Name
Abstract | ||
|---|---|---|
Aggregate views of large complex data are at the core of many data analytics systems. Group-By OLAP (on-line analytical processing) queries are among the most popular but also very time consuming and particularly challenging in real-time data analytics environments. In contrast to queries for transaction processing systems that typically access only a small portion of a database, OLAP queries may need to aggregate large portions of a database which often leads to performance issues. We present new multicore and cloud based real-time OLAP systems utilizing a novel distributed index structure for OLAP, termed distributed PDCR tree. Our system supports multiple dimension hierarchies and efficient query processing on elaborate dimension hierarchies which are central to OLAP systems. It is particularly efficient for complex OLAP queries that need to aggregate large portions of a data warehouse. |
Year | Venue | Field |
|---|---|---|
2015 | CASCON | Data science,Data warehouse,Data analysis,Computer science,Complex data type,Analytics,Online analytical processing,Multi-core processor,Transaction processing system,Cloud computing |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joanna Ng | 1 | 33 | 2.51 |
| Frank Dehne | 2 | 518 | 43.70 |
| Stan Matwin | 3 | 3025 | 344.20 |
| Herna Lydia Viktor | 4 | 20 | 4.46 |
| Olga Baysal | 5 | 0 | 0.34 |