ISOMER: Consistent Histogram Construction Using Query Feedback

Database columns are often correlated, so that cardinality estimates computed by assuming independence often lead to a poor choice of query plan by the optimizer. Multidimensional histograms can help solve this problem, but the traditional approach of building such histograms using a data scan often scales poorly and does not always yield the best histogram for a given workload. An attractive alternative is to gather feedback from the query execution engine about the observed cardinality of predicates and use this feedback as the basis for a histogram. In this paper we describe ISOMER, a new feedback-based algorithm for collecting optimizer statistics by constructing and maintaining multidimensional histograms. ISOMER uses the maximumentropy principle to approximate the true data distribution by a histogram distribution that is as "simple" as possible while being consistent with the observed predicate cardinalities. ISOMER adapts readily to changes in the underlying data, au...

• Type: Conference
• Year: 2006
• Where: ICDE
• Authors: Utkarsh Srivastava, Peter J. Haas, Volker Markl, Marcel Kutsch, Tam Minh Tran
• Keywords: Accurate Cardinality Estimates, Database, Feedback-driven Histogram Maintenance, Histogram Distribution, ICDE 2006