Abstract:
In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a stateless, deterministic scheduler and work discovery system with interruption recovery. For instance, according to one embodiment, there is disclosed a system to implement a stateless scheduler service, in which the system includes: a processor and a memory to execute instructions at the system; a compute resource discovery engine to identify one or more computing resources available to execute workload tasks; a workload discovery engine to identify a plurality of workload tasks to be scheduled for execution; a cache to store information on behalf of the compute resource discovery engine and the workload discovery engine; a scheduler to request information from the cache specifying the one or more computing resources available to execute workload tasks and the plurality of workload tasks to be scheduled for execution; and further in which the scheduler is to schedule at least a portion of the plurality of workload tasks for execution via the one or more computing resources based on the information requested. Other related embodiments are disclosed.
Abstract:
A system determines factored score by multiplying factor and match score for values of field in two records, offset score by adding offset to factored score, and weighted score by applying weight to offset score. The system determines status for two records based on combining weighted score with other weighted score corresponding to other field of two records. The system revises factor, offset, and weight based on feedback associated with two records. The system determines revised factored score by multiplying revised factor and match score for other values of field in two other records, revised offset score by adding revised offset to revised factored score, and revised weighted score by applying revised weight to revised offset score. The system determines learned status for two other records based on combining revised weighted score with additional weighted score corresponding to other field for two other records.
Abstract:
In one embodiment, a computer-implemented method executable by a server system to store data in a data cache and refresh the data based on a dynamic schedule is provided. The method includes: receiving, by a processor, data from a first resource; storing, by the processor, the data in a data cache; determining, by the processor, a type of the data, and an access frequency of the data; determining, by the processor, a dynamic schedule based on the type of the data, and the access frequency of the data; and refreshing the data cache with new data from the first resource based on the dynamic schedule.
Abstract:
In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a stateless, deterministic scheduler and work discovery system with interruption recovery. For instance, according to one embodiment, there is disclosed a system to implement a stateless scheduler service, in which the system includes: a processor and a memory to execute instructions at the system; a compute resource discovery engine to identify one or more computing resources available to execute workload tasks; a workload discovery engine to identify a plurality of workload tasks to be scheduled for execution; a cache to store information on behalf of the compute resource discovery engine and the workload discovery engine; a scheduler to request information from the cache specifying the one or more computing resources available to execute workload tasks and the plurality of workload tasks to be scheduled for execution; and further in which the scheduler is to schedule at least a portion of the plurality of workload tasks for execution via the one or more computing resources based on the information requested. Other related embodiments are disclosed.
Abstract:
In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a stateless, deterministic scheduler and work discovery system with interruption recovery. For instance, according to one embodiment, there is disclosed a system to implement a stateless scheduler service, in which the system includes: a processor and a memory to execute instructions at the system; a compute resource discovery engine to identify one or more computing resources available to execute workload tasks; a workload discovery engine to identify a plurality of workload tasks to be scheduled for execution; a cache to store information on behalf of the compute resource discovery engine and the workload discovery engine; a scheduler to request information from the cache specifying the one or more computing resources available to execute workload tasks and the plurality of workload tasks to be scheduled for execution; and further in which the scheduler is to schedule at least a portion of the plurality of workload tasks for execution via the one or more computing resources based on the information requested. Other related embodiments are disclosed.
Abstract:
In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a scheduler with preemptive termination of existing workloads to free resources for high priority items. For instance, according to one embodiment, there is disclosed a system to implement a scheduling service, wherein the system includes: a processor and a memory to execute instructions at the system; a compute resource discovery engine to identify a plurality of computing resources currently executing scheduled workload tasks; a workload discovery engine to identify one or more pending workload tasks to be scheduled for execution; in which each of the computing resources lack current available capacity to execute additional scheduled workload tasks; a policy engine to define a Service Level Target (SLT) for each of the scheduled workload tasks currently executing via the plurality of computing resources and for each of the one or more pending workload tasks to be scheduled for execution; an analysis engine to further terminate one of the scheduled workload tasks currently executing via the plurality of computing resources based on the defined SLTs for the respective workload tasks; and a scheduler to schedule one of the pending workload tasks into capacity within the plurality of computing resources freed up by the terminated workload task. Other related embodiments are disclosed.
Abstract:
In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a scheduler with preemptive termination of existing workloads to free resources for high priority items. For instance, according to one embodiment, there is disclosed a system to implement a scheduling service, wherein the system includes: a processor and a memory to execute instructions at the system; a compute resource discovery engine to identify a plurality of computing resources currently executing scheduled workload tasks; a workload discovery engine to identify one or more pending workload tasks to be scheduled for execution; in which each of the computing resources lack current available capacity to execute additional scheduled workload tasks; a policy engine to define a Service Level Target (SLT) for each of the scheduled workload tasks currently executing via the plurality of computing resources and for each of the one or more pending workload tasks to be scheduled for execution; an analysis engine to further terminate one of the scheduled workload tasks currently executing via the plurality of computing resources based on the defined SLTs for the respective workload tasks; and a scheduler to schedule one of the pending workload tasks into capacity within the plurality of computing resources freed up by the terminated workload task. Other related embodiments are disclosed.
Abstract:
In one embodiment, a computer-implemented method executable by a server system to store data in a data cache and refresh the data based on a dynamic schedule is provided. The method includes: receiving, by a processor, data from a first resource; storing, by the processor, the data in a data cache; determining, by the processor, a type of the data, and an access frequency of the data; determining, by the processor, a dynamic schedule based on the type of the data, and the access frequency of the data; and refreshing the data cache with new data from the first resource based on the dynamic schedule.
Abstract:
A method is provided for transferring a session between at least two user devices. The method includes receiving a transfer command from a first user device during a session to initiate a session transfer; generating a session code representing the session; receiving the session code from a second user device; and reestablishing the session with the second user device.
Abstract:
Systems and methods are described for managing the application of data management actions to one or more data objects in a data store. The systems and methods extract at least a portion of a first set of data objects from a data store to a file, wherein a first data object of the first set of data objects comprises a first set of attributes and a set of data management actions. A second set of data objects is loaded into the data store. A confidence score is generated based on a comparison of the first data object of the first set of data objects and a second data object of the second set of data objects. A determination is made that the confidence score satisfies a condition. In response to the confidence score satisfying the condition, the set of data management actions is applied to the second data object.