Big Data With Hadoop Mapreduce

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Big Data with Hadoop MapReduce

Author : Rathinaraja Jeyaraj
Publisher : CRC Press
ISBN 13 : 1000439089
Total Pages : 269 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Big Data with Hadoop MapReduce by : Rathinaraja Jeyaraj

Download or read book Big Data with Hadoop MapReduce written by Rathinaraja Jeyaraj and published by CRC Press. This book was released on 2020-05-01 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all the necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc. Ultimately, readers will be able to: • understand what big data is and the factors that are involved • understand the inner workings of MapReduce, which is essential for certification exams • learn the features and weaknesses of MapReduce • set up Hadoop clusters with 100s of physical/virtual machines • create a virtual machine in AWS • write MapReduce with Eclipse in a simple way • understand other big data processing tools and their applications

Big Data with Hadoop MapReduce

Author : Rathinaraja Jeyaraj
Publisher : CRC Press
ISBN 13 : 1000398242
Total Pages : 427 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Big Data with Hadoop MapReduce by : Rathinaraja Jeyaraj

Download or read book Big Data with Hadoop MapReduce written by Rathinaraja Jeyaraj and published by CRC Press. This book was released on 2020-05-01 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all the necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc. Ultimately, readers will be able to: • understand what big data is and the factors that are involved • understand the inner workings of MapReduce, which is essential for certification exams • learn the features and weaknesses of MapReduce • set up Hadoop clusters with 100s of physical/virtual machines • create a virtual machine in AWS • write MapReduce with Eclipse in a simple way • understand other big data processing tools and their applications

Big Data with Hadoop Mapreduce

Author : Taylor & Francis Group
Publisher :
ISBN 13 : 9781774634844
Total Pages : pages
Book Rating : 4.6/5 (348 download)

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Book Synopsis Big Data with Hadoop Mapreduce by : Taylor & Francis Group

Download or read book Big Data with Hadoop Mapreduce written by Taylor & Francis Group and published by . This book was released on 2022-03-09 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data-Intensive Text Processing with MapReduce

Author : Jimmy Lin
Publisher : Springer Nature
ISBN 13 : 3031021363
Total Pages : 171 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Data-Intensive Text Processing with MapReduce by : Jimmy Lin

Download or read book Data-Intensive Text Processing with MapReduce written by Jimmy Lin and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks

Frank Kane's Taming Big Data with Apache Spark and Python

Author : Frank Kane
Publisher : Packt Publishing Ltd
ISBN 13 : 1787288307
Total Pages : 289 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Frank Kane's Taming Big Data with Apache Spark and Python by : Frank Kane

Download or read book Frank Kane's Taming Big Data with Apache Spark and Python written by Frank Kane and published by Packt Publishing Ltd. This book was released on 2017-06-30 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn Find out how you can identify Big Data problems as Spark problems Install and run Apache Spark on your computer or on a cluster Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets Implement machine learning on Spark using the MLlib library Process continuous streams of data in real time using the Spark streaming module Perform complex network analysis using Spark's GraphX library Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.

Big Data Analytics with Hadoop 3

Author : Sridhar Alla
Publisher : Packt Publishing Ltd
ISBN 13 : 1788624955
Total Pages : 471 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Big Data Analytics with Hadoop 3 by : Sridhar Alla

Download or read book Big Data Analytics with Hadoop 3 written by Sridhar Alla and published by Packt Publishing Ltd. This book was released on 2018-05-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Big Data and Hadoop

Author : VK Jain
Publisher : KHANNA PUBLISHING
ISBN 13 : 938260913X
Total Pages : 600 pages
Book Rating : 4.3/5 (826 download)

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Book Synopsis Big Data and Hadoop by : VK Jain

