Proactive and reactive multi-dimensional histogram maintenance for selectivity estimation

Many state-of-the-art selectivity estimation methods use query feedback to maintain histogram buckets, thereby using the limited memory efficiently. However, they are "reactive" in nature, that is, they update the histogram based on queries that have come to the system in the past for evaluation. In some applications, future occurrences of certain queries may be predicted and a "proactive" approach can bring much needed performance gain, especially when combined with the reactive approach. For these applications, this paper provides a method that builds customized proactive histograms based on query prediction and mergers them into reactive histograms when the predicted future arrives. Thus, the method is called the Proactive and Reactive Histogram (PRHist). Two factors affect the usefulness of the proactive histograms and are dealt with during the merge process: the first is the predictability of queries and the second is the extent of data updates. PRHist adjusts...

• Type: Journal
• Year: 2008
• Where: JSS
• Authors: Zhen He, Byung Suk Lee, Xiaoyang Sean Wang
• Keywords: Histograms, JSS 2008, Proactive, Reactive Histogram