Download or read book HBase The Definitive Guide written by Lars George and published by "O'Reilly Media, Inc.". This book was released on 2011-08-29 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this book shows you how Apache HBase can fulfill your needs. As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Many IT executives are asking pointed questions about HBase. This book provides meaningful answers, whether you’re evaluating this non-relational database or planning to put it into practice right away. Discover how tight integration with Hadoop makes scalability with HBase easier Distribute large datasets across an inexpensive cluster of commodity servers Access HBase with native Java clients, or with gateway servers providing REST, Avro, or Thrift APIs Get details on HBase’s architecture, including the storage format, write-ahead log, background processes, and more Integrate HBase with Hadoop's MapReduce framework for massively parallelized data processing jobs Learn how to tune clusters, design schemas, copy tables, import bulk data, decommission nodes, and many other tasks

Download or read book Learning HBase written by Shashwat Shriparv and published by Packt Publishing Ltd. This book was released on 2014-11-25 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book HBase in Action written by Amandeep Khurana and published by Simon and Schuster. This book was released on 2012-11-01 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary HBase in Action has all the knowledge you need to design, build, and run applications using HBase. First, it introduces you to the fundamentals of distributed systems and large scale data handling. Then, you'll explore real-world applications and code samples with just enough theory to understand the practical techniques. You'll see how to build applications with HBase and take advantage of the MapReduce processing framework. And along the way you'll learn patterns and best practices. About the Technology HBase is a NoSQL storage system designed for fast, random access to large volumes of data. It runs on commodity hardware and scales smoothly from modest datasets to billions of rows and millions of columns. About this Book HBase in Action is an experience-driven guide that shows you how to design, build, and run applications using HBase. First, it introduces you to the fundamentals of handling big data. Then, you'll explore HBase with the help of real applications and code samples and with just enough theory to back up the practical techniques. You'll take advantage of the MapReduce processing framework and benefit from seeing HBase best practices in action. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside When and how to use HBase Practical examples Design patterns for scalable data systems Deployment, integration, and design Written for developers and architects familiar with data storage and processing. No prior knowledge of HBase, Hadoop, or MapReduce is required. Table of Contents PART 1 HBASE FUNDAMENTALS Introducing HBase Getting started Distributed HBase, HDFS, and MapReduce PART 2 ADVANCED CONCEPTS HBase table design Extending HBase with coprocessors Alternative HBase clients PART 3 EXAMPLE APPLICATIONS HBase by example: OpenTSDB Scaling GIS on HBase PART 4 OPERATIONALIZING HBASE Deploying HBase Operations

Download or read book Learning Hadoop 2 written by Garry Turkington and published by Packt Publishing Ltd. This book was released on 2015-02-13 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. You are expected to be familiar with the Unix/Linux command-line interface and have some experience with the Java programming language. Familiarity with Hadoop would be a plus.

