US 12,013,853 B2
Cloud based query workload optimization
Hiren S. Patel, Bothell, WA (US); Rathijit Sen, Madison, WI (US); Zhicheng Yin, Kirkland, WA (US); Shi Qiao, Bellevue, WA (US); Abhishek Roy, Bellevue, WA (US); Alekh Jindal, Sammamish, WA (US); Subramaniam Venkatraman Krishnan, Santa Clara, CA (US); and Carlo Aldo Curino, Woodinville, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Sep. 25, 2019, as Appl. No. 16/581,905.
Prior Publication US 2021/0089532 A1, Mar. 25, 2021
Int. Cl. G06F 16/2453 (2019.01)
CPC G06F 16/24542 (2019.01) 20 Claims
OG exemplary drawing
 
1. A physical article of manufacture including one or more non-transitory computer-readable storage media, encoding computer-executable instructions for executing on a computer system a computer process, the computer process comprising:
receiving query logs from various query engines to a cloud data service;
extracting various query traces from the query logs, wherein the query traces including at least one of query metadata, query plans, and query runtime statistics;
parsing query traces using a plurality of parsers with each of the plurality of parsers configured to parse a different types of queries to generate a set of common workload features;
generating intermediate representations of the query workloads using the set of common workload features, wherein the intermediate representations are agnostic to the language of the plurality of the queries and are common across workloads and query engines;
identifying a plurality of workload patterns based on the intermediate representations of the query workloads;
categorizing the workloads in one or more workload type categories based on the workload patterns and the workload features; and
selecting an optimization scheme based on the category of workload pattern.