Mastering Hadoop

Do you want to broaden your Hadoop skill set and take your knowledge to the next level? Do you wish to enhance your knowledge of Hadoop to solve challenging data processing problems? Are your Hadoop jobs, Pig scripts, or Hive queries not working as fast as you intend? Are you looking to understand the benefits of upgrading Hadoop? If the answer is yes to any of these, this book is for you. It assumes novice-level familiarity with Hadoop.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key FeaturesGet to grips with the newly introduced features and capabilities of Hadoop 3Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystemSharpen your Hadoop skills with real-world case studies and codeBook Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learnGain an in-depth understanding of distributed computing using Hadoop 3Develop enterprise-grade applications using Apache Spark, Flink, and moreBuild scalable and high-performance Hadoop data pipelines with security, monitoring, and data governanceExplore batch data processing patterns and how to model data in HadoopMaster best practices for enterprises using, or planning to use, Hadoop 3 as a data platformUnderstand security aspects of Hadoop, including authorization and authenticationWho this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

Understand data in a simple way using a data lake. KEY FEATURES ● In-depth practical demonstration of Hadoop/Yarn concepts with numerous examples. ● Includes graphical illustrations and visual explanations for Hadoop commands and parameters. ● Includes details of dimensional modeling and Data Vault modeling. ● Includes details of how to create and define a structure to a data lake. DESCRIPTION The book 'Data Processing and Modeling with Hadoop' explains how a distributed system works and its benefits in the big data era in a straightforward and clear manner. After reading the book, you will be able to plan and organize projects involving a massive amount of data. The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution. It discusses security and the measures that are utilized to reduce the impact of security. Self-service analytics, Data Lake, Data Vault 2.0, and Data Mesh are discussed in the book. After reading this book, the reader will have a thorough understanding of how to structure a data lake, as well as the ability to plan, organize, and carry out the implementation of a data-driven business with full governance and security. WHAT YOU WILL LEARN ● Learn the basics of components to the Hadoop Ecosystem. ● Understand the structure, files, and zones of a Data Lake. ● Learn to implement the security part of the Hadoop Ecosystem. ● Learn to work with the Data Vault 2.0 modeling. ● Learn to develop a strategy to define good governance. ● Learn new tools to work with Data and Big Data WHO THIS BOOK IS FOR This book caters to big data developers, technical specialists, consultants, and students who want to build good proficiency in big data. Knowing basic SQL concepts, modeling, and development would be good, although not mandatory. TABLE OF CONTENTS 1. Understanding the Current Moment 2. Defining the Zones 3. The Importance of Modeling 4. Massive Parallel Processing 5. Doing ETL/ELT 6. A Little Governance 7. Talking About Security 8. What Are the Next Steps?

