JOIN QUERY PROCESSING USING PRUNING INDEX

    公开(公告)号:US20220292098A1

    公开(公告)日:2022-09-15

    申请号:US17804630

    申请日:2022-05-31

    Applicant: Snowflake Inc.

    Abstract: A query directed at a table organized into a set of batch units is received. The query comprises a predicate for which values are unknown prior to runtime. A set of values for the predicate are determined based on the query. An index access plan is created based on the set of values. Based on the index access plan, the set of batch units are pruned using a pruning index associated with the table. The pruning index comprises a set of filters that index distinct values in each column of the table. The pruning of the set of batch units comprises identifying a subset of batch units to scan for data that satisfies the query. The subset of batch units of the table are scanned to identify data that satisfies the query.

    ALERT BASED ON BASELINE RESULT
    185.
    发明申请

    公开(公告)号:US20220292071A1

    公开(公告)日:2022-09-15

    申请号:US17804674

    申请日:2022-05-31

    Applicant: Snowflake Inc.

    Abstract: Disclosed herein are systems and methods for providing percentile-based alerts from historical event-occurrence data. An embodiment of a method includes identifying a baseline result of an aggregation operation performed with respect to a detection set of attributes of event records. Each baseline result corresponds to a baseline set of one or more event records from a baseline time period within a baseline time window. The method includes determining a subject result of the aggregation operation performed with respect to the detection set of attributes of a subject set of the event records corresponding to a subject time period. The method includes determining, based on the baseline result and the subject result, whether the subject result indicates an alert condition for the detection set for the subject time period, and if so then outputting one or more alerts.

    Distributed stop operator for limit queries

    公开(公告)号:US11436253B2

    公开(公告)日:2022-09-06

    申请号:US17517935

    申请日:2021-11-03

    Applicant: Snowflake Inc.

    Abstract: A global and local row count limit associated with a limit query are received by a stop operator of a first execution node among a set of execution nodes that are assigned to process the limit query. Local distributed row count data is generated based on a local row count corresponding to a number of rows output by the first execution node in processing the query. Based on determining the local row count satisfies the local limit, the first execution node buffers rows produced in processing the query. The local distributed row count data is updated based on remote distributed row count data received from a second execution node. A stopping condition is detected based on determining the global limit is satisfied based on updated local distributed row count data and query processing by the first execution node based on detecting the stopping condition.

    RESOURCE PROVISIONING IN DATABASE SYSTEMS

    公开(公告)号:US20220269676A1

    公开(公告)日:2022-08-25

    申请号:US17663248

    申请日:2022-05-13

    Applicant: Snowflake Inc.

    Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.

    PREDICTIVE RESOURCE ALLOCATION FOR DISTRIBUTED QUERY EXECUTION

    公开(公告)号:US20220237192A1

    公开(公告)日:2022-07-28

    申请号:US17157233

    申请日:2021-01-25

    Applicant: Snowflake Inc.

    Abstract: The subject technology receives a query directed to a set of source tables, each source table organized into a set of micro-partitions. The subject technology determines a set of metadata, the set of metadata comprising table metadata, query metadata, and historical data related to the query. The subject technology predicts, using a machine learning model, an indicator of an amount of computing resources for executing the query based at least in part on the set of metadata. The subject technology generates a query plan for executing the query based at least in part on the predicted indicator of the amount of computing resources. The subject technology executes the query based at least in part on the query plan.

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