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Apache Hive
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Hive provides standard SQL functionality, including many of the later 2003 and 2011 features for analytics. HiveHive's SQL can also be extended with user code via User Defined Functions user defined functions (UDFs), user defined aggregates (UDAFs), and user defined table functions (UDTFs).
There is not a single "Hive format" in which data must be stored. Hive Hive comes with built in connectors for comma-separated values (CSV) text files, Apache ParquetTM, Apache ORCTM, and other formats. Users Users can extend Hive with connectors for other formats. Please Please see File Formats and Hive SerDe in the Developer Guide for details.
Hive is not designed for online transaction processing (OLTP) workloads. It is best used for traditional data warehousing tasks. Hive Hive is designed to maximize scalability (scale out with more machines added dynamically to the Hadoop cluster), performance, extensibility, fault-tolerance, and loose-coupling with its input formats.
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- How to Contribute
- Hive Contributors Meetings
- Hive Developer Docs
- Hive Testing Docs
- Hive Performance
- Hive Architecture Overview
- Hive Design Docs: Completed; In Progress; Proposed; Incomplete, Abandoned, Other
- Roadmap/Call to Add More Features
- Full-Text Search over All Hive Resources
- How to edit the website
- Becoming a Committer
- How to Commit
- How to Release
- Project Bylaws
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Apache Hive, Apache Hadoop, Apache HBase, Apache HDFS, Apache, the Apache feather logo, and the Apache Hive project logo are trademarks of The Apache Software Foundation.