Abstract: Systems and techniques for leveraging query executions to improve index recommendations are described herein. In an example, a machine learning model is adapted to receive a first query plan and a second query plan for performing a query with a database, where the first query plan is different from the second query plan. The machine learning model may be further adapted to determine execution cost efficiency between the first query plan and the second query plan. The machine learning model is trained using relative execution cost comparisons between a set of pairs of query plans for the database. The machine learning model is further adapted to output a ranking of the first query plan and second query plan, where the first query plan and second query plan are ranked based on execution cost efficiency.

Abstract: Systems and techniques for leveraging query executions to improve index recommendations are described herein. In an example, a machine learning model is adapted to receive a first query plan and a second query plan for performing a query with a database, where the first query plan is different from the second query plan. The machine learning model may be further adapted to determine execution cost efficiency between the first query plan and the second query plan. The machine learning model is trained using relative execution cost comparisons between a set of pairs of query plans for the database. The machine learning model is further adapted to output a ranking of the first query plan and second query plan, where the first query plan and second query plan are ranked based on execution cost efficiency.

Abstract: Methods, systems, and media for distributing database queries across a metered virtual network are provided, the method comprising: receiving a first query at a first time; selecting, using probabilistic models, a first virtual machine to execute the first query, each of the probabilistic models associated with one of a plurality of virtual machines; receiving information indicative of a monetary cost of executing the first query based at least in part on the execution time of the first query by the first virtual machine; providing an observation to each of the plurality of probabilistic models, wherein the observation includes at least information about the cost of executing the first query, and information about an action selected by the probabilistic model in connection with the first query; and reducing, over time, the costs of using the metered virtual network to execute queries received after the first query based on the observations.