CONTEXT DEPENDENT EXECUTION TIME PREDICTION FOR REDIRECTING QUERIES

    公开(公告)号:US20220269680A1

    公开(公告)日:2022-08-25

    申请号:US17662623

    申请日:2022-05-09

    Abstract: Context dependent execution time prediction may be applied to redirect queries to additional query processing resources. A query to a database may be received at a first query engine. A prediction model for executing queries at the first query engine may be applied to determine predicted query execution time for the first query engine. A prediction model for executing queries at a second query engine may also be applied to determine predicted query execution time for the second query engine. One of the query engines may be selected to perform the query based on a comparison of the predicted query execution times.

    INGESTION PARTITION AUTO-SCALING IN A TIME-SERIES DATABASE

    公开(公告)号:US20220171792A1

    公开(公告)日:2022-06-02

    申请号:US17675567

    申请日:2022-02-18

    Abstract: Methods, systems, and computer-readable media for ingestion partition auto-scaling in a time-series database are disclosed. A first set of one or more hosts divides elements of time-series data into a plurality of partitions. A second set of one or more hosts stores the elements of time-series data from the plurality of partitions into one or more storage tiers of a time-series database. An analyzer receives first data indicative of the resource usage of the time-series data at the first set of one or more hosts. The analyzer receives second data indicative of the resource usage of the time-series data at the second set of one or more hosts. Based at least in part on analysis of the first data and the second data, the analyzer initiates a split of an individual one of the partitions into two or more partitions.

    Ingestion partition auto-scaling in a time-series database

    公开(公告)号:US11256719B1

    公开(公告)日:2022-02-22

    申请号:US16455591

    申请日:2019-06-27

    Abstract: Methods, systems, and computer-readable media for ingestion partition auto-scaling in a time-series database are disclosed. A first set of one or more hosts divides elements of time-series data into a plurality of partitions. A second set of one or more hosts stores the elements of time-series data from the plurality of partitions into one or more storage tiers of a time-series database. An analyzer receives first data indicative of the resource usage of the time-series data at the first set of one or more hosts. The analyzer receives second data indicative of the resource usage of the time-series data at the second set of one or more hosts. Based at least in part on analysis of the first data and the second data, the analyzer initiates a split of an individual one of the partitions into two or more partitions.

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