Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Big Data Analytics
Big Data Analytics

Big Data Analytics: Real time analytics using Apache Spark and Hadoop

eBook
€8.99 €32.99
Paperback
€41.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Table of content icon View table of contents Preview book icon Preview Book

Big Data Analytics

Chapter 2. Getting Started with Apache Hadoop and Apache Spark

In this chapter, we will understand the basics of Hadoop and Spark, how Spark is different from MapReduce, and get started with the installation of clusters and setting up the tools needed for analytics.

This chapter is divided into the following subtopics:

  • Introducing Apache Hadoop
  • Introducing Apache Spark
  • Discussing why we use Hadoop with Spark
  • Installing Hadoop and Spark clusters

Introducing Apache Hadoop

Apache Hadoop is a software framework that enables distributed processing on large clusters with thousands of nodes and petabytes of data. Apache Hadoop clusters can be built using commodity hardware where failure rates are generally high. Hadoop is designed to handle these failures gracefully without user intervention. Also, Hadoop uses the move computation to the data approach, thereby avoiding significant network I/O. Users will be able to develop parallel applications quickly, focusing on business logic rather than doing the heavy lifting of distributing data, distributing code for parallel processing, and handling failures.

Apache Hadoop has mainly four projects: Hadoop Common, Hadoop Distributed File System (HDFS), Yet Another Resource Negotiator (YARN), and MapReduce.

In simple words, HDFS is used to store data, MapReduce is used to process data, and YARN is used to manage the resources (CPU and memory) of the cluster and common utilities that support Hadoop...

Introducing Apache Spark

Hadoop and MR have been around for 10 years and have proven to be the best solution to process massive data with high performance. However, MR lacked performance in iterative computing where the output between multiple MR jobs had to be written to HDFS. In a single MR job, it lacked performance because of the drawbacks of the MR framework.

Let's take a look at the history of computing trends to understand how computing paradigms have changed over the last two decades.

The trend has been to Reference the URI when the network was cheaper (in 1990), Replicate when storage became cheaper (in 2000), and Recompute when memory became cheaper (in 2010), as shown in Figure 2.5:

Introducing Apache Spark

Figure 2.5: Trends of computing

Note

So, what really changed over a period of time?

Tape is dead, disk has become tape, and SSD has almost become the disk. Now, caching data in RAM is the current trend.

Let's understand why memory-based computing is important and how it provides significant performance...

Why Hadoop plus Spark?

Apache Spark shines better when it is combined with Hadoop. To understand this, let's take a look at Hadoop and Spark features.

Hadoop features

Feature

Details

Unlimited scalability

Stores unlimited data by scaling out HDFS

Effectively manages cluster resources with YARN

Runs multiple applications along with Spark

Thousands of simultaneous users

Enterprise grade

Provides security with Kerberos authentication and ACLs authorization

Data encryption

High reliability and integrity

Multi-tenancy

Wide range of applications

Files: Structured, semi-structured, and unstructured

Streaming sources: Flume and Kafka

Databases: Any RDBMS and NoSQL database

Spark features

Feature

Details

Easy development

No boilerplate coding

Multiple native APIs such as Java, Scala, Python, and R

REPL for Scala, Python, and R

Optimized performance

Caching

Optimized shuffle

Catalyst Optimizer

Unification

Batch, SQL, machine learning, streaming, and graph processing...

Installing Hadoop plus Spark clusters

Before installing Hadoop and Spark, let's understand the versions of Hadoop and Spark. Spark is offered as a service in all three popular Hadoop distributions from Cloudera, Hortonworks, and MapR. The current Hadoop and Spark versions are 2.7.2 and 2.0 respectively as of writing this book. However, Hadoop distributions might have a lower version of Spark as Hadoop and Spark release cycles do not coincide.

For the upcoming chapters' practical exercises, let's use one of the free virtual machines (VM) from Cloudera, Hortonworks, and MapR, or use an open source version of Apache Spark. These VMs makes it easy to get started with Spark and Hadoop. The same exercises can be run on bigger clusters as well.

The prerequisites to use virtual machines on your laptop are as follows:

  • RAM of 8 GB and above
  • At least two virtual CPUs
  • The latest VMWare Player or Oracle VirtualBox must be installed for Windows or Linux OS
  • The latest Oracle VirtualBox or VMWare...

