Journal article
Factorized Databases
- Abstract:
- This paper overviews factorized databases and their application to machine learning. The key observation underlying this work is that state-of-the-art relational query processing entails a high degree of redundancy in the computation and representation of query results. This redundancy can be avoided and is not necessary for subsequent analytics such as learning regression models.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 377.9KB, Terms of use)
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- Publisher copy:
- 10.1145/3003665.3003667
Authors
- Publisher:
- Association for Computing Machinery
- Journal:
- SIGMOD Record More from this journal
- Volume:
- 45
- Issue:
- 2
- Publication date:
- 2016-09-28
- Acceptance date:
- 2016-06-15
- DOI:
- ISSN:
-
0163-5808
- Pubs id:
-
pubs:629444
- UUID:
-
uuid:9116c474-1e8a-4d63-943e-e0d038454f25
- Local pid:
-
pubs:629444
- Source identifiers:
-
629444
- Deposit date:
-
2016-06-23
- ARK identifier:
Terms of use
- Copyright holder:
- Association for Computing Machinery
- Copyright date:
- 2016
- Notes:
- © ACM, 2016. This is the accepted manuscript version of the article. The final version is available online from ACM at: [10.1145/3003665.3003667]
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