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| Content Provider | ACM Digital Library |
|---|---|
| Author | Zdonik, Stan Rasin, Alexander |
| Abstract | Good database design is typically a very difficult and costly process. As database systems get more complex and as the amount of data under management grows, the stakes increase accordingly. Past research produced a number of design tools capable of automatically selecting secondary indexes and materialized views for a known workload. However, a significant bulk of research on automated database design has been done in the context of row-store DBMSes. While this work has produced effective design tools, new specialized database architectures demand a rethinking of automated design algorithms. In this paper, we present results for an automatic design tool that is aimed at column-oriented DBMSes on OLAP workloads. In particular, we have chosen a commercial column store DBMS that supports data sorting. In this setting, the key problem is selecting proper sort orders and compression schemes for the columns as well as appropriate pre-join views. This paper describes our automatic design algorithms as well as the results of some experiments using it on realistic data sets. |
| Starting Page | 203 |
| Ending Page | 214 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450315975 |
| DOI | 10.1145/2452376.2452402 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-03-18 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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