Selecting a Host Based on Quality of Stored Data

    公开(公告)号:US20230079026A1

    公开(公告)日:2023-03-16

    申请号:US18056647

    申请日:2022-11-17

    Applicant: eBay Inc.

    Abstract: A database node selects one of a number of database mirror hosts to perform a database read query. In theory, mirror hosts store redundant database entries. In practice, some mirror hosts fail to receive or retain some entries, e.g. if a mirror host was down for maintenance, a mirror host was overburdened, etc. The health of a mirror host, quantified as a health score, represents a likelihood that an insert statement was received and retained. Health scores are generated based on health metrics—data periodically retrieved from mirror hosts used to infer how well the database was operating, e.g. a count of entries that were inserted, a count of errors encountered while the entries were inserted, etc. If the database read query specifies entries inserted during a specific time period, the mirror host may be selected based on the health scores representing that time period.

    Selecting a host based on quality of stored data

    公开(公告)号:US12141140B2

    公开(公告)日:2024-11-12

    申请号:US18056647

    申请日:2022-11-17

    Applicant: eBay Inc.

    Abstract: A database node selects one of a number of database mirror hosts to perform a database read query. In theory, mirror hosts store redundant database entries. In practice, some mirror hosts fail to receive or retain some entries, e.g. if a mirror host was down for maintenance, a mirror host was overburdened, etc. The health of a mirror host, quantified as a health score, represents a likelihood that an insert statement was received and retained. Health scores are generated based on health metrics—data periodically retrieved from mirror hosts used to infer how well the database was operating, e.g. a count of entries that were inserted, a count of errors encountered while the entries were inserted, etc. If the database read query specifies entries inserted during a specific time period, the mirror host may be selected based on the health scores representing that time period.

    RATE-LIMITING BASED ON CARDINALITY COMPUTATION

    公开(公告)号:US20210075702A1

    公开(公告)日:2021-03-11

    申请号:US16562769

    申请日:2019-09-06

    Applicant: eBay Inc.

    Abstract: A cloud-based service records time-series data of a plurality of metrics from a plurality of tenants. The time-series data comprises a series of measures of a metric at sequential points in time. The time-series data is recorded in database tables in a manner that consumes more resources when the cardinality of the time-series data is high. When the cardinality of the data for the tenant is too high, the tenant is blacklisted and further data for the tenant is not stored. In addition to identifying incoming time-series data by the tenant that produced it, the data may also identify its type. In this case, the cardinality of each type of data may be determined and the types of data may be individually allowed or blacklisted for the tenant.

    Selecting a host based on quality of stored data

    公开(公告)号:US11544258B2

    公开(公告)日:2023-01-03

    申请号:US16783078

    申请日:2020-02-05

    Applicant: eBay Inc.

    Abstract: A database node selects one of a number of database mirror hosts to perform a database read query. In theory, mirror hosts store redundant database entries. In practice, some mirror hosts fail to receive or retain some entries, e.g. if a mirror host was down for maintenance, a mirror host was overburdened, etc. The health of a mirror host, quantified as a health score, represents a likelihood that an insert statement was received and retained. Health scores are generated based on health metrics—data periodically retrieved from mirror hosts used to infer how well the database was operating, e.g. a count of entries that were inserted, a count of errors encountered while the entries were inserted, etc. If the database read query specifies entries inserted during a specific time period, the mirror host may be selected based on the health scores representing that time period.

    Rate-limiting based on cardinality computation

    公开(公告)号:US11303545B2

    公开(公告)日:2022-04-12

    申请号:US16562769

    申请日:2019-09-06

    Applicant: eBay Inc.

    Abstract: A cloud-based service records time-series data of a plurality of metrics from a plurality of tenants. The time-series data comprises a series of measures of a metric at sequential points in time. The time-series data is recorded in database tables in a manner that consumes more resources when the cardinality of the time-series data is high. When the cardinality of the data for the tenant is too high, the tenant is blacklisted and further data for the tenant is not stored. In addition to identifying incoming time-series data by the tenant that produced it, the data may also identify its type. In this case, the cardinality of each type of data may be determined and the types of data may be individually allowed or blacklisted for the tenant.

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