Download or read book Big Data and Hadoop written by VK Jain and published by KHANNA PUBLISHING. This book was released on 2017-01-01 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces you to the Big Data processing techniques addressing but not limited to various BI (business intelligence) requirements, such as reporting, batch analytics, online analytical processing (OLAP), data mining and Warehousing, and predictive analytics. The book has been written on IBMs Platform of Hadoop framework. IBM Infosphere BigInsight has the highest amount of tutorial matter available free of cost on Internet which makes it easy to acquire proficiency in this technique. This therefore becomes highly vunerable coaching materials in easy to learn steps. The book optimally provides the courseware as per MCA and M. Tech Level Syllabi of most of the Universities. All components of big Data Platform like Jaql, Hive Pig, Sqoop, Flume , Hadoop Streaming, Oozie: HBase, HDFS, FlumeNG, Whirr, Cloudera, Fuse , Zookeeper and Mahout: Machine learning for Hadoop has been discussed in sufficient Detail with hands on Exercises on each.

MapReduce Design Patterns

Author : Donald Miner
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449341985
Total Pages : 417 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis MapReduce Design Patterns by : Donald Miner

Download or read book MapReduce Design Patterns written by Donald Miner and published by "O'Reilly Media, Inc.". This book was released on 2012-11-21 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you’re using. Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations, and why design patterns are so important. All code examples are written for Hadoop. Summarization patterns: get a top-level view by summarizing and grouping data Filtering patterns: view data subsets such as records generated from one user Data organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easier Join patterns: analyze different datasets together to discover interesting relationships Metapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same job Input and output patterns: customize the way you use Hadoop to load or store data "A clear exposition of MapReduce programs for common data processing patterns—this book is indespensible for anyone using Hadoop." --Tom White, author of Hadoop: The Definitive Guide

Big Data Analytics with R and Hadoop

Author : Vignesh Prajapati
Publisher :
ISBN 13 : 9781782163282
Total Pages : 0 pages
Book Rating : 4.1/5 (632 download)

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Book Synopsis Big Data Analytics with R and Hadoop by : Vignesh Prajapati

Download or read book Big Data Analytics with R and Hadoop written by Vignesh Prajapati and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

Big Data

Author : Balamurugan Balusamy
Publisher : John Wiley & Sons
ISBN 13 : 1119701872
Total Pages : 368 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Big Data by : Balamurugan Balusamy

Download or read book Big Data written by Balamurugan Balusamy and published by John Wiley & Sons. This book was released on 2021-03-15 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

Hadoop MapReduce v2 Cookbook - Second Edition

Author : Thilina Gunarathne
Publisher : Packt Publishing Ltd
ISBN 13 : 1783285486
Total Pages : 322 pages
Book Rating : 4.7/5 (832 download)

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Book Synopsis Hadoop MapReduce v2 Cookbook - Second Edition by : Thilina Gunarathne

Download or read book Hadoop MapReduce v2 Cookbook - Second Edition written by Thilina Gunarathne and published by Packt Publishing Ltd. This book was released on 2015-02-25 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a Big Data enthusiast and wish to use Hadoop v2 to solve your problems, then this book is for you. This book is for Java programmers with little to moderate knowledge of Hadoop MapReduce. This is also a one-stop reference for developers and system admins who want to quickly get up to speed with using Hadoop v2. It would be helpful to have a basic knowledge of software development using Java and a basic working knowledge of Linux.

Big Data Analytics Beyond Hadoop

Author : Vijay Srinivas Agneeswaran
Publisher : FT Press
ISBN 13 : 0133838250
Total Pages : 235 pages
Book Rating : 4.1/5 (338 download)

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Book Synopsis Big Data Analytics Beyond Hadoop by : Vijay Srinivas Agneeswaran

