HBase Essentials : a practical guide to realizing the seamless potential of storing and managing high-volume, high-velocity data quickly and painlessly with HBase /

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. Thi...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Garg, Nishant (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, U.K. : Packt Publishing, 2014.
Colección:Community experience distilled.
Temas:
Database design > Computer programs.
Data structures (Computer science)
Database management.
Bases de données > Conception > Logiciels.
Structures de données (Informatique)
Bases de données > Gestion.
Database management
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • 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
  • 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
  • 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
  • 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
  • JVM tuningOther recommendations; Troubleshooting; Summary; Index

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