Mastering Apache Hadoop

Mastering Apache Hadoop
Author: Cybellium Ltd
Publisher: Cybellium Ltd
Total Pages: 194
Release: 2023-09-26
Genre: Computers
ISBN:
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Unleash the Power of Big Data Processing with Apache Hadoop Ecosystem Are you ready to embark on a journey into the world of big data processing and analysis using Apache Hadoop? "Mastering Apache Hadoop" is your comprehensive guide to understanding and harnessing the capabilities of Hadoop for processing and managing massive datasets. Whether you're a data engineer seeking to optimize processing pipelines or a business analyst aiming to extract insights from large data, this book equips you with the knowledge and tools to master the art of Hadoop-based data processing. Key Features: 1. Deep Dive into Hadoop Ecosystem: Immerse yourself in the core components and concepts of the Apache Hadoop ecosystem. Understand the architecture, components, and functionalities that make Hadoop a powerful platform for big data. 2. Installation and Configuration: Master the art of installing and configuring Hadoop on various platforms. Learn about cluster setup, resource management, and configuration settings for optimal performance. 3. Hadoop Distributed File System (HDFS): Uncover the power of HDFS for distributed storage and data management. Explore concepts like replication, fault tolerance, and data placement to ensure data durability. 4. MapReduce and Data Processing: Delve into MapReduce, the core data processing paradigm in Hadoop. Learn how to write MapReduce jobs, optimize performance, and leverage parallel processing for efficient data analysis. 5. Data Ingestion and ETL: Discover techniques for ingesting and transforming data in Hadoop. Explore tools like Apache Sqoop and Apache Flume for extracting data from various sources and loading it into Hadoop. 6. Data Querying and Analysis: Master querying and analyzing data using Hadoop. Learn about Hive, Pig, and Spark SQL for querying structured and semi-structured data, and uncover insights that drive informed decisions. 7. Data Storage Formats: Explore data storage formats optimized for Hadoop. Learn about Avro, Parquet, and ORC, and understand how to choose the right format for efficient storage and retrieval. 8. Batch and Stream Processing: Uncover strategies for batch and real-time data processing in Hadoop. Learn how to use Apache Spark and Apache Flink to process data in both batch and streaming modes. 9. Data Visualization and Reporting: Discover techniques for visualizing and reporting on Hadoop data. Explore integration with tools like Apache Zeppelin and Tableau to create compelling visualizations. 10. Real-World Applications: Gain insights into real-world use cases of Apache Hadoop across industries. From financial analysis to social media sentiment analysis, explore how organizations are leveraging Hadoop's capabilities for data-driven innovation. Who This Book Is For: "Mastering Apache Hadoop" is an essential resource for data engineers, analysts, and IT professionals who want to excel in big data processing using Hadoop. Whether you're new to Hadoop or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of big data technology.

Apache Sqoop Cookbook

Apache Sqoop Cookbook
Author: Kathleen Ting
Publisher: "O'Reilly Media, Inc."
Total Pages: 125
Release: 2013-07-02
Genre: Computers
ISBN: 1449364586
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Integrating data from multiple sources is essential in the age of big data, but it can be a challenging and time-consuming task. This handy cookbook provides dozens of ready-to-use recipes for using Apache Sqoop, the command-line interface application that optimizes data transfers between relational databases and Hadoop. Sqoop is both powerful and bewildering, but with this cookbook’s problem-solution-discussion format, you’ll quickly learn how to deploy and then apply Sqoop in your environment. The authors provide MySQL, Oracle, and PostgreSQL database examples on GitHub that you can easily adapt for SQL Server, Netezza, Teradata, or other relational systems. Transfer data from a single database table into your Hadoop ecosystem Keep table data and Hadoop in sync by importing data incrementally Import data from more than one database table Customize transferred data by calling various database functions Export generated, processed, or backed-up data from Hadoop to your database Run Sqoop within Oozie, Hadoop’s specialized workflow scheduler Load data into Hadoop’s data warehouse (Hive) or database (HBase) Handle installation, connection, and syntax issues common to specific database vendors

