Conference item
Benchmarking the chase
- Abstract:
- The chase is a family of algorithms used in a number of data management tasks, such as data exchange, answering queries under dependencies, query reformulation with constraints, and data cleaning. It is well established as a theoretical tool for understanding these tasks, and in addition a number of prototype systems have been developed. While individual chase-based systems and particular optimizations of the chase have been experimentally evaluated in the past, we provide the first comprehensive and publicly available benchmark—test infrastructure and a set of test scenarios—for evaluating chase implementations across a wide range of assumptions about the dependencies and the data. We used our benchmark to compare chase-based systems on data exchange and query answering tasks with one another, as well as with systems that can solve similar tasks developed in closely related communities. Our evaluation provided us with a number of new insights concerning the factors that impact the performance of chase implementations.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 348.4KB, Terms of use)
-
- Publisher copy:
- 10.1145/3034786.3034796
Authors
+ Engineering and Physical Sciences Research Council
More from this funder
- Funding agency for:
- Benedikt, M
- Konstantinidis, G
- Motik, B
- Grant:
- MaSI3 (EP/K00607X/1
- MaSI3 (EP/K00607X/1
- MaSI3 (EP/K00607X/1
- Publisher:
- Association for Computing Machinery
- Host title:
- PODS '17 Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems
- Pages:
- 37-52
- Publication date:
- 2017-05-09
- Acceptance date:
- 2016-12-21
- DOI:
- ISBN:
- 9781450341981
- Pubs id:
-
pubs:671854
- UUID:
-
uuid:3c98021b-310f-4100-8d81-047a5b8ebcfc
- Local pid:
-
pubs:671854
- Source identifiers:
-
671854
- Deposit date:
-
2017-01-19
- ARK identifier:
Terms of use
- Copyright holder:
- ACM
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 ACM. This is the accepted manuscript version of the article. The final version is available online from ACM at: https://doi.org/10.1145/3034786.3034796
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