Download or read book Big Data Forensics Learning Hadoop Investigations written by Joe Sremack and published by Packt Publishing Ltd. This book was released on 2015-09-24 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perform forensic investigations on Hadoop clusters with cutting-edge tools and techniques About This Book Identify, collect, and analyze Hadoop evidence forensically Learn about Hadoop's internals and Big Data file storage concepts A step-by-step guide to help you perform forensic analysis using freely available tools Who This Book Is For This book is meant for statisticians and forensic analysts with basic knowledge of digital forensics. They do not need to know Big Data Forensics. If you are an IT professional, law enforcement professional, legal professional, or a student interested in Big Data and forensics, this book is the perfect hands-on guide for learning how to conduct Hadoop forensic investigations. Each topic and step in the forensic process is described in accessible language. What You Will Learn Understand Hadoop internals and file storage Collect and analyze Hadoop forensic evidence Perform complex forensic analysis for fraud and other investigations Use state-of-the-art forensic tools Conduct interviews to identify Hadoop evidence Create compelling presentations of your forensic findings Understand how Big Data clusters operate Apply advanced forensic techniques in an investigation, including file carving, statistical analysis, and more In Detail Big Data forensics is an important type of digital investigation that involves the identification, collection, and analysis of large-scale Big Data systems. Hadoop is one of the most popular Big Data solutions, and forensically investigating a Hadoop cluster requires specialized tools and techniques. With the explosion of Big Data, forensic investigators need to be prepared to analyze the petabytes of data stored in Hadoop clusters. Understanding Hadoop's operational structure and performing forensic analysis with court-accepted tools and best practices will help you conduct a successful investigation. Discover how to perform a complete forensic investigation of large-scale Hadoop clusters using the same tools and techniques employed by forensic experts. This book begins by taking you through the process of forensic investigation and the pitfalls to avoid. It will walk you through Hadoop's internals and architecture, and you will discover what types of information Hadoop stores and how to access that data. You will learn to identify Big Data evidence using techniques to survey a live system and interview witnesses. After setting up your own Hadoop system, you will collect evidence using techniques such as forensic imaging and application-based extractions. You will analyze Hadoop evidence using advanced tools and techniques to uncover events and statistical information. Finally, data visualization and evidence presentation techniques are covered to help you properly communicate your findings to any audience. Style and approach This book is a complete guide that follows every step of the forensic analysis process in detail. You will be guided through each key topic and step necessary to perform an investigation. Hands-on exercises are presented throughout the book, and technical reference guides and sample documents are included for real-world use.

Download or read book Deep Learning with Hadoop written by Dipayan Dev and published by Packt Publishing Ltd. This book was released on 2017-02-20 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, implement and scale distributed deep learning models for large-scale datasets About This Book Get to grips with the deep learning concepts and set up Hadoop to put them to use Implement and parallelize deep learning models on Hadoop's YARN framework A comprehensive tutorial to distributed deep learning with Hadoop Who This Book Is For If you are a data scientist who wants to learn how to perform deep learning on Hadoop, this is the book for you. Knowledge of the basic machine learning concepts and some understanding of Hadoop is required to make the best use of this book. What You Will Learn Explore Deep Learning and various models associated with it Understand the challenges of implementing distributed deep learning with Hadoop and how to overcome it Implement Convolutional Neural Network (CNN) with deeplearning4j Delve into the implementation of Restricted Boltzmann Machines (RBM) Understand the mathematical explanation for implementing Recurrent Neural Networks (RNN) Get hands on practice of deep learning and their implementation with Hadoop. In Detail This book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop for optimal performance. Starting with understanding what deep learning is, and what the various models associated with deep neural networks are, this book will then show you how to set up the Hadoop environment for deep learning. In this book, you will also learn how to overcome the challenges that you face while implementing distributed deep learning with large-scale unstructured datasets. The book will also show you how you can implement and parallelize the widely used deep learning models such as Deep Belief Networks, Convolutional Neural Networks, Recurrent Neural Networks, Restricted Boltzmann Machines and autoencoder using the popular deep learning library deeplearning4j. Get in-depth mathematical explanations and visual representations to help you understand the design and implementations of Recurrent Neural network and Denoising AutoEncoders with deeplearning4j. To give you a more practical perspective, the book will also teach you the implementation of large-scale video processing, image processing and natural language processing on Hadoop. By the end of this book, you will know how to deploy various deep neural networks in distributed systems using Hadoop. Style and approach This book takes a comprehensive, step-by-step approach to implement efficient deep learning models on Hadoop. It starts from the basics and builds the readers' knowledge as they strengthen their understanding of the concepts. Practical examples are included in every step of the way to supplement the theory.

Download or read book Architecting HBase Applications written by Jean-Marc Spaggiari and published by "O'Reilly Media, Inc.". This book was released on 2016-07-18 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lots of HBase books, online HBase guides, and HBase mailing lists/forums are available if you need to know how HBase works. But if you want to take a deep dive into use cases, features, and troubleshooting, Architecting HBase Applications is the right source for you. With this book, you'll learn a controlled set of APIs that coincide with use-case examples and easily deployed use-case models, as well as sizing/best practices to help jump start your enterprise application development and deployment.

