Hbase The Definitive Guide
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Hbase The Definitive Guide
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Author : Lars George
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2011-08-29
Hbase The Definitive Guide written by Lars George and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-29 with Computers categories.
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
Hbase The Definitive Guide
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Author : Lars George
language : en
Publisher: O'Reilly Media
Release Date : 2020-07-05
Hbase The Definitive Guide written by Lars George and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-05 with Computers categories.
If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this updated edition shows you how Apache HBase can meet your needs. Modeled after Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Fully revised for HBase 1.0, this second edition brings you up to speed on the new HBase client API, as well as security features and new case studies that demonstrate HBase use in the real world. Whether you just started to evaluate this non-relational database, or plan to put it into practice right away, this book has your back. Launch into basic, advanced, and administrative features of HBase's new client-facing API Use new classes to integrate HBase with Hadoop's MapReduce framework Explore HBase's architecture, including the storage format, write-ahead log, and background processes Dive into advanced usage, such extended client and server options Learn cluster sizing, tuning, and monitoring best practices Design schemas, copy tables, import bulk data, decommission nodes, and other tasks Go deeper into HBase security, including Kerberos and encryption at rest
Hbase
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Author : Lars George
language : en
Publisher:
Release Date : 2017
Hbase written by Lars George and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Big data categories.
With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters as they're written, and the final ebook bundle. If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this updated edition shows you how Apache HBase can meet your needs. Modeled after Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Fully revised for HBase 1.0, this second edition brings you up to speed on the new HBase client API, as well as security features and new case studies that demonstrate HBase use in the real world. Whether you just started to evaluate this non-relational database, or plan to put it into practice right away, this book has your back. Launch into basic, advanced, and administrative features of HBase's new client-facing API Use new classes to integrate HBase with Hadoop's MapReduce framework Explore HBase's architecture, including the storage format, write-ahead log, and background processes Dive into advanced usage, such extended client and server options Learn cluster sizing, tuning, and monitoring best practices Design schemas, copy tables, import bulk data, decommission nodes, and other tasks Go deeper into HBase security, including Kerberos and encryption at rest.
Hadoop The Definitive Guide
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Author : Tom White
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-05-10
Hadoop The Definitive Guide written by Tom White and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-10 with Computers categories.
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
Architecting Hbase Applications
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Author : Jean-Marc Spaggiari
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-07-18
Architecting Hbase Applications written by Jean-Marc Spaggiari and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-18 with Computers categories.
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.
Practical Hadoop Ecosystem
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Author : Deepak Vohra
language : en
Publisher: Apress
Release Date : 2016-09-30
Practical Hadoop Ecosystem written by Deepak Vohra and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Computers categories.
Learn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.
Learn Hbase In 1 Day
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Author : Krishna Rungta
language : en
Publisher:
Release Date : 2017-06-28
Learn Hbase In 1 Day written by Krishna Rungta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-28 with categories.
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 content 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
Hadoop The Definitive Guide
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Author : Tom White
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2010-09-24
Hadoop The Definitive Guide written by Tom White and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-24 with Computers categories.
Discover how Apache Hadoop can unleash the power of your data. This comprehensive resource shows you how to build and maintain reliable, scalable, distributed systems with the Hadoop framework -- an open source implementation of MapReduce, the algorithm on which Google built its empire. Programmers will find details for analyzing datasets of any size, and administrators will learn how to set up and run Hadoop clusters. This revised edition covers recent changes to Hadoop, including new features such as Hive, Sqoop, and Avro. It also provides illuminating case studies that illustrate how Hadoop is used to solve specific problems. Looking to get the most out of your data? This is your book. Use the Hadoop Distributed File System (HDFS) for storing large datasets, then run distributed computations over those datasets with MapReduce Become familiar with Hadoop’s data and I/O building blocks for compression, data integrity, serialization, 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 Use Pig, a high-level query language for large-scale data processing Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase, Hadoop’s database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems "Now you have the opportunity to learn about Hadoop from a master -- not only of the technology, but also of common sense and plain talk." --Doug Cutting, Cloudera
Cassandra The Definitive Guide
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Author : Jeff Carpenter
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-06-29
Cassandra The Definitive Guide written by Jeff Carpenter and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-29 with Computers categories.
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s non-relational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra on site, in the Cloud, or with Docker Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene
Seven Databases In Seven Weeks
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Author : Luc Perkins
language : en
Publisher: Pragmatic Bookshelf
Release Date : 2018-04-05
Seven Databases In Seven Weeks written by Luc Perkins and has been published by Pragmatic Bookshelf this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-05 with Computers categories.
Data is getting bigger and more complex by the day, and so are your choices in handling it. Explore some of the most cutting-edge databases available - from a traditional relational database to newer NoSQL approaches - and make informed decisions about challenging data storage problems. This is the only comprehensive guide to the world of NoSQL databases, with in-depth practical and conceptual introductions to seven different technologies: Redis, Neo4J, CouchDB, MongoDB, HBase, Postgres, and DynamoDB. This second edition includes a new chapter on DynamoDB and updated content for each chapter. While relational databases such as MySQL remain as relevant as ever, the alternative, NoSQL paradigm has opened up new horizons in performance and scalability and changed the way we approach data-centric problems. This book presents the essential concepts behind each database alongside hands-on examples that make each technology come alive. With each database, tackle a real-world problem that highlights the concepts and features that make it shine. Along the way, explore five database models - relational, key/value, columnar, document, and graph - from the perspective of challenges faced by real applications. Learn how MongoDB and CouchDB are strikingly different, make your applications faster with Redis and more connected with Neo4J, build a cluster of HBase servers using cloud services such as Amazon's Elastic MapReduce, and more. This new edition brings a brand new chapter on DynamoDB, updated code samples and exercises, and a more up-to-date account of each database's feature set. Whether you're a programmer building the next big thing, a data scientist seeking solutions to thorny problems, or a technology enthusiast venturing into new territory, you will find something to inspire you in this book. What You Need: You'll need a *nix shell (Mac OS or Linux preferred, Windows users will need Cygwin), Java 6 (or greater), and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.