Abstract
The paper demonstrates Hippo a lightweight database indexing scheme that significantly reduces the storage and maintenance overhead without compromising much on the query execution performance. Hippo stores disk page ranges instead of tuple pointers in the indexed table to reduce the storage space occupied by the index. It maintains simplified histograms that represent the data distribution and adopts a page grouping technique that groups contiguous pages into page ranges based on the similarity of their index key attribute distributions. When a query is issued, Hippo leverages the page ranges and histogram-based page summaries to recognize those pages such that their tuples are guaranteed not to satisfy the query predicates and then inspects the remaining pages.We demonstrate Hippo using a billion NYC taxi trip records.
Original language | English (US) |
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Title of host publication | Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 |
Publisher | IEEE Computer Society |
Pages | 1413-1414 |
Number of pages | 2 |
ISBN (Electronic) | 9781509065431 |
DOIs | |
State | Published - May 16 2017 |
Event | 33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States Duration: Apr 19 2017 → Apr 22 2017 |
Other
Other | 33rd IEEE International Conference on Data Engineering, ICDE 2017 |
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Country/Territory | United States |
City | San Diego |
Period | 4/19/17 → 4/22/17 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Information Systems