{"id":1137365,"date":"2025-04-23T00:23:24","date_gmt":"2025-04-23T07:23:24","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=1137365"},"modified":"2025-10-08T22:43:56","modified_gmt":"2025-10-09T05:43:56","slug":"esc-an-early-stopping-checker-for-budget-aware-index-tuning-2","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/esc-an-early-stopping-checker-for-budget-aware-index-tuning-2\/","title":{"rendered":"Esc: An Early-stopping Checker for Budget-aware Index Tuning (Extended Version)"},"content":{"rendered":"<p>Index tuning is a time-consuming process. One major performance bottleneck in existing index tuning systems is the large amount of \u201cwhat-if\u201d query optimizer calls that estimate the cost of a given pair of query and index configuration without materializing the indexes. There has been recent work on budget-aware index tuning that limits the amount of what-if calls allowed in index tuning. Existing budget-aware index tuning algorithms, however, typically make fast progress early on in terms of the best configuration found but slow down when more and more what-if calls are allocated. This observation of \u201cdiminishing return\u201d on index quality leads us to introduce early stopping for budget-aware index tuning, where user specifies a threshold on the tolerable loss of index quality and we stop index tuning if the projected loss with the remaining budget is below the threshold. We further propose Esc, a low-overhead early-stopping checker that realizes this new functionality. Experimental evaluation on top of both industrial benchmarks and real customer workloads demonstrate that Esc can significantly reduce the number of what-if calls made during budget-aware index tuning while incur little or zero improvement loss and little extra computational overhead compared to the overall index tuning time.<\/p>\n<p>&nbsp;<\/p>\n<p>Extended version of the paper:\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/04\/esc-full.pdf\">[Full Version]<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Index tuning is a time-consuming process. One major performance bottleneck in existing index tuning systems is the large amount of \u201cwhat-if\u201d query optimizer calls that estimate the cost of a given pair of query and index configuration without materializing the indexes. There has been recent work on budget-aware index tuning that limits the amount of [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"Proceedings of the VLDB Endowment (VLDB 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