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Programming Hive
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- Nombre de pages350
- FormatMulti-format
- ISBN978-1-4493-2696-8
- EAN9781449326968
- Date de parution19/09/2012
- Protection num.NC
- Infos supplémentairesMulti-format incluant PDF sans p...
- ÉditeurO'Reilly Media
Résumé
Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop's data warehouse infrastructure. You'll quickly learn how to use Hive's SQL dialect-HiveQL-to summarize, query, and analyze large datasets stored in Hadoop's distributed filesystem.
This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem.
You'll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. - Use Hive to create, alter, and drop databases, tables, views, functions, and indexes - Customize data formats and storage options, from files to external databases - Load and extract data from tables-and use queries, grouping, filtering, joining, and other conventional query methods - Gain best practices for creating user defined functions (UDFs) - Learn Hive patterns you should use and anti-patterns you should avoid - Integrate Hive with other data processing programs - Use storage handlers for NoSQL databases and other datastores - Learn the pros and cons of running Hive on Amazon's Elastic MapReduce
You'll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. - Use Hive to create, alter, and drop databases, tables, views, functions, and indexes - Customize data formats and storage options, from files to external databases - Load and extract data from tables-and use queries, grouping, filtering, joining, and other conventional query methods - Gain best practices for creating user defined functions (UDFs) - Learn Hive patterns you should use and anti-patterns you should avoid - Integrate Hive with other data processing programs - Use storage handlers for NoSQL databases and other datastores - Learn the pros and cons of running Hive on Amazon's Elastic MapReduce
Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop's data warehouse infrastructure. You'll quickly learn how to use Hive's SQL dialect-HiveQL-to summarize, query, and analyze large datasets stored in Hadoop's distributed filesystem.
This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem.
You'll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. - Use Hive to create, alter, and drop databases, tables, views, functions, and indexes - Customize data formats and storage options, from files to external databases - Load and extract data from tables-and use queries, grouping, filtering, joining, and other conventional query methods - Gain best practices for creating user defined functions (UDFs) - Learn Hive patterns you should use and anti-patterns you should avoid - Integrate Hive with other data processing programs - Use storage handlers for NoSQL databases and other datastores - Learn the pros and cons of running Hive on Amazon's Elastic MapReduce
You'll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. - Use Hive to create, alter, and drop databases, tables, views, functions, and indexes - Customize data formats and storage options, from files to external databases - Load and extract data from tables-and use queries, grouping, filtering, joining, and other conventional query methods - Gain best practices for creating user defined functions (UDFs) - Learn Hive patterns you should use and anti-patterns you should avoid - Integrate Hive with other data processing programs - Use storage handlers for NoSQL databases and other datastores - Learn the pros and cons of running Hive on Amazon's Elastic MapReduce
A propos de Dean Wampler
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