Title :
rFEED: A Mixed Workload Scheduler for Enterprise Data Warehouses
Author :
Mehta, Abhay ; Gupta, Chetan ; Wang, Song ; Dayal, Umesh
fDate :
March 29 2009-April 2 2009
Abstract :
A typical online business intelligence (BI) workload consists of a combination of short, less intensive queries, along with long, resource intensive queries. As such, the longest queries in a typical BI workload may take several orders of magnitude more time to execute, compared with the shortest queries in the workload. This makes it challenging to design a good mixed workload scheduler (MWS). In this paper we first define the design criteria that make a ´good´ MWS. We then use these criteria to design rFEED, a MWS that is fair, effective, efficient, and differentiated. We simulate real workloads and compare our rFEED MWS with models of the current best of breed commercial systems. We show that the rFEED MWS works extremely well.
Keywords :
business data processing; competitive intelligence; data warehouses; enterprise data warehouses; mixed workload scheduler; online business intelligence; rFEED; resource intensive queries; Bismuth; Business; Data engineering; Data warehouses; Delay; Feeds; Frequency; Scheduling; Enterprise Data Warehouse; Scheduling;
Conference_Titel :
Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3422-0
Electronic_ISBN :
1084-4627
DOI :
10.1109/ICDE.2009.66