. Then, choose the one, which suits you the best.
All the best for your data analysis future.
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