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|a 1783987251
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|a 9781783987252
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|a 1783987243
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|a QA76.9.D26
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100 |
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|a Garg, Nishant
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245 |
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|a HBase Essentials
|b a practical guide to realizing the seamless potential of storing and managing high-volume, high-velocity data quickly and painlessly with HBase
|c Nishant Garg
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|a Practical guide to realizing the seamless potential of storing and managing high-volume, high-velocity data quickly and painlessly with HBase
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260 |
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|a Birmingham, U.K.
|b Packt Publishing
|c 2014
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300 |
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|a 1 volume
|b illustrations
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505 |
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|a The Thrift clientGetting started; The Hadoop ecosystem client; Hive; Summary; Chapter 7: HBase Administration; Cluster management; The Start/stop HBase cluster; Adding nodes; Decommissioning a node; Upgrading a cluster; HBase cluster consistency; HBase data import/export tools; Copy table; Cluster monitoring; The HBase metrics framework; Master server metrics; Region server metrics; JVM metrics; Info metrics; Ganglia; Nagios; JMX; File-based monitoring; Performance tuning; Compression; Available codecs; Load balancing; Splitting regions; Merging regions; MemStore-local allocation buffer
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|a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introducing HBase; The world of Big Data; The origin of HBase; The use cases of HBase; Installing HBase; Installing Java 1.7; The local mode; The pseudo-distributed mode; The fully distributed mode; Understanding HBase cluster components; Start playing; Summary; Chapter 2: Defining the Schema; Data modeling in HBase; Designing tables; Accessing HBase; Establishing a connection; CRUD operations; Writing data; Reading data; Updating data; Deleting data; Summary
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505 |
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|a Chapter 3: Advanced Data ModelingUnderstanding keys; HBase table scans; Implementing filters; Utility filters; Comparison filters; Custom filters; Summary; Chapter 4: The HBase Architecture; Data storage; HLog (the write-ahead log -- WAL); HFile (the real data storage file); Data replication; Securing HBase; Enabling authentication; Enabling authorization; Configuring REST Clients; HBase and MapReduce; Hadoop MapReduce; Running MapReduce over HBase; HBase as a data source; HBase as a data sink; HBase as a data source and sink; Summary; Chapter 5: The HBase Advanced API; Counters
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|a JVM tuningOther recommendations; Troubleshooting; Summary; Index
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505 |
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|a Single countersMultiple counters; Coprocessors; The observer coprocessor; The endpoint coprocessor; The administrative API; The data definition API; Table name methods; Column family methods; Other methods; The HBaseAdmin API; Summary; Chapter 6: HBase Clients; The HBase shell; Data definition commands; Data manipulation commands; Data-handling tools; Kundera -- object mapper; CRUD using Kundera; Query HBase using Kundera; Using filters within query; REST client; Getting started; The plain format; The XML format; The JSON format (defined as a key-value pair); The REST Java client
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653 |
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|a Bases de données / Gestion
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653 |
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|a Bases de données / Conception / Logiciels
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653 |
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|a Data structures (Computer science) / http://id.loc.gov/authorities/subjects/sh85035862
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653 |
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|a Database design / Computer programs
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653 |
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|a Data structures (Computer science) / fast
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653 |
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|a Database management / http://id.loc.gov/authorities/subjects/sh85035848
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653 |
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|a Structures de données (Informatique)
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653 |
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|a Database management / fast
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|a eng
|2 ISO 639-2
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989 |
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|b OREILLY
|a O'Reilly
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490 |
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|a Community experience distilled
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500 |
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|a Includes index
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776 |
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|z 9781783987245
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856 |
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|u https://learning.oreilly.com/library/view/~/9781783987245/?ar
|x Verlag
|3 Volltext
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|a 658
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|a 500
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|a 745.4
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|a 005.74
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|a This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. 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
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