Hands On Big Data Analysis With Hadoop 3


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Big Data Analytics with Hadoop 3


Big Data Analytics with Hadoop 3

Author: Sridhar Alla

language: en

Publisher: Packt Publishing Ltd

Release Date: 2018-05-31


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Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.

Hands-on Big Data Analysis with Hadoop 3


Hands-on Big Data Analysis with Hadoop 3

Author: Tomasz Lelek

language: en

Publisher:

Release Date: 2018


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"This course is your guide to performing real-time data analytics and stream processing with Spark. Use different components and tools such as HDFS, HBase, and Hive to process raw data. Learn how tools such as Hive and Pig aid in this process. In this course, you will start off by learning data analysis techniques with Hadoop using tools such as Hive. Furthermore, you will learn to apply these techniques in real-world big data applications. Also, you will delve into Spark and its related tools to perform real-time data analytics, streaming, and batch processing on your application. Finally, you'll learn how to extend your analytics solutions to the cloud."--Resource description page.

A Hands-on Introduction to Big Data Analytics


A Hands-on Introduction to Big Data Analytics

Author: Funmi Obembe

language: en

Publisher: SAGE Publications Limited

Release Date: 2024-02-23


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This practical textbook offers a hands-on introduction to big data analytics, helping you to develop the skills required to hit the ground running as a data professional. It complements theoretical foundations with an emphasis on the application of big data analytics, illustrated by real-life examples and datasets. Containing comprehensive coverage of all the key topics in this area, this book uses open-source technologies and examples in Python and Apache Spark. Learning features include: - Ethics by Design encourages you to consider data ethics at every stage. - Industry Insights facilitate a deeper understanding of the link between what you are studying and how it is applied in industry. - Datasets, questions, and exercises give you the opportunity to apply your learning. Dr Funmi Obembe is the Head of Technology at the Faculty of Arts, Science and Technology, University of Northampton. Dr Ofer Engel is a Data Scientist at the University of Groningen.