Database Query Optimization Via Parameter-Sensitive Plan Selection

    公开(公告)号:US20250165470A1

    公开(公告)日:2025-05-22

    申请号:US19035387

    申请日:2025-01-23

    Applicant: Google LLC

    Abstract: A method includes receiving a database query requesting a database to conditionally return one or more data blocks. The database is stored on memory hardware in communication with the data processing hardware and the database query includes a plurality of parameters characterizing the database query. The method includes generating a set of query plans. Each query plan in the set of query plans is configured to execute the database query using a different order of operations. The method includes training a model using historical database queries and generating, using the trained model, a query plan score for each query plan in the set of query plans. The method includes selecting, using the query plan score of each query plan in the set of query plans, a query plan from the set of query plans. The method also includes executing the database query using the selected query plan.

    Autonomous Column Selection for Columnar Cache

    公开(公告)号:US20230141891A1

    公开(公告)日:2023-05-11

    申请号:US17523520

    申请日:2021-11-10

    Applicant: Google LLC

    CPC classification number: G06F16/24539 G06F16/2264 G06F16/24552 G06F16/221

    Abstract: Aspects of the disclosure are directed to generating cache configurations for caching data for a database. A database management system (DBMS) can search for column data to cache in a database cache to improve performance of the DBMS in resolving queries. Column data selection can be performed automatically and in the background of a deployed DBMS. Periodically, the DBMS can assess the performance benefit of having certain data cached in the database cache and select data for caching based on the assessed performance benefit. The DBMS can also determine the performance benefit of cached data when not cached, as well as select some portions of data to cache over others. The DBMS can also select data for caching based on different degrees of compression, to further improve query resolution performance.

    Database query optimization via parameter-sensitive plan selection

    公开(公告)号:US12235840B2

    公开(公告)日:2025-02-25

    申请号:US18055502

    申请日:2022-11-15

    Applicant: Google LLC

    Abstract: A method includes receiving a database query requesting a database to conditionally return one or more data blocks. The database is stored on memory hardware in communication with the data processing hardware and the database query includes a plurality of parameters characterizing the database query. The method includes generating a set of query plans. Each query plan in the set of query plans is configured to execute the database query using a different order of operations. The method includes training a model using historical database queries and generating, using the trained model, a query plan score for each query plan in the set of query plans. The method includes selecting, using the query plan score of each query plan in the set of query plans, a query plan from the set of query plans. The method also includes executing the database query using the selected query plan.

    Database Query Optimization Via Parameter-Sensitive Plan Selection

    公开(公告)号:US20230153303A1

    公开(公告)日:2023-05-18

    申请号:US18055502

    申请日:2022-11-15

    Applicant: Google LLC

    CPC classification number: G06F16/24542 G06F11/3419

    Abstract: A method includes receiving a database query requesting a database to conditionally return one or more data blocks. The database is stored on memory hardware in communication with the data processing hardware and the database query includes a plurality of parameters characterizing the database query. The method includes generating a set of query plans. Each query plan in the set of query plans is configured to execute the database query using a different order of operations. The method includes training a model using historical database queries and generating, using the trained model, a query plan score for each query plan in the set of query plans. The method includes selecting, using the query plan score of each query plan in the set of query plans, a query plan from the set of query plans. The method also includes executing the database query using the selected query plan.

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