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Apache ORC

Apache ORC (Optimized Row Columnar) is a free and open-source column-oriented data storage format.[3] It is similar to the other columnar-storage file formats available in the Hadoop ecosystem such as RCFile and Parquet. It is used by most of the data processing frameworks Apache Spark, Apache Hive, Apache Flink and Apache Hadoop.

Apache ORC
Initial release20 February 2013; 9 years ago (2013-02-20)[1]
Stable release
1.8.0 / 3 September 2022; 4 months ago (2022-09-03)[2]
RepositoryORC Repository
Operating systemCross-platform
TypeDatabase management system
LicenseApache License 2.0
Websiteorc.apache.org

In February 2013, the Optimized Row Columnar (ORC) file format was announced by Hortonworks in collaboration with Facebook.[4] A month later, the Apache Parquet format was announced, developed by Cloudera and Twitter.[5]

History

Version Original release date Latest version Release date
Old version, no longer maintained: 1.0 2016-01-25 1.0.0 2016-01-25
Old version, no longer maintained: 1.1 2016-06-10 1.1.2 2016-07-08
Old version, no longer maintained: 1.2 2016-08-25 1.2.3 2016-12-12
Old version, no longer maintained: 1.3 2017-01-23 1.3.4 2017-10-16
Old version, no longer maintained: 1.4 2017-05-08 1.4.5 2019-12-09
Old version, no longer maintained: 1.5 2018-05-14 1.5.13 2021-09-15
Older version, yet still maintained: 1.6 2019-09-03 1.6.14 2022-04-14
Current stable version: 1.7 2021-09-15 1.7.4 2022-04-15
Legend:
Old version
Older version, still maintained
Latest version
Latest preview version
Future release

See also

References

  1. ^ "The Stinger Initiative: Making Apache Hive 100 Times Faster". Retrieved Jan 1, 2019.
  2. ^ "Apache ORC - Releases". Retrieved 27 September 2022.
  3. ^ Yin Huai, Siyuan Ma, Rubao Lee, Owen O'Malley, and Xiaodong Zhang (2013). "Understanding Insights into the Basic Structure and Essential Issues of Table Placement Methods in Clusters " (PDF). VLDB' 39. pp. 1750–1761.{{cite conference}}: CS1 maint: multiple names: authors list (link)
  4. ^ Alan Gates (February 20, 2013). "The Stinger Initiative: Making Apache Hive 100 Times Faster". Hortonworks blog. Retrieved Dec 31, 2018.
  5. ^ Justin Kestelyn (March 13, 2013). . Cloudera blog. Archived from the original on September 19, 2016. Retrieved May 4, 2017.

apache, this, article, multiple, issues, please, help, improve, discuss, these, issues, talk, page, learn, when, remove, these, template, messages, topic, this, article, meet, wikipedia, notability, guidelines, products, services, please, help, demonstrate, no. This article has multiple issues Please help improve it or discuss these issues on the talk page Learn how and when to remove these template messages The topic of this article may not meet Wikipedia s notability guidelines for products and services Please help to demonstrate the notability of the topic by citing reliable secondary sources that are independent of the topic and provide significant coverage of it beyond a mere trivial mention If notability cannot be shown the article is likely to be merged redirected or deleted Find sources Apache ORC news newspapers books scholar JSTOR February 2019 Learn how and when to remove this template message This article may rely excessively on sources too closely associated with the subject potentially preventing the article from being verifiable and neutral Please help improve it by replacing them with more appropriate citations to reliable independent third party sources February 2019 Learn how and when to remove this template message Learn how and when to remove this template message Apache ORC Optimized Row Columnar is a free and open source column oriented data storage format 3 It is similar to the other columnar storage file formats available in the Hadoop ecosystem such as RCFile and Parquet It is used by most of the data processing frameworks Apache Spark Apache Hive Apache Flink and Apache Hadoop Apache ORCInitial release20 February 2013 9 years ago 2013 02 20 1 Stable release1 8 0 3 September 2022 4 months ago 2022 09 03 2 RepositoryORC RepositoryOperating systemCross platformTypeDatabase management systemLicenseApache License 2 0Websiteorc wbr apache wbr orgIn February 2013 the Optimized Row Columnar ORC file format was announced by Hortonworks in collaboration with Facebook 4 A month later the Apache Parquet format was announced developed by Cloudera and Twitter 5 History EditVersion Original release date Latest version Release dateOld version no longer maintained 1 0 2016 01 25 1 0 0 2016 01 25Old version no longer maintained 1 1 2016 06 10 1 1 2 2016 07 08Old version no longer maintained 1 2 2016 08 25 1 2 3 2016 12 12Old version no longer maintained 1 3 2017 01 23 1 3 4 2017 10 16Old version no longer maintained 1 4 2017 05 08 1 4 5 2019 12 09Old version no longer maintained 1 5 2018 05 14 1 5 13 2021 09 15Older version yet still maintained 1 6 2019 09 03 1 6 14 2022 04 14Current stable version 1 7 2021 09 15 1 7 4 2022 04 15Legend Old versionOlder version still maintainedLatest versionLatest preview versionFuture releaseSee also Edit Free and open source software portalApache Spark Apache Arrow Apache Hive Apache NiFi Pig programming tool Trino SQL query engine Presto SQL query engine References Edit The Stinger Initiative Making Apache Hive 100 Times Faster Retrieved Jan 1 2019 Apache ORC Releases Retrieved 27 September 2022 Yin Huai Siyuan Ma Rubao Lee Owen O Malley and Xiaodong Zhang 2013 Understanding Insights into the Basic Structure and Essential Issues of Table Placement Methods in Clusters PDF VLDB 39 pp 1750 1761 a href Template Cite conference html title Template Cite conference cite conference a CS1 maint multiple names authors list link Alan Gates February 20 2013 The Stinger Initiative Making Apache Hive 100 Times Faster Hortonworks blog Retrieved Dec 31 2018 Justin Kestelyn March 13 2013 Introducing Parquet Efficient Columnar Storage for Apache Hadoop Cloudera blog Archived from the original on September 19 2016 Retrieved May 4 2017 Retrieved from https en wikipedia org w index php title Apache ORC amp oldid 1119714079, wikipedia, wiki, book, books, library,

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