DISTRIBUTED EXECUTION OF TRANSACTIONAL QUERIES

    公开(公告)号:US20240232173A1

    公开(公告)日:2024-07-11

    申请号:US18415826

    申请日:2024-01-18

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/2379 G06F16/24568

    Abstract: The subject technology receives, at a first execution node, a first transaction, the first transaction to be executed on linearizable storage. The subject technology determines whether the first execution node corresponds to a rank indicating a leader worker. The subject technology, in response to the first execution node corresponding to the rank indicating the leader worker, performs, by the first execution node, an initialization process for executing the first transaction. The subject technology broadcasts a first read timestamp associated with the first transaction to a set of execution nodes, the set of execution nodes being different than the first execution node. The subject technology executes, by the first execution node, at least a first operation from the first transaction.

    OPPORTUNISTIC CLOUD DATA PLATFORM PIPELINE SCHEDULER

    公开(公告)号:US20230205770A1

    公开(公告)日:2023-06-29

    申请号:US18176010

    申请日:2023-02-28

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/24542 G06F9/4881 G06F16/27 G06F16/24532

    Abstract: Methods, systems, and computer programs are presented for scheduling and executing request plans using an opportunistic approach. An opportunistic scheduler generates a request plan for a request on a cloud data platform, the request plan comprising a plurality of operations and identifies a plurality of contingent operations from the plurality of operations of the request plan. The opportunistic scheduler schedules the plurality of contingent operations for execution and sets the scheduled plurality of contingent operations to execute at a specific position in the request plan. The opportunistic scheduler sets remaining operations for execution by any available thread as threads that are processing the request plan become available and processes the request plan according to the scheduled plurality of contingent operations.

    Limit query processing using distributed stop operator

    公开(公告)号:US11023491B1

    公开(公告)日:2021-06-01

    申请号:US17077403

    申请日:2020-10-22

    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.

    DYNAMIC DATABASE PIPELINE SCHEDULER
    14.
    发明公开

    公开(公告)号:US20240338366A1

    公开(公告)日:2024-10-10

    申请号:US18746586

    申请日:2024-06-18

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/24542 G06F9/4881 G06F16/24532 G06F16/27

    Abstract: A database system configured to optimize query execution through an opportunistic scheduling approach. The database system generates a query plan and identifies a contingent database operation within the query plan, the contingent database operation being dependent on a completion of at least one additional operation. The database system schedules the contingent operation using an opportunistic scheduler. The database system executes the query plan comprising processing the contingent database operation after the completion of the at least one additional operation.

    Opportunistic cloud data platform pipeline scheduler

    公开(公告)号:US12050603B2

    公开(公告)日:2024-07-30

    申请号:US18176010

    申请日:2023-02-28

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/24542 G06F9/4881 G06F16/24532 G06F16/27

    Abstract: Methods, systems, and computer programs are presented for scheduling and executing request plans using an opportunistic approach. An opportunistic scheduler generates a request plan for a request on a cloud data platform, the request plan comprising a plurality of operations and identifies a plurality of contingent operations from the plurality of operations of the request plan. The opportunistic scheduler schedules the plurality of contingent operations for execution and sets the scheduled plurality of contingent operations to execute at a specific position in the request plan. The opportunistic scheduler sets remaining operations for execution by any available thread as threads that are processing the request plan become available and processes the request plan according to the scheduled plurality of contingent operations.

    Distributed execution of transactional queries

    公开(公告)号:US11921708B1

    公开(公告)日:2024-03-05

    申请号:US17823801

    申请日:2022-08-31

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/2379 G06F16/24568

    Abstract: The subject technology receives, at a first execution node, a first transaction, the first transaction to be executed on linearizable storage. The subject technology determines whether the first execution node corresponds to a rank indicating a leader worker. The subject technology, in response to the first execution node corresponding to the rank indicating the leader worker, performs, by the first execution node, an initialization process for executing the first transaction. The subject technology broadcasts a first read timestamp associated with the first transaction to a set of execution nodes, the set of execution nodes being different than the first execution node. The subject technology executes, by the first execution node, at least a first operation from the first transaction.

    DISTRIBUTED EXECUTION OF TRANSACTIONAL QUERIES

    公开(公告)号:US20240070143A1

    公开(公告)日:2024-02-29

    申请号:US17823801

    申请日:2022-08-31

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/2379 G06F16/24568

    Abstract: The subject technology receives, at a first execution node, a first transaction, the first transaction to be executed on linearizable storage. The subject technology determines whether the first execution node corresponds to a rank indicating a leader worker. The subject technology, in response to the first execution node corresponding to the rank indicating the leader worker, performs, by the first execution node, an initialization process for executing the first transaction. The subject technology broadcasts a first read timestamp associated with the first transaction to a set of execution nodes, the set of execution nodes being different than the first execution node. The subject technology executes, by the first execution node, at least a first operation from the first transaction.

    Scheduling parallel execution of query sub-plans

    公开(公告)号:US11907221B2

    公开(公告)日:2024-02-20

    申请号:US17804770

    申请日:2022-05-31

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/24545 G06F16/24532 G06F16/24537

    Abstract: Sub-plans are executed in parallel using a plurality of execution nodes, which can be part of a data platform. In particular, various embodiments identify sub-plans (e.g., fragments or portions of one or more child operators) of a root operator in a query plan such that the identified sub-plans that are candidates for execution on a single execution node, determine a cost estimate for causing the candidate sub-plans to be executed in parallel using multiple execution nodes, and cause the candidate sub-plans to be executed in parallel based on the cost estimate.

    Distributed stop operator for query processing

    公开(公告)号:US10860609B1

    公开(公告)日:2020-12-08

    申请号:US16855372

    申请日:2020-04-22

    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.

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