知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

10 records (took 0.015 seconds)

    Connector interface for data pipeline
    1.
    发明授权
    Connector interface for data pipeline 有权
    数据管道连接器接口

    公开(公告)号：US08812752B1

    公开(公告)日：2014-08-19

    申请号：US13764711

    申请日：2013-02-11

    Applicant: Amazon Technologies, Inc.

    Inventor： Kathryn Marie Shih ,  Eider Brantly Moore ,  Richard Rex McKnight ,  Vaibhav Aggarwal ,  Peter Sirota ,  Richard Jeffrey Cole ,  James P. Bartlett ,  Carl Louis Christofferson

    IPC: G06F3/00 ,  G06F9/44

    CPC classification number: G06F9/52 ,  G06F9/542 ,  G06Q10/063

    Abstract: Methods and systems for a connector interface in a data pipeline are disclosed. A pipeline comprising two data source nodes and an activity node is configured. Each data source node represents data from a different data source, and the activity node represents a workflow activity that uses the data as input. Two connectors which implement the same connector interface are triggered. In response, data is acquired at each connector from the corresponding data source through the connector interface. The data is sent from the connectors to the activity node through the connector interface. The workflow activity is performed using the acquired data.

    Abstract translation: 公开了数据管线中的连接器接口的方法和系统。 配置包括两个数据源节点和活动节点的流水线。 每个数据源节点表示来自不同数据源的数据，活动节点表示使用数据作为输入的工作流活动。 实现相同连接器接口的两个连接器被触发。 作为响应，通过连接器接口从相应的数据源在每个连接器处获取数据。 数据通过连接器接口从连接器发送到活动节点。 使用获取的数据执行工作流活动。

    Cost-minimizing task scheduler
    2.
    发明授权
    Cost-minimizing task scheduler 有权

    公开(公告)号：US10552774B2

    公开(公告)日：2020-02-04

    申请号：US13764692

    申请日：2013-02-11

    Applicant: Amazon Technologies, Inc.

    Inventor： Kathryn Marie Shih ,  Carl Louis Christofferson ,  Richard Jeffrey Cole ,  Peter Sirota ,  Vaibhav Aggarwal

    IPC: G06Q10/06 ,  G06F9/50

    Abstract: Methods and systems for cost-minimizing job scheduling are disclosed. A definition of a task is received. The definition comprises a need-by time. The need-by time comprises a deadline for completion of execution of the task. An estimated duration to complete the execution of the task is determined for each of a plurality of computing resources. One or more of the computing resources are selected based on an estimated cost of completing the execution using the computing resources. The execution of the task is initiated at a scheduled time using the selected one or more computing resources. The scheduled time is earlier than the need-by time by at least the estimated duration.

    Scheduler for data pipeline
    5.
    发明授权
    Scheduler for data pipeline 有权
    数据管线调度器

    公开(公告)号：US09588822B1

    公开(公告)日：2017-03-07

    申请号：US13764716

    申请日：2013-02-11

    Applicant: Amazon Technologies, Inc.

    Inventor： Kathryn Marie Shih ,  Eider Brantly Moore ,  Lorenzo Minore ,  Carl Louis Christofferson ,  Richard Rex McKnight ,  Richard Jeffrey Cole ,  Vaibhav Aggarwal ,  Peter Sirota ,  James P. Bartlett

    IPC: G06F9/46 ,  G06F9/52

    CPC classification number: G06F9/52 ,  G06F9/542 ,  G06Q10/063

    Abstract: Methods and systems for using a scheduler in a data pipeline are disclosed. A plurality of objects in a first layer are created, each representing a respective regularly scheduled task. A plurality of objects in a second layer are created, each representing a respective scheduled instance of a regularly scheduled task. It is determined whether each object in the second layer is ready to execute. For at least one object in the second layer, it is determined if the object has received notifications from any objects on which it depends. For each object that is ready to execute, the regularly scheduled task associated with the object is performed. For each object that is not ready to execute, the object is put to sleep.

    Abstract translation: 公开了在数据流水线中使用调度器的方法和系统。 创建第一层中的多个对象，每个对象表示相应的规则排列任务。 创建第二层中的多个对象，每个对象表示规则调度任务的相应调度实例。 确定第二层中的每个对象是否准备好执行。 对于第二层中的至少一个对象，确定对象是否已经从其所依赖的任何对象接收到通知。 对于准备执行的每个对象，执行与对象相关联的定期计划的任务。 对于尚未准备好执行的每个对象，对象都将进入休眠状态。

    Task timeouts based on input data characteristics
    7.
    发明授权
    Task timeouts based on input data characteristics 有权
    基于输入数据特征的任务超时

    公开(公告)号：US09430280B1

    公开(公告)日：2016-08-30

    申请号：US13764705

    申请日：2013-02-11

    Applicant: Amazon Technologies, Inc.

