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apache / carbondata / 2ee7775519cc86f51cb351e90f6b042d6db38adb
commit2ee7775519cc86f51cb351e90f6b042d6db38adb[log] [tgz]
authorxuchuanyin <xuchuanyin@hust.edu.cn>Fri Aug 11 23:00:20 2017 +0800
committerJacky Li <jacky.likun@qq.com>Fri Aug 18 15:07:24 2017 +0800
treea968738dc6fe2c21ae2fdd9fc135fecf748fd69f
parente8df8ba515f85c21efb152b66b1fd9ef8b3f1ab8 [diff]
[CARBONDATA-1373] Enhance update performance by increasing parallelism

+ Increase parallelism while processing one segment in update
+ Use partitionBy instead of groupby
+ Return directly for no-rows-update case
+ Add a property to configure the parallelism
+ Clean up local files after update (previous bugs)

This closes #1261
7 files changed
tree: a968738dc6fe2c21ae2fdd9fc135fecf748fd69f
  1. .github/
  2. assembly/
  3. bin/
  4. build/
  5. common/
  6. conf/
  7. core/
  8. dev/
  9. docs/
  10. examples/
  11. format/
  12. hadoop/
  13. integration/
  14. processing/
  15. .gitignore
  16. LICENSE
  17. NOTICE
  18. pom.xml
  19. README.md
README.md

Apache CarbonData is an indexed columnar data format for fast analytics on big data platform, e.g.Apache Hadoop, Apache Spark, etc.

You can find the latest CarbonData document and learn more at: http://carbondata.apache.org

CarbonData cwiki

Status

Spark2.1: Build Status Spark1.6: Build Status

Features

CarbonData file format is a columnar store in HDFS, it has many features that a modern columnar format has, such as splittable, compression schema ,complex data type etc, and CarbonData has following unique features:

  • Stores data along with index: it can significantly accelerate query performance and reduces the I/O scans and CPU resources, where there are filters in the query. CarbonData index consists of multiple level of indices, a processing framework can leverage this index to reduce the task it needs to schedule and process, and it can also do skip scan in more finer grain unit (called blocklet) in task side scanning instead of scanning the whole file.
  • Operable encoded data :Through supporting efficient compression and global encoding schemes, can query on compressed/encoded data, the data can be converted just before returning the results to the users, which is “late materialized”.
  • Supports for various use cases with one single Data format : like interactive OLAP-style query, Sequential Access (big scan), Random Access (narrow scan).

Building CarbonData

CarbonData is built using Apache Maven, to build CarbonData

Online Documentation

Other Technical Material

Apache CarbonData meetup material

Fork and Contribute

This is an active open source project for everyone, and we are always open to people who want to use this system or contribute to it. This guide document introduce how to contribute to CarbonData.

Contact us

To get involved in CarbonData:

About

Apache CarbonData is an open source project of The Apache Software Foundation (ASF).