Summary

Apache Hadoop provides you with a reliable and scalable framework (HDFS) for Big Data storage and a powerful cluster resource management framework (YARN) to run and manage multiple Big Data applications. Apache Spark provides in-memory performance in Big Data processing and libraries and APIs for interactive exploratory analytics, real-time analytics, machine learning, and graph analytics. While MR was the primary processing engine on top of Hadoop, it had multiple drawbacks, such as poor performance and inflexibility in designing applications. Apache Spark is a replacement for MR. All MR-based tools, such as Hive, Pig, Mahout, and Crunch, have already started offering Apache Spark as an additional execution engine apart from MR.

Nowadays, Big Data projects are being implemented in many businesses, from large Fortune 500 companies to small start-ups. Organizations gain an edge if they can go from raw data to decisions quickly with easy-to-use tools to develop applications and explore...

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools.
  • Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and SparkR.
  • Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall.

Description

Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data.

Who is this book for?

Though this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory.

What you will learn

  • Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop
  • Understand all the Hadoop and Spark ecosystem components
  • Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx
  • See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming
  • Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall.

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 28, 2016
Length: 326 pages
Edition : 1st
Language : English
ISBN-13 : 9781785889707
Category :
Concepts :
Tools :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Product Details

Publication date : Sep 28, 2016
Length: 326 pages
Edition : 1st
Language : English
ISBN-13 : 9781785889707
Category :
Concepts :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
€18.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
€189.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts
€264.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total €26.97 €92.97 €66.00 saved
Big Data Analytics
€41.99
Hadoop Blueprints
€36.99
Real-Time Big Data Analytics
€36.99
Total €26.97€92.97 €66.00 saved Stars icon
Banner background image

Table of Contents

11 Chapters
1. Big Data Analytics at a 10,000-Foot View Chevron down icon Chevron up icon
2. Getting Started with Apache Hadoop and Apache Spark Chevron down icon Chevron up icon
3. Deep Dive into Apache Spark Chevron down icon Chevron up icon
4. Big Data Analytics with Spark SQL, DataFrames, and Datasets Chevron down icon Chevron up icon
5. Real-Time Analytics with Spark Streaming and Structured Streaming Chevron down icon Chevron up icon
6. Notebooks and Dataflows with Spark and Hadoop Chevron down icon Chevron up icon
7. Machine Learning with Spark and Hadoop Chevron down icon Chevron up icon
8. Building Recommendation Systems with Spark and Mahout Chevron down icon Chevron up icon
9. Graph Analytics with GraphX Chevron down icon Chevron up icon
10. Interactive Analytics with SparkR Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7
(7 Ratings)
5 star 85.7%
4 star 0%
3 star 14.3%
2 star 0%
1 star 0%
Filter icon Filter
Top Reviews

Filter reviews by




Ravi Oct 11, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The big data analytics is very helpful book for anyone familiar with hadoop technologies and also for beginners learning spark ecosystem.
Amazon Verified review Amazon
Subbaraju Cherukuri Oct 11, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Big data had remained an enigma to many. This book by Venkat Ankam, a highly experienced & well respected Big data trainer and Architect deals with this very premise and bares it to turn it upside down. He uses simple, regularly used instructional language constructs to unravel the most popular big data technologies of Hadoop & Spark. The reader gets immersed into it as into a popular work of fiction. So engrossing is his style of presentation that one generally does not care for a few grammatical lacunae. It is so comprehensive that if you did not find a concept in it, you may treat that it is still in incubation. The author deals with both data analytics and data science in intricate detail and with mesmerising alacrity. The range of case studies discussed cover all one might ever come across."The bible for every Hadoop and Spark engineer."
Amazon Verified review Amazon
Amazon Customer Oct 11, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Great book I read after a long time, Nice examples are provided, content provided in easily understandable format. I am very glad that I read this book.Thanks. Amruth puppala
Amazon Verified review Amazon
Vin Oct 11, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is excellent book forbig data analytics concepts and It covered all in detail.
Amazon Verified review Amazon
venkat Oct 10, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book has covered all aspects of the big data concepts that are required for anyone to compete in the big data market.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.