| Full text | |
| Author(s): |
Brito, Jaqueline J.
[1]
;
Mosqueiro, Thiago
[2]
;
Ciferri, Ricardo R.
[3]
;
Ciferri, Cristina D. A.
[1]
Total Authors: 4
|
| Affiliation: | [1] Univ Sao Paulo, Sao Carlos - Brazil
[2] Univ Calif Los Angeles, Los Angeles, CA - USA
[3] Univ Fed Sao Carlos, Sao Carlos - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | HELIYON; v. 6, n. 2 FEB 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
Indices improve the performance of relational databases, especially on queries that return a small portion of the data (i.e., low-selectivity queries). Star joins are particularly expensive operations that commonly rely on indices for improved performance at scale. The development and support of index-based solutions for Star Joins are still at very early stages. To address this gap, we propose a distributed Bitmap Join Index (dBJI) and a framework-agnostic strategy to solve join predicates in linear time. For empirical analysis, we used common Hadoop technologies (e.g., HBase and Spark) to show that dBJI significantly outperforms full scan approaches by a factor between 59% and 88% in queries with low selectivity from the Star Schema Benchmark (SSB). Thus, distributed indices may significantly enhance low-selectivity query performance even in very large databases. (AU) | |
| FAPESP's process: | 12/13158-9 - Storage and recovery of warehouse data in the cloud |
| Grantee: | Jaqueline Joice Brito |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 18/22277-8 - Processing of OLAP and SOLAP Queries on Parallel and Distributed Environments |
| Grantee: | Cristina Dutra de Aguiar |
| Support Opportunities: | Regular Research Grants |