Download or read book Big Data Analytics Beyond Hadoop written by Vijay Srinivas Agneeswaran and published by FT Press. This book was released on 2014-05-15 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master alternative Big Data technologies that can do what Hadoop can't: real-time analytics and iterative machine learning. When most technical professionals think of Big Data analytics today, they think of Hadoop. But there are many cutting-edge applications that Hadoop isn't well suited for, especially real-time analytics and contexts requiring the use of iterative machine learning algorithms. Fortunately, several powerful new technologies have been developed specifically for use cases such as these. Big Data Analytics Beyond Hadoop is the first guide specifically designed to help you take the next steps beyond Hadoop. Dr. Vijay Srinivas Agneeswaran introduces the breakthrough Berkeley Data Analysis Stack (BDAS) in detail, including its motivation, design, architecture, Mesos cluster management, performance, and more. He presents realistic use cases and up-to-date example code for: Spark, the next generation in-memory computing technology from UC Berkeley Storm, the parallel real-time Big Data analytics technology from Twitter GraphLab, the next-generation graph processing paradigm from CMU and the University of Washington (with comparisons to alternatives such as Pregel and Piccolo) Halo also offers architectural and design guidance and code sketches for scaling machine learning algorithms to Big Data, and then realizing them in real-time. He concludes by previewing emerging trends, including real-time video analytics, SDNs, and even Big Data governance, security, and privacy issues. He identifies intriguing startups and new research possibilities, including BDAS extensions and cutting-edge model-driven analytics. Big Data Analytics Beyond Hadoop is an indispensable resource for everyone who wants to reach the cutting edge of Big Data analytics, and stay there: practitioners, architects, programmers, data scientists, researchers, startup entrepreneurs, and advanced students.

Big Data For Dummies

Author : Judith S. Hurwitz
Publisher : John Wiley & Sons
ISBN 13 : 1118644174
Total Pages : 336 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Big Data For Dummies by : Judith S. Hurwitz

Download or read book Big Data For Dummies written by Judith S. Hurwitz and published by John Wiley & Sons. This book was released on 2013-04-02 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.

Hadoop: The Definitive Guide

Author : Tom White
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449338771
Total Pages : 687 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Hadoop: The Definitive Guide by : Tom White

Download or read book Hadoop: The Definitive Guide written by Tom White and published by "O'Reilly Media, Inc.". This book was released on 2012-05-10 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Learning Big Data with Amazon Elastic MapReduce

Author : Amarkant Singh
Publisher :
ISBN 13 : 9781782173434
Total Pages : 242 pages
Book Rating : 4.1/5 (734 download)

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Book Synopsis Learning Big Data with Amazon Elastic MapReduce by : Amarkant Singh

Download or read book Learning Big Data with Amazon Elastic MapReduce written by Amarkant Singh and published by . This book was released on 2014-10-10 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at developers and system administrators who want to learn about Big Data analysis using Amazon Elastic MapReduce. Basic Java programming knowledge is required. You should be comfortable with using command-line tools. Prior knowledge of AWS, API, and CLI tools is not assumed. Also, no exposure to Hadoop and MapReduce is expected.

BIG DATA AND HADOOP

Author : Mayank Bhusan
Publisher : BPB Publications
ISBN 13 : 9387284832
Total Pages : 333 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis BIG DATA AND HADOOP by : Mayank Bhusan

Download or read book BIG DATA AND HADOOP written by Mayank Bhusan and published by BPB Publications. This book was released on 2018-06-02 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book contains the latest trend in IT industry 'BigData and Hadoop'. It explains how big is 'Big Data' and why everybody is trying to implement this into their IT project.It includes research work on various topics, theoretical and practical approach, each component of the architecture is described along with current industry trends.Big Data and Hadoop have taken together are a new skill as per the industry standards. Readers will get a compact book along with the industry experience and would be a reference to help readers.KEY FEATURES Overview Of Big Data, Basics of Hadoop, Hadoop Distributed File System, HBase, MapReduce, HIVE: The Dataware House Of Hadoop, PIG: The Higher Level Programming Environment, SQOOP: Importing Data From Heterogeneous Sources, Flume, Ozzie, Zookeeper & Big Data Stream Mining, Chapter-wise Questions & Previous Years Questions

Modern Big Data Processing with Hadoop

Author : V Naresh Kumar
Publisher : Packt Publishing Ltd
ISBN 13 : 1787128814
Total Pages : 390 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Modern Big Data Processing with Hadoop by : V Naresh Kumar

Download or read book Modern Big Data Processing with Hadoop written by V Naresh Kumar and published by Packt Publishing Ltd. This book was released on 2018-03-30 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.