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Big Data Architect???s Handbook
Big Data Architect???s Handbook

Big Data Architect???s Handbook: A guide to building proficiency in tools and systems used by leading big data experts

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Big Data Architect???s Handbook

Big Data Environment Setup

In this chapter, we will go through a step by step guide on how to set up an environment to run big data applications. We will go through the following step-by-step setup guides:

  • Installing Oracle VM VirtualBox
  • Installing and configuring Ubuntu
  • Installing Apache Hadoop prerequisite applications
  • Installing Apache Hadoop
  • Configuring Hadoop to run as a single node server and pseudo-distributed mode

Oracle VM VirtualBox installation

There is a lot of software available in the market that can help you create virtual environments, also known as virtual machines, on top of your existing operating system. Creation of a virtual machine is useful if you want to try a new setup or application without affecting your existing configuration. Most of the softwares are available for all platforms, such as Windows, macOS, and different Linux distributions. Some of them are paid and some are free. We will be using Oracle VM VirtualBox, as it is a free open source software available under GNU General Public License (GPL) version 2:

  1. Download the latest version of the application from http://www.virtualbox.org/, based on your operation system.
  2. Double click on the downloaded file to start setup.
  1. Click Next and leave the default options selected, as shown in the following screenshot...

Ubuntu installation

After the successful installation of VirtualBox application, let's go ahead and create our first virtual machine and install Ubuntu Linux on it. Later, we will be using this Ubuntu Linux to configure big data applications and modules. Follow the steps given to set up the VM and install Ubuntu:

  1. Download the Ubuntu ISO file from https://www.ubuntu.com/download/desktop.
  2. Open the VirtualBox application and click on New. Give a Name to your new virtual machine as shown in the following screenshot:
Figure 2.2.1
  1. Assign memory (RAM). It is recommended to assign 4GB, as shown in the screenshot that follows:
Figure 2.2.2
  1. The next step is to Create a virtual hard disk now for your VM, as shown in the screenshot that follows:
Figure 2.2.3
  1. It will ask you to select the type of virtual hard disk you want to create; keep the default option selected...

Hadoop prerequisite installation

Hadoop modules are mostly written in Java, so one of the prerequisites is to install Java. Hadoop daemons requires SSH to encrypt the communication between its nodes in an insecure environment. We will now go through a step by step guide for installing and configuring Java and SSH.

Java installation

Hadoop is compatible with both Oracle Java and OpenJDK, but it is preferable to install Oracle Java. To install it, use the following instructions:

  1. Download JDK and JRE from http://www.oracle.com/technetwork/java/javase/downloads/index.html.
  2. Copy the downloaded tar.gz file to the location where you want to install Java.
  3. Extract and install Java by using the following command. Make sure...

Apache Hadoop installation

After the successful installation of the prerequisites, it is now time to start the installation and configuration of Hadoop itself. The following are the steps to get started:

  1. Download the stable version of Apache Hadoop from http://www-us.apache.org/dist/hadoop/common/. As of now the stable version available for download is hadoop-2.8.1.
  1. Extract the downloaded file by using the following command:
$ tar zxvf hadoop-2.8.1.tar.gz
  1. It's time to configure some parameters to run Hadoop. Use the following command to edit the hadoop-env.sh configuration file:
$ gedit etc/hadoop/hadoop-env.sh
  1. Look for the following line to set the JAVA_HOME path. Replace /home/hadoopadmin/jdk1.8.0_144/ with the directory where you have installed it. In our case, it will remain the same:
# set to the root of your Java installation
export JAVA_HOME...

Summary

In this chapter, we have gone through a step by step guide for installing and setting up a new virtual machine. Then, while using our new virtual machine, we have gone through the installation of Ubuntu to treat it as a dedicated server. We then learnt how to install and configure Apache Hadoop in a single node environment as well as in pseudo-distributed mode. In between, we have also gone through a step by step guide to the installation of the Hadoop prerequisite applications Java and SSH. Now, we are ready to go deeper into the big data world, and will be able to execute our programs.

In the next chapter, we will take a deep dive into the Hadoop echo system, considering the past and present of Hadoop, HDFS, MapReduce, and YARN in detail.

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Key benefits

  • • Learn to build and run a big data application with sample code
  • • Explore examples to implement activities that a big data architect performs
  • • Use Machine Learning and AI for structured and unstructured data

Description

The big data architects are the “masters” of data, and hold high value in today’s market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights. Big Data Architect’s Handbook takes you through developing a complete, end-to-end big data pipeline, which will lay the foundation for you and provide the necessary knowledge required to be an architect in big data. Right from understanding the design considerations to implementing a solid, efficient, and scalable data pipeline, this book walks you through all the essential aspects of big data. It also gives you an overview of how you can leverage the power of various big data tools such as Apache Hadoop and ElasticSearch in order to bring them together and build an efficient big data solution. By the end of this book, you will be able to build your own design system which integrates, maintains, visualizes, and monitors your data. In addition, you will have a smooth design flow in each process, putting insights in action.

Who is this book for?

Big Data Architect’s Handbook is for you if you are an aspiring data professional, developer, or IT enthusiast who aims to be an all-round architect in big data. This book is your one-stop solution to enhance your knowledge and carry out easy to complex activities required to become a big data architect.

What you will learn

  • • Learn Hadoop Ecosystem and Apache projects
  • • Understand, compare NoSQL database and essential software architecture
  • • Cloud infrastructure design considerations for big data
  • • Explore application scenario of big data tools for daily activities
  • • Learn to analyze and visualize results to uncover valuable insights
  • • Build and run a big data application with sample code from end to end
  • • Apply Machine Learning and AI to perform big data intelligence
  • • Practice the daily activities performed by big data architects

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 21, 2018
Length: 486 pages
Edition : 1st
Language : English
ISBN-13 : 9781788835824
Vendor :
Apache
Category :
Languages :
Concepts :
Tools :

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Product Details

Publication date : Jun 21, 2018
Length: 486 pages
Edition : 1st
Language : English
ISBN-13 : 9781788835824
Vendor :
Apache
Category :
Languages :
Concepts :
Tools :

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Table of Contents

20 Chapters
Why Big Data? Chevron down icon Chevron up icon
Big Data Environment Setup Chevron down icon Chevron up icon
Hadoop Ecosystem Chevron down icon Chevron up icon
NoSQL Database Chevron down icon Chevron up icon
Off-the-Shelf Commercial Tools Chevron down icon Chevron up icon
Containerization Chevron down icon Chevron up icon
Network Infrastructure Chevron down icon Chevron up icon
Cloud Infrastructure Chevron down icon Chevron up icon
Security and Monitoring Chevron down icon Chevron up icon
Frontend Architecture Chevron down icon Chevron up icon
Backend Architecture Chevron down icon Chevron up icon
Machine Learning Chevron down icon Chevron up icon
Artificial Intelligence Chevron down icon Chevron up icon
Elasticsearch Chevron down icon Chevron up icon
Structured Data Chevron down icon Chevron up icon
Unstructured Data Chevron down icon Chevron up icon
Data Visualization Chevron down icon Chevron up icon
Financial Trading System Chevron down icon Chevron up icon
Retail Recommendation System Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(2 Ratings)
5 star 50%
4 star 0%
3 star 0%
2 star 0%
1 star 50%
Placeholder Jul 23, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good
Amazon Verified review Amazon
James Apr 27, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
It's basically a very high level description of well known big data tools. You could probably get the same amount of info from just Googling "what is Hadoop". If this is meant to be a 'bible' for big data architects then I am genuinely concerned about the future of our industry.
Amazon Verified review Amazon
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