Amazon Technologies, Inc.

Chunbin Lin

Naresh Chainani

Gaurav Saxena

George Constantin Caragea

Mohammad Rezaur Rahman

Ippokratis Pandis

Mengchu Cai

Krishna Chaitanya Gudipati

Fabian Oliver Nagel

Sanjay Wangoo

Raj Narayan Sett

Qichen Zhang

Nikolaos Armenatzoglou

Dynamic selection of topologies for database data may be performed for performing queries. Different possible query plans for different assignments of topologies are determined for a query. One of the query plans is selected according to a cost-based model that assigns costs to different uses of the different topologies. The query is then performed using the selected query plan.

Dynamic selection of database data topologies for performing queries

Database systems may dynamically management concurrency levels for performing queries. A query may be received at a database system and a memory usage for the query may be predicted. A determination may be made as to whether available memory is enough to satisfy the predicted memory usage for the query. If the available memory is enough to satisfy the predicted memory usage for the query, then an increase in a concurrency level for performing queries at the database system may be made. The query may be allowed to execute concurrently with other queries according to the increased concurrency level.

Dynamic concurrency level management for database queries

Performance measures are predicted for queries to prioritize query performance at a database system. A trained machine learning model for the database system may be applied to a query to determine a predicted performance measure for the query. The predicted performance measure may be compared with other predicted performance measures for other waiting queries to determine a priority for executing the query.

Predicting query performance for prioritizing query execution

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Dublin, CA, United States of America

Chunbin Lin