Download or read book Hbase Administration Cookbook written by Yifeng Jiang and published by Packt Publishing Ltd. This book was released on 2012-08-16 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of Packt's cookbook series, each recipe offers a practical, step-by-step solution to common problems found in HBase administration. This book is for HBase administrators, developers, and will even help Hadoop administrators. You are not required to have HBase experience, but are expected to have a basic understanding of Hadoop and MapReduce.

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

Download or read book Learn Hbase in 24 Hours written by Alex Nordeen and published by Guru99. This book was released on 2020-09-15 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: HBase data storage technology is rapidly adopted by traditional RDMS users. Unlike RDMS, where scaling the server vertically for a huge data is a big challenge. With HBase, you can do this easily. It allows you to integrate with Hadoop's MapReduce framework for massively parallelized data processing jobs. Many expert and beginners are asking for a point-to-point guide that helps them to get a complete insight on HBase working. This book will answer all their queries and give them a complete tour of HBase technology. In this edition, you will begin with some very basic concept like HBase’s architecture, including the storage format, write-ahead log, background processes, and some of the advance topics. You will also learn about accessing HBase with native Java clients, how to tune clusters, design schemas, copy tables, etc. So far if tracking other resources for HBase have disappointed you, you must try this e-book. It is cheap, easy to comprehend and concise in its content. The examples and images are an additional benefit of this book. While to enhance your knowledge pool for related topics, more referrals and links are provided. Table Of Contents Chapter 1: Introduction Chapter 2: Architecture, Data Flow, and Use cases Storage Mechanism in Hbase HBase Architecture and its Important Components Data flow in HBase HBASE vs. HDFS Chapter 3: Installation Guide How to Download Hbase tar file stable version Hbase - Standalone mode installation Hbase - Pseudo Distributed mode of installation Hbase - Fully Distributed mode installation Chapter 4: Shell and General Commands General commands Tables Managements commands Data manipulation commands Cluster Replication Commands Chapter 5: Handling Tables Creation of Table with Rows and Column names Placing values into tables and retrieving values from table Retrieving Inserted Values in HBase shell mode Chapter 6: Limitations, Advantage & Problems Chapter 7: Troubleshooting

Download or read book HBase High Performance Cookbook written by Ruchir Choudhry and published by Packt Publishing Ltd. This book was released on 2017-01-31 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exciting projects that will teach you how complex data can be exploited to gain maximum insights About This Book Architect a good HBase cluster for a very large distributed system Get to grips with the concepts of performance tuning with HBase A practical guide full of engaging recipes and attractive screenshots to enhance your system's performance Who This Book Is For This book is intended for developers and architects who want to know all about HBase at a hands-on level. This book is also for big data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic scalable database solution in the big data space. What You Will Learn Configure HBase from a high performance perspective Grab data from various RDBMS/Flat files into the HBASE systems Understand table design and perform CRUD operations Find out how the communication between the client and server happens in HBase Grasp when to use and avoid MapReduce and how to perform various tasks with it Get to know the concepts of scaling with HBase through practical examples Set up Hbase in the Cloud for a small scale environment Integrate HBase with other tools including ElasticSearch In Detail Apache HBase is a non-relational NoSQL database management system that runs on top of HDFS. It is an open source, disturbed, versioned, column-oriented store and is written in Java to provide random real-time access to big Data. We'll start off by ensuring you have a solid understanding the basics of HBase, followed by giving you a thorough explanation of architecting a HBase cluster as per our project specifications. Next, we will explore the scalable structure of tables and we will be able to communicate with the HBase client. After this, we'll show you the intricacies of MapReduce and the art of performance tuning with HBase. Following this, we'll explain the concepts pertaining to scaling with HBase. Finally, you will get an understanding of how to integrate HBase with other tools such as ElasticSearch. By the end of this book, you will have learned enough to exploit HBase for boost system performance. Style and approach This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications. This books also provides examples for C#, Python, and Ruby users.

