Mastering Apache Hbase
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| Author | : Cybellium Ltd |
| Publisher | : Cybellium Ltd |
| Total Pages | : 345 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
Unlock the Power of Scalable and Distributed Data Storage with "Mastering Apache HBase" In the rapidly evolving landscape of data management, the ability to efficiently handle massive amounts of data has become an indispensable skill. "Mastering Apache HBase" serves as your definitive guide to mastering one of the most powerful and flexible distributed NoSQL databases – Apache HBase. Whether you're a seasoned data professional or a newcomer to the world of big data, this book equips you with the knowledge and skills needed to harness the full potential of Apache HBase. About the Book: "Mastering Apache HBase" takes you on a comprehensive journey through the intricacies of this robust and versatile NoSQL database. From the fundamentals of installation and configuration to advanced topics such as performance tuning and integration with other Big Data tools, this book covers it all. Each chapter is meticulously crafted to provide a deep understanding of the concepts along with practical, real-world applications. Key Features: · Solid Foundation: Build a strong understanding by exploring the core concepts of Apache HBase, including its architecture, data model, and storage components. · Efficient Data Management: Learn how to create tables, insert and retrieve data, and implement effective data modeling strategies that maximize performance and flexibility. · Scalability and Distribution: Dive into the distributed nature of Apache HBase and discover techniques to scale your cluster horizontally, ensuring seamless growth as your data needs expand. · Advanced Techniques: Master advanced topics such as data versioning, coprocessors, security, and backup and recovery, enabling you to tackle complex scenarios with confidence. · Performance Optimization: Uncover strategies and best practices for optimizing the performance of your Apache HBase cluster, ensuring your applications run smoothly even at scale. · Integration with Ecosystem: Explore how Apache HBase seamlessly integrates with other Big Data tools like Apache Hadoop, Apache Spark, and Apache Hive, opening up possibilities for data analysis and processing. · Real-World Use Cases: Learn through practical examples and use cases from various industries, including social media, e-commerce, finance, and more, to understand how Apache HBase can solve real-world data challenges. · Expert Insights: Benefit from the experience of seasoned professionals who provide insights, tips, and recommendations garnered from their years of working with Apache HBase. Who This Book Is For: "Mastering Apache HBase" is designed for data engineers, database administrators, and anyone involved in managing and analyzing large volumes of data. Whether you're a developer looking to expand your skillset or an experienced professional aiming to deepen your understanding of distributed data storage, this book is your ultimate resource. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
| Author | : Cybellium Ltd |
| Publisher | : Cybellium Ltd |
| Total Pages | : 194 |
| Release | : 2023-09-26 |
| Genre | : Computers |
| ISBN | : |
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.
| Author | : Ankit Jain |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 276 |
| Release | : 2017-08-16 |
| Genre | : Computers |
| ISBN | : 1787120406 |
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.
| Author | : Cybellium Ltd |
| Publisher | : Cybellium Ltd |
| Total Pages | : 248 |
| Release | : 2023-09-26 |
| Genre | : Computers |
| ISBN | : |
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.
| Author | : Peter Jones |
| Publisher | : Walzone Press |
| Total Pages | : 195 |
| Release | : 2024-10-19 |
| Genre | : Computers |
| ISBN | : |
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.
| Author | : Chanchal Singh |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 531 |
| Release | : 2019-02-28 |
| Genre | : Computers |
| ISBN | : 1788628322 |
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.
| Author | : Sherwin John C. Tragura |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 494 |
| Release | : 2024-08-16 |
| Genre | : Computers |
| ISBN | : 1837638578 |
Discover how to construct API and web components, build enterprise-grade applications, design and implement unit and behavioral testing, and plan deployment strategies for scalable Flask 3 applications Key Features Implement web and API applications using both standard and asynchronous Flask components Improve your dev experience with signals, route decorators, async/await design patterns, context managers, and nested blueprints Tie all the features together in each chapter through practical, relatable applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionFlask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web and API Development will take you on an exhaustive tour of the Flask environment and teach you how to build a production-ready application. You’ll start by installing Flask and grasping fundamental concepts, such as MVC and ORM database access. Next, you’ll master structuring applications for scalability through Flask blueprints. As you progress, you’ll explore both SQL and NoSQL databases while creating REST APIs and implementing JWT authentication, and improve your skills in role-based access security, utilizing LDAP, OAuth, OpenID, and databases. The new project structure, managed by context managers, as well as ASGI support, has revolutionized Flask, and you’ll get to grips with these crucial upgrades. You'll also explore out-of-the-box integrations with technologies, such as RabbitMQ, Celery, NoSQL databases, PostgreSQL, and various external modules. The concluding chapters discuss enterprise-related challenges where Flask proves its mettle as a core solution. By the end of this book, you’ll be well-versed with Flask, seeing it not only as a lightweight web and API framework, but also as a potent problem-solving tool in your daily work, addressing integration and enterprise issues alongside Django and FastAPI.What you will learn Prepare, set up, and configure development environments for both API and web applications Explore built-in serializers and encoders that processes request and response data Solve big data issues by integrating Flask applications with NoSQL databases Apply various ORM and ODM techniques to build model and repository layers Integrate with OpenAPI, Circuit Breaker, ZooKeeper, and OpenTracing to build scalable API applications Use Flask middleware to provide CRUD transactions for Flutter-based mobile applications Who this book is for This book is for proficient Python developers seeking a deeper understanding of the Flask framework as a solution for tackling enterprise challenges. It is also a great resource for Flask-savvy readers eager to learn more about the framework’s advanced capabilities and new features.
| Author | : |
| Publisher | : Anand Vemula |
| Total Pages | : 166 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
"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.
| Author | : Charles Givre |
| Publisher | : O'Reilly Media |
| Total Pages | : 331 |
| Release | : 2018-11-02 |
| Genre | : Computers |
| ISBN | : 1492032778 |
Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as HBase, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster. In this practical book, Drill committers Charles Givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you’ll learn how Drill helps you analyze data more effectively to drive down time to insight. Use Drill to clean, prepare, and summarize delimited data for further analysis Query file types including logfiles, Parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL Connect to Drill programmatically using a variety of languages Use Drill even with challenging or ambiguous file formats Perform sophisticated analysis by extending Drill’s functionality with user-defined functions Facilitate data analysis for network security, image metadata, and machine learning
| Author | : Shashwat Shriparv |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 516 |
| Release | : 2014-11-25 |
| Genre | : Computers |
| ISBN | : 178398595X |
If you are an administrator or developer who wants to enter the world of Big Data and BigTables and would like to learn about HBase, this is the book for you.