Mastering Data Engineering: Advanced Techniques with Apache Hadoop and Hive

Mastering Data Engineering: Advanced Techniques with Apache Hadoop and Hive
Author: Peter Jones
Publisher: Walzone Press
Total Pages: 195
Release: 2024-10-19
Genre: Computers
ISBN:
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Immerse yourself in the realm of big data with "Mastering Data Engineering: Advanced Techniques with Apache Hadoop and Hive," your definitive guide to mastering two of the most potent technologies in the data engineering landscape. This book provides comprehensive insights into the complexities of Apache Hadoop and Hive, equipping you with the expertise to store, manage, and analyze vast amounts of data with precision. From setting up your initial Hadoop cluster to performing sophisticated data analytics with HiveQL, each chapter methodically builds on the previous one, ensuring a robust understanding of both fundamental concepts and advanced methodologies. Discover how to harness HDFS for scalable and reliable storage, utilize MapReduce for intricate data processing, and fully exploit data warehousing capabilities with Hive. Targeted at data engineers, analysts, and IT professionals striving to advance their proficiency in big data technologies, this book is an indispensable resource. Through a blend of theoretical insights, practical knowledge, and real-world examples, you will master data storage optimization, advanced Hive functionalities, and best practices for secure and efficient data management. Equip yourself to confront big data challenges with confidence and skill with "Mastering Data Engineering: Advanced Techniques with Apache Hadoop and Hive." Whether you're a novice in the field or seeking to expand your expertise, this book will be your invaluable guide on your data engineering journey.

Mastering Apache Spark

Mastering Apache Spark
Author: Cybellium Ltd
Publisher: Cybellium Ltd
Total Pages: 248
Release: 2023-09-26
Genre: Computers
ISBN:
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Unleash the Potential of Distributed Data Processing with Apache Spark Are you prepared to venture into the realm of distributed data processing and analytics with Apache Spark? "Mastering Apache Spark" is your comprehensive guide to unlocking the full potential of this powerful framework for big data processing. Whether you're a data engineer seeking to optimize data pipelines or a business analyst aiming to extract insights from massive datasets, this book equips you with the knowledge and tools to master the art of Spark-based data processing. Key Features: 1. Deep Dive into Apache Spark: Immerse yourself in the core principles of Apache Spark, comprehending its architecture, components, and versatile functionalities. Construct a robust foundation that empowers you to manage big data with precision. 2. Installation and Configuration: Master the art of installing and configuring Apache Spark across diverse platforms. Learn about cluster setup, resource allocation, and configuration tuning for optimal performance. 3. Spark Core and RDDs: Uncover the core of Spark—Resilient Distributed Datasets (RDDs). Explore the functional programming paradigm and leverage RDDs for efficient and fault-tolerant data processing. 4. Structured Data Processing with Spark SQL: Delve into Spark SQL for querying structured data with ease. Learn how to execute SQL queries, perform data manipulations, and tap into the power of DataFrames. 5. Streamlining Data Processing with Spark Streaming: Discover the power of real-time data processing with Spark Streaming. Learn how to handle continuous data streams and perform near-real-time analytics. 6. Machine Learning with MLlib: Master Spark's machine learning library, MLlib. Dive into algorithms for classification, regression, clustering, and recommendation, enabling you to develop sophisticated data-driven models. 7. Graph Processing with GraphX: Embark on a journey through graph processing with Spark's GraphX. Learn how to analyze and visualize graph data to glean insights from complex relationships. 8. Data Processing with Spark Structured Streaming: Explore the world of structured streaming in Spark. Learn how to process and analyze data streams with the declarative power of DataFrames. 9. Spark Ecosystem and Integrations: Navigate Spark's rich ecosystem of libraries and integrations. From data ingestion with Apache Kafka to interactive analytics with Apache Zeppelin, explore tools that enhance Spark's capabilities. 10. Real-World Applications: Gain insights into real-world use cases of Apache Spark across industries. From fraud detection to sentiment analysis, discover how organizations leverage Spark for data-driven innovation. Who This Book Is For: "Mastering Apache Spark" is a must-have resource for data engineers, analysts, and IT professionals poised to excel in the world of distributed data processing using Spark. Whether you're new to Spark or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of this transformative framework.

