Microsoft Technology Licensing, LLC

In-Jerng Choe

Alexandre Olegovich Verbitski

Aleksandras Surna

Vasileios Papadimos

Chandrashekhar Kadiam

Boris Baryshnikov

Ankit Mahajan

Gjorgji Gjeorgjievski

Adrian Catalin Dragusanu

Alexey Eksarevskiy

Patryk Maciej Uchman

Pedro M Lopes

Irving Alfonso Covarrubias Martin Del Campo

Manish Eknath Tawade

Smita Behera

Nan Xing

Wai Keat Tan

Joel L Redman, Jr

Joseph I Sack

Ravishankar Rajamani

Derek Marcel Wilson

Shitong Song

When two ad hoc query batches with the same query text are to be compiled, one locking key is created for both ad hoc query batches. The locking key is allocated to the first ad hoc query batch. In a subsequent cache lookup stage, if no cache is found for the first ad hoc query batch, a plan is compiled for the first ad hoc query batch, and inserted into a cache. The locking key is released and allocated to the second ad hoc query batch. If the locking key for the second ad hoc query batch is the same as for the first ad hoc query batch, the compiled plan is identified in the cache. Plan compilation is bypassed for the second ad hoc query batch.

Ad hoc query batch compilation serialization

Methods for cardinality estimation feedback loops in query processing are performed by systems and devices. A query host executes queries against data sources via an engine based on estimated cardinalities, and query monitors generate event signals during and at completion of execution. Event signals include indicia of actual data cardinality, runtime statistics, and query parameters in query plans, and are routed to analyzers of a feedback optimizer where event signal information is analyzed. The feedback optimizer utilizes analysis results to generate change recommendations as feedback for later executions of the queries, or similar queries, performed by a query optimizer of the query host. The query host stores change recommendations, and subsequent queries are monitored for the same or similar queries to which change recommendations are applied to query plans for execution and observance by the query monitors. Change recommendations are optionally viewed and selected via a user interface.

System and method for cardinality estimation feedback loops in query processing

A database can have multiple requests applied at one time. Each of these requests requires a specific amount of server resources. There can be a differentiation of user-submitted workloads between each other. These workloads are a set of queries submitted by different users. Each query can have specific resource limits. In addition, each set can have specific resource limits.

Enforcing system resource usage limits on query requests based on grouping query requests into workgroups and assigning workload groups to resource pools

Growing community of inventors

Sammamish, WA, United States of America

In-Jerng Choe