About the Book: The book is divided into 4 modules which consist of 21 chapters, that narrates briefly about the top five recent emerging trends such as: Cloud Computing, Internet of Things (IoT), Blockchain, Artificial Intelligence, and Machine Learning. At the end of each module, authors have provided two Appendices. One is Job oriented short-type questions with answers, and the second one provide us different MCQs with their keys. Salient Features of the Book:  Detailed Coverage on Topics like: Introduction to Cloud Computing, Cloud Architecture, Cloud Applications, Cloud Platforms, Open-Source Cloud Simulation Tools, and Mobile Cloud Computing.  Expanded Coverage on Topics like: Introduction to IoT, Architecture, Core Modules, Communication models and protocols, IoT Environment, IoT Testing, IoT and Cloud Computing.  Focused Coverage on Topics like: Introduction to Blockchain Technology, Security and Privacy component of Blockchain Technology, Consensus Algorithms, Blockchain Development Platform, and Various Applications.  Dedicated Coverage on Topics like: Introduction to Artificial Intelligence and Machine Learning Techniques, Types of Machine Learning, Clustering Algorithms, K-Nearest Neighbor Algorithm, Artificial Neural Network, Deep Learning, and Applications of Machine Learning.  Pictorial Two-Minute Drill to Summarize the Whole Concept.  Inclusion of 300 Job Oriented Short Type Questions with Answers for the aspirants to have the Thoroughness, Practice and Multiplicity.  Around 178 Job Oriented MCQs with their keys.  Catch Words and Questions on Self-Assessment at Chapter-wise Termination. About the Authors: Dr. Rajesh Kumar Dhanaraj is an Associate Professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, Uttar Pradesh, India. He holds a Ph.D. degree in Information and Communication Engineering from Anna University Chennai, India. He has published more than 20 authored and edited books on various emerging technologies and more than 35 articles in various peer-reviewed journals and international conferences and contributed chapters to the books. His research interests include Machine Learning, Cyber-Physical Systems and Wireless Sensor Networks. He is an expert advisory panel member of Texas Instruments Inc. USA. Mr. Soumya Ranjan Jena is currently working as an Assistant Professor in the Department of CSE, School of Computing at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science & Technology, Avadi, Chennai, Tamil Nadu, India. He has teaching and research experience from various reputed institutions in India like Galgotias University, Greater Noida, Uttar Pradesh, AKS University, Satna, Madhya Pradesh, K L Deemed to be University, Guntur, Andhra Pradesh, GITA (Autonomous), Bhubaneswar, Odisha. He has been awarded M.Tech in Information Technology from Utkal University, Odisha, B.Tech in Computer Science & Engineering from BPUT, Odisha, and Cisco Certified Network Associate (CCNA) from Central Tool Room and Training Centre (CTTC), Bhubaneswar, Odisha. He has got the immense experience to teach to graduate as well as post-graduate students and author of two books i.e. “Theory of Computation and Application” and “Design and Analysis of Algorithms”. He has published more than 25 research papers on Cloud Computing, IoT in various international journals and conferences which are indexed by Scopus, Web of Science, and also published six patents out of which one is granted in Australia. Mr. Ashok Kumar Yadav is currently working as Dean Academics and Assistant Professor at Rajkiya Engineering College, Azamgarh, Uttar Pradesh. He has worked as an Assistant Professor (on Ad-hoc) in the Department of Computer Science, University of Delhi. He has also worked with Cluster Innovation Center, University of Delhi, New Delhi. He qualified for UGC-JRF. Presently, he is pursuing his Ph.D. in Computer Science from JNU, New Delhi. He has received M.Tech in Computer Science and Technology from JNU, New Delhi. He has presented and published papers at international conferences and journals on blockchain technology and machine learning. He has delivered various expert lectures on reputed institutes. Ms. Vani Rajasekar completed B. Tech (Information Technology), M. Tech (Information and Cyber warfare) in Department of Information Technology, Kongu Engineering College, Erode, Tamil Nadu, India. She is pursuing her Ph.D. (Information and Communication Engineering) in the area of Biometrics and Network security. Presently she is working as an Assistant professor in the Department of Computer Science and Engineering, Kongu Engineering College Erode, Tamil Nadu, India for the past 5 years. Her areas of interest include Cryptography, Biometrics, Network Security, and Wireless Networks. She has authored around 20 research papers and book chapters published in various international journals and conferences which were indexed in Scopus, Web of Science, and SCI.

The book is aimed at intermediate developers with an understanding of core database concepts who want to become a master at implementing Cassandra for their application.

An expert's guide to build fault tolerant MongoDB application About This Book Master the advanced modeling, querying, and administration techniques in MongoDB and become a MongoDB expert Covers the latest updates and Big Data features frequently used by professional MongoDB developers and administrators If your goal is to become a certified MongoDB professional, this book is your perfect companion Who This Book Is For Mastering MongoDB is a book for database developers, architects, and administrators who want to learn how to use MongoDB more effectively and productively. If you have experience in, and are interested in working with, NoSQL databases to build apps and websites, then this book is for you. What You Will Learn Get hands-on with advanced querying techniques such as indexing, expressions, arrays, and more. Configure, monitor, and maintain highly scalable MongoDB environment like an expert. Master replication and data sharding to optimize read/write performance. Design secure and robust applications based on MongoDB. Administer MongoDB-based applications on-premise or in the cloud Scale MongoDB to achieve your design goals Integrate MongoDB with big data sources to process huge amounts of data In Detail MongoDB has grown to become the de facto NoSQL database with millions of users—from small startups to Fortune 500 companies. Addressing the limitations of SQL schema-based databases, MongoDB pioneered a shift of focus for DevOps and offered sharding and replication maintainable by DevOps teams. The book is based on MongoDB 3.x and covers topics ranging from database querying using the shell, built in drivers, and popular ODM mappers to more advanced topics such as sharding, high availability, and integration with big data sources. You will get an overview of MongoDB and how to play to its strengths, with relevant use cases. After that, you will learn how to query MongoDB effectively and make use of indexes as much as possible. The next part deals with the administration of MongoDB installations on-premise or in the cloud. We deal with database internals in the next section, explaining storage systems and how they can affect performance. The last section of this book deals with replication and MongoDB scaling, along with integration with heterogeneous data sources. By the end this book, you will be equipped with all the required industry skills and knowledge to become a certified MongoDB developer and administrator. Style and approach This book takes a practical, step-by-step approach to explain the concepts of MongoDB. Practical use-cases involving real-world examples are used throughout the book to clearly explain theoretical concepts.