Mastering Apache Storm

Mastering Apache Storm
Author: Ankit Jain
Publisher: Packt Publishing Ltd
Total Pages: 276
Release: 2017-08-16
Genre: Computers
ISBN: 1787120406
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Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn Understand the core concepts of Apache Storm and real-time processing Follow the steps to deploy multiple nodes of Storm Cluster Create Trident topologies to support various message-processing semantics Make your cluster sharing effective using Storm scheduling Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You'll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we'll introduce you to Trident and you'll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.

Mastering Java Machine Learning

Mastering Java Machine Learning
Author: Dr. Uday Kamath
Publisher: Packt Publishing Ltd
Total Pages: 556
Release: 2017-07-11
Genre: Computers
ISBN: 1785888552
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Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects More than 15 open source Java tools in a wide range of techniques, with code and practical usage. More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. Apply machine learning to real-world data with methodologies, processes, applications, and analysis. Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Mastering Big Data

Mastering Big Data
Author: Cybellium Ltd
Publisher: Cybellium Ltd
Total Pages: 205
Release: 2023-09-06
Genre: Computers
ISBN:
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Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.

Mastering Data Integration

Mastering Data Integration
Author: Cybellium Ltd
Publisher: Cybellium Ltd
Total Pages: 186
Release:
Genre: Computers
ISBN:
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Unlock Seamless Data Flow Across Your Organization Are you prepared to revolutionize the way your organization handles data integration? "Mastering Data Integration" is your definitive guide to unlocking the potential of seamless and efficient data flow across diverse systems. Whether you're a data engineer seeking to optimize integration pipelines or a business leader aiming to harness data-driven insights, this book equips you with the knowledge and strategies to master the art of data integration.

Architecting Big Data: Mastering Hadoop Solution

Architecting Big Data: Mastering Hadoop Solution
Author:
Publisher: Anand Vemula
Total Pages: 166
Release:
Genre: Computers
ISBN:
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"Architecting Big Data: Mastering Hadoop Solutions Certification" is a comprehensive guide tailored for professionals seeking to become proficient in architecting Hadoop solutions for big data applications. Authored by industry experts with extensive experience in big data technologies and Hadoop ecosystems, this book offers a succinct yet thorough overview of the concepts, techniques, and best practices essential for success in this rapidly evolving field. The book begins by providing a solid foundation in big data fundamentals, covering topics such as data storage, processing frameworks, and distributed computing principles. It then delves into the intricacies of the Hadoop ecosystem, including HDFS (Hadoop Distributed File System), MapReduce, YARN (Yet Another Resource Negotiator), and various Hadoop ecosystem projects like Hive, Pig, and Spark. Through clear explanations and practical examples, readers gain a deep understanding of how these components work together to handle large volumes of data efficiently. One of the book's key strengths lies in its focus on architectural considerations. Readers learn how to design scalable, fault-tolerant, and high-performance Hadoop solutions that meet the unique requirements of their organizations. From data ingestion and storage to processing and analysis, the authors provide insights into designing robust architectures that optimize resource utilization and minimize latency. Moreover, the book addresses advanced topics such as data governance, security, and optimization techniques, ensuring that readers are well-equipped to address the complexities of real-world big data projects. Throughout the book, emphasis is placed on practical implementation, with hands-on exercises and case studies that reinforce learning and facilitate skill development. Whether you're a seasoned data professional looking to expand your expertise or a newcomer seeking to enter the field of big data architecture, "Architecting Big Data: Mastering Hadoop Solutions Certification" serves as an invaluable resource. By combining comprehensive coverage of Hadoop technologies with practical insights and expert guidance, this book equips readers with the knowledge and skills needed to excel as Hadoop solution architects in today's data-driven world.

Mastering Disruptive Technologies

Mastering Disruptive Technologies
Author: Dr. R. K. Dhanaraj
Publisher: HP Hamilton Limited, U.K.
Total Pages: 371
Release: 2021-04-30
Genre: Computers
ISBN: 1913936236
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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.