Task scheduling for highly concurrent analytical and transaction workloads

    公开(公告)号:US10545789B2

    公开(公告)日:2020-01-28

    申请号:US15963060

    申请日:2018-04-25

    Applicant: SAP SE

    Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

    ADAPTIVE TABLE PLACEMENT IN NUMA ARCHITECTURES
    2.
    发明申请
    ADAPTIVE TABLE PLACEMENT IN NUMA ARCHITECTURES 审中-公开
    NUMA建筑中的自适应桌布置

    公开(公告)号:US20170017674A1

    公开(公告)日:2017-01-19

    申请号:US14802580

    申请日:2015-07-17

    Applicant: SAP SE

    CPC classification number: G06F16/2282

    Abstract: Techniques and solutions are provided for performing adaptive database table placement in a non-uniform memory access (NUMA) architecture. The adaptive table placement can occur in response to changing workloads on the NUMA nodes. For example, if a particular NUMA node is saturated, a database table may be moved from the memory of the saturated NUMA node to the memory of another NUMA node that is underutilized. In some cases, an entire database table is moved, while in other cases the database table is partitioned and only part of the table is moved.

    Abstract translation: 提供了技术和解决方案,用于在非均匀存储器访问(NUMA)架构中执行自适应数据库表放置。 自适应表放置可以响应于NUMA节点上的工作负载变化而发生。 例如,如果特定的NUMA节点饱和,则数据库表可以从饱和NUMA节点的存储器移动到未充分利用的另一个NUMA节点的存储器。 在某些情况下,整个数据库表被移动,而在其他情况下,数据库表被分区,只有表的一部分被移动。

    Task Scheduling for Highly Concurrent Analytical and Transaction Workloads
    3.
    发明申请
    Task Scheduling for Highly Concurrent Analytical and Transaction Workloads 审中-公开
    高度并发分析和事务工作负载的任务计划

    公开(公告)号:US20160217003A1

    公开(公告)日:2016-07-28

    申请号:US15088810

    申请日:2016-04-01

    Applicant: SAP SE

    Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

    Abstract translation: 公开了具有并发级别和任务粒度的动态调整的任务调度器的系统和方法,用于改进高并发分析和事务系统的执行。 任务调度器可以通过监视和控制活动的工作线程的数量来避免计算资源的过度承诺和利用不足。 活动的工作线程的数量可以通过给操作系统控制额外的工作线程处理被阻止的应用程序任务而适应于避免计算资源利用不足。 任务调度器可以基于可用线程的数量动态地确定特定任务的并行操作的数量。 可以根据应用程序的最近历史中的工作线程的平均可用性来确定可用的工作线程数。 基于可用的工作线程的数量,可分割操作可以划分为多个子操作并且并行执行。

    Adaptive table placement in NUMA architectures

    公开(公告)号:US11275721B2

    公开(公告)日:2022-03-15

    申请号:US14802580

    申请日:2015-07-17

    Applicant: SAP SE

    Abstract: Techniques and solutions are provided for performing adaptive database table placement in a non-uniform memory access (NUMA) architecture. The adaptive table placement can occur in response to changing workloads on the NUMA nodes. For example, if a particular NUMA node is saturated, a database table may be moved from the memory of the saturated NUMA node to the memory of another NUMA node that is underutilized. In some cases, an entire database table is moved, while in other cases the database table is partitioned and only part of the table is moved.

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