If you are a Java developer with experience in developing applications with Spring, then this book is perfect for you. A good working knowledge of Spring programming conventions and applying dependency injections is recommended to make the most of this book.

Unlock the power of your data with Hadoop 2.X ecosystem and its data warehousing techniques across large data sets About This Book Conquer the mountain of data using Hadoop 2.X tools The authors succeed in creating a context for Hadoop and its ecosystem Hands-on examples and recipes giving the bigger picture and helping you to master Hadoop 2.X data processing platforms Overcome the challenging data processing problems using this exhaustive course with Hadoop 2.X Who This Book Is For This course is for Java developers, who know scripting, wanting a career shift to Hadoop - Big Data segment of the IT industry. So if you are a novice in Hadoop or an expert, this book will make you reach the most advanced level in Hadoop 2.X. What You Will Learn Best practices for setup and configuration of Hadoop clusters, tailoring the system to the problem at hand Integration with relational databases, using Hive for SQL queries and Sqoop for data transfer Installing and maintaining Hadoop 2.X cluster and its ecosystem Advanced Data Analysis using the Hive, Pig, and Map Reduce programs Machine learning principles with libraries such as Mahout and Batch and Stream data processing using Apache Spark Understand the changes involved in the process in the move from Hadoop 1.0 to Hadoop 2.0 Dive into YARN and Storm and use YARN to integrate Storm with Hadoop Deploy Hadoop on Amazon Elastic MapReduce and Discover HDFS replacements and learn about HDFS Federation In Detail As Marc Andreessen has said “Data is eating the world,” which can be witnessed today being the age of Big Data, businesses are producing data in huge volumes every day and this rise in tide of data need to be organized and analyzed in a more secured way. With proper and effective use of Hadoop, you can build new-improved models, and based on that you will be able to make the right decisions. The first module, Hadoop beginners Guide will walk you through on understanding Hadoop with very detailed instructions and how to go about using it. Commands are explained using sections called “What just happened” for more clarity and understanding. The second module, Hadoop Real World Solutions Cookbook, 2nd edition, is an essential tutorial to effectively implement a big data warehouse in your business, where you get detailed practices on the latest technologies such as YARN and Spark. Big data has become a key basis of competition and the new waves of productivity growth. Hence, once you get familiar with the basics and implement the end-to-end big data use cases, you will start exploring the third module, Mastering Hadoop. So, now the question is if you need to broaden your Hadoop skill set to the next level after you nail the basics and the advance concepts, then this course is indispensable. When you finish this course, you will be able to tackle the real-world scenarios and become a big data expert using the tools and the knowledge based on the various step-by-step tutorials and recipes. Style and approach This course has covered everything right from the basic concepts of Hadoop till you master the advance mechanisms to become a big data expert. The goal here is to help you learn the basic essentials using the step-by-step tutorials and from there moving toward the recipes with various real-world solutions for you. It covers all the important aspects of Hadoop from system designing and configuring Hadoop, machine learning principles with various libraries with chapters illustrated with code fragments and schematic diagrams. This is a compendious course to explore Hadoop from the basics to the most advanced techniques available in Hadoop 2.X.