Name
Abstract | ||
|---|---|---|
In this paper, we consider the problem of scheduling a database query execution graph on a parallel machine. Specifically, we consider the problem of data-partitioning pipelined operators with the objective of minimizing response time. This is a basic problem in scheduling database execution trees. Partitioning promises increased parallelism and memory availability at the price of greater communication overhead. Current partitioning methods [BB90, TWPY92, LCRY93, NSHL93] do not consider these trade-offs. We present a mathematical framework within which these alternatives can be quantified for many interesting practical scenarios. We then present an algorithm whose performance is within a factor of 2 of the optimum possible. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1007/3-540-60584-3_40 | CISMOD |
Field | DocType | Citations |
Query optimization,Graph,Pipeline transport,Database query,Computer science,Scheduling (computing),Response time,Operator (computer programming),Instruction cycle,Distributed computing | Conference | 3 |
PageRank | References | Authors |
0.66 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sumit Ganguly | 1 | 813 | 236.01 |
| Apostolos Gerasoulis | 2 | 531 | 49.60 |
| Weining Wang | 3 | 111 | 11.74 |