A Pay-As-You-Go Framework for Query Execution Feedback

Surajit Chaudhuri, Vivek Narasayya, and Ravi Ramamurthy

Abstract

Past work has suggested that query execution feedback can be useful in improving the quality of plans by correcting cardinality estimation errors in the query optimizer. The state-of-the-art approach for obtaining execution feedback is “passive” monitoring which records the cardinality of each operator in the execution plan. We observe that there are many cases where even after repeated executions of the same query with use of feedback from passive monitoring, suboptimal choices in the execution plan cannot be corrected. We present a novel “pay-as-you-go” framework in which a query potentially incurs a small overhead on each execution but obtains cardinality information that is not available with passive monitoring alone. Such a framework can significantly extend the reach of query execution feedback in obtaining better plans. We have implemented our techniques in Microsoft SQL Server, and our evaluation on real world and synthetic queries suggests that plan quality can improve significantly compared to passive monitoring even at low overheads.

Details

Publication typeInproceedings
Published inVLDB
PublisherVery Large Data Bases Endowment Inc.
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