Download or read book Computer Science and Education written by Wenxing Hong and published by Springer Nature. This book was released on 2023-06-16 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set constitues selected papers presented during the 17th International Conference on Computer Science and Education, ICCSE 2022, held in Ningbo, China, in August 2022. The 168 full papers and 43 short papers presented were thoroughly reviewed and selected from the 510 submissions. They focus on a wide range of computer science topics, especially AI, data science, and engineering, and technology-based education, by addressing frontier technical and business issues essential to the applications of data science in both higher education and advancing e-Society.

Download or read book Exploring Hadoop Tools on Windows 10 Platform written by Dr. Poornima G. Naik and published by Shashwat Publication. This book was released on 2023-02-23 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is precisely organized into five chapters. Each chapter has been carefully developed with the help of several implemented commands. Dedicated efforts have been put in to ensure that every concept of Hadoop tools discussed in this book is explained with help of relevant commands and screenshots of the outputs have been included. Chapter-1 includes details of Installing Hadoop on Windows 10, with prerequisites required. A step by step detail process of downloading is explained along with Configuring Hadoop Cluster, HDFS Site Configuration, Hadoop Web UI, HDFS Commands etc . Chapter-2 describes Installation Pig on Windows 10. Apache Pig is a platform build on the top of Hadoop. It explores Hands on Sessions with Apache Pig focusing on Loading Data into Pig Relation and Operators in Pig. Chapter-3 talks about Installing Sqoop on Windows 10. It also demonstrates Installing MySQL Workbench, Exporting and importing Data Using Sqoop. Chapter-4 explores Installation of HBase on Windows 10 along with Testing HBase Installation and different HBase Commands. Chapter-5 the last chapter of the book entitled ‘Installing Hive On Windows 10’, includes Installing Apache Derby, Cygwin Tool, downloading Apache Hive binaries, Initializing Hive Metastore etc.

Download or read book Data Analytics with Hadoop written by Benjamin Bengfort and published by "O'Reilly Media, Inc.". This book was released on 2016-06 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

Download or read book Pro Hadoop Data Analytics written by Kerry Koitzsch and published by Apress. This book was released on 2016-12-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn advanced analytical techniques and leverage existing tool kits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems that go beyond the basics of classification, clustering, and recommendation. Pro Hadoop Data Analytics emphasizes best practices to ensure coherent, efficient development. A complete example system will be developed using standard third-party components that consist of the tool kits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system. The book also highlights the importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. You'll discover the importance of mix-and-match or hybrid systems, using different analytical components in one application. This hybrid approach will be prominent in the examples. What You'll Learn Build big data analytic systems with the Hadoop ecosystem Use libraries, tool kits, and algorithms to make development easier and more effective Apply metrics to measure performance and efficiency of components and systems Connect to standard relational databases, noSQL data sources, and more Follow case studies with example components to create your own systems Who This Book Is For Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.

Download or read book Hadoop Essentials written by Shiva Achari and published by Packt Publishing Ltd. This book was released on 2015-04-29 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. This book is also meant for Hadoop professionals who want to find solutions to the different challenges they come across in their Hadoop projects.

Download or read book Hadoop Real World Solutions Cookbook written by Tanmay Deshpande and published by Packt Publishing Ltd. This book was released on 2016-03-31 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout About This Book Implement outstanding Machine Learning use cases on your own analytics models and processes. Solutions to common problems when working with the Hadoop ecosystem. Step-by-step implementation of end-to-end big data use cases. Who This Book Is For Readers who have a basic knowledge of big data systems and want to advance their knowledge with hands-on recipes. What You Will Learn Installing and maintaining Hadoop 2.X cluster and its ecosystem. Write advanced Map Reduce programs and understand design patterns. Advanced Data Analysis using the Hive, Pig, and Map Reduce programs. Import and export data from various sources using Sqoop and Flume. Data storage in various file formats such as Text, Sequential, Parquet, ORC, and RC Files. Machine learning principles with libraries such as Mahout Batch and Stream data processing using Apache Spark In Detail Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business. Style and approach An easy-to-follow guide that walks you through world of big data. Each tool in the Hadoop ecosystem is explained in detail and the recipes are placed in such a manner that readers can implement them sequentially. Plenty of reference links are provided for advanced reading.