Machine learning inference calls for database query processing

    公开(公告)号:US11449796B2

    公开(公告)日:2022-09-20

    申请号:US16578060

    申请日:2019-09-20

    Abstract: Techniques for making machine learning inference calls for database query processing are described. In some embodiments, a method of making machine learning inference calls for database query processing may include generating a first batch of machine learning requests based at least on a query to be performed on data stored in a database service, wherein the query identifies a machine learning service, sending the first batch of machine learning requests to an input buffer of an asynchronous request handler, the asynchronous request handler to generate a second batch of machine learning requests based on the first batch of machine learning requests, and obtaining a plurality of machine learning responses from an output buffer of the asynchronous request handler, the machine learning responses generated by the machine learning service using a machine learning model in response to receiving the second batch of machine learning requests.

    Dynamic splitting of contentious index data pages

    公开(公告)号:US11080253B1

    公开(公告)日:2021-08-03

    申请号:US14977439

    申请日:2015-12-21

    Abstract: A storage engine may implement dynamic splitting of contentious data pages. Data pages may store data for a table of a data store as part of an indexing structure for the table. Access to the table may be provided by locating the corresponding data pages via the indexing structure. Access contention for different data pages may be monitored. Data pages may be identified for splitting based on the monitoring. A split operation for an identified data page may be formed to store the data on the identified data page on two different data pages so that subsequent access requests for the data are divided between the two data pages. Monitoring of access contention may also be performed to identify data pages for merging in order to consolidate access requests to a single data page.

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