    Inventor： Kathryn Marie Shih ,  Carl Louis Christofferson ,  Richard Jeffrey Cole ,  Peter Sirota ,  Vaibhav Aggarwal

    IPC: G06F9/48 ,  G06F9/50

    CPC classification number: G06F9/485 ,  G06F9/5005 ,  G06F9/5027 ,  G06F2209/5013 ,  G06F2209/508

    Abstract: Methods and systems for task timeouts as a function of input data size are disclosed. A definition of a task is received. The definition of the task indicates a set of input data for the task. A timeout duration for the task is determined based on the set of input data. The timeout duration varies with one or more characteristics of the set of input data. The execution of the task is initiated. The execution of the task is stopped if the execution of the task exceeds the timeout duration.

    Abstract translation: 公开了作为输入数据大小的函数的任务超时的方法和系统。 收到任务的定义。 任务的定义表示一组任务的输入数据。 基于输入数据集来确定任务的超时持续时间。 超时持续时间随输入数据组的一个或多个特性而变化。 启动任务的执行。 如果执行任务超过超时持续时间，则任务的执行将停止。

    DYNAMIC SCALING OF A CLUSTER OF COMPUTING NODES
    8.
    发明申请
    DYNAMIC SCALING OF A CLUSTER OF COMPUTING NODES 审中-公开
    计算节点集群的动态缩放

    公开(公告)号：US20150135185A1

    公开(公告)日：2015-05-14

    申请号：US14598137

    申请日：2015-01-15

    Applicant: Amazon Technologies, Inc.

    Inventor： Peter Sirota ,  Richard J. Cole ,  Vaibhav Aggarwal ,  Andrew J. Hitchcock ,  Jai Vasanth

    IPC: G06F9/48 ,  G06F9/50

    CPC classification number: G06F9/4881 ,  G06F9/5011 ,  G06F9/5061 ,  G06F2209/5011 ,  H04L67/10

    Abstract: Techniques are described for managing distributed execution of programs, including by dynamically scaling a cluster of multiple computing nodes performing ongoing distributed execution of a program, such as to increase and/or decrease computing node quantity. An architecture may be used that has core nodes that each participate in a distributed storage system for the distributed program execution, and that has one or more other auxiliary nodes that do not participate in the distributed storage system. Furthermore, as part of performing the dynamic scaling of a cluster, computing nodes that are only temporarily available may be selected and used, such as computing nodes that might be removed from the cluster during the ongoing program execution to be put to other uses and that may also be available for a different fee (e.g., a lower fee) than other computing nodes that are available throughout the ongoing use of the cluster.

    Abstract translation: 描述了用于管理程序的分布式执行的技术，包括通过动态地缩放执行程序的正在进行的分布式执行的多个计算节点的集群，例如增加和/或减少计算节点数量。 可以使用具有每个参与用于分布式程序执行的分布式存储系统的核心节点并且具有不参与分布式存储系统的一个或多个其他辅助节点的架构。 此外，作为执行群集的动态缩放的一部分，可以选择和使用仅临时可用的计算节点，例如在正在进行的程序执行期间可能从群集中移除的计算节点以被放置到其他用途， 也可能与在整个持续使用集群时可用的其他计算节点的费用不同（例如，较低的费用）可用。

    Dynamic scaling of a cluster of computing nodes
    9.
    发明授权
    Dynamic scaling of a cluster of computing nodes 有权
    一组计算节点的动态缩放

    公开(公告)号：US09280390B2

    公开(公告)日：2016-03-08

    申请号：US14598137

    申请日：2015-01-15

    Applicant: Amazon Technologies, Inc.

    Inventor： Peter Sirota ,  Richard J. Cole ,  Vaibhav Aggarwal ,  Andrew J. Hitchcock ,  Jai Vasanth

    IPC: G06F15/177 ,  H04L12/28 ,  G06F9/48 ,  G06F9/50 ,  H04L29/08

    CPC classification number: G06F9/4881 ,  G06F9/5011 ,  G06F9/5061 ,  G06F2209/5011 ,  H04L67/10

    Abstract: Techniques are described for managing distributed execution of programs, including by dynamically scaling a cluster of multiple computing nodes performing ongoing distributed execution of a program, such as to increase and/or decrease computing node quantity. An architecture may be used that has core nodes that each participate in a distributed storage system for the distributed program execution, and that has one or more other auxiliary nodes that do not participate in the distributed storage system. Furthermore, as part of performing the dynamic scaling of a cluster, computing nodes that are only temporarily available may be selected and used, such as computing nodes that might be removed from the cluster during the ongoing program execution to be put to other uses and that may also be available for a different fee (e.g., a lower fee) than other computing nodes that are available throughout the ongoing use of the cluster.

    Abstract translation: 描述了用于管理程序的分布式执行的技术，包括通过动态地缩放执行程序的正在进行的分布式执行的多个计算节点的集群，例如增加和/或减少计算节点数量。 可以使用具有每个参与用于分布式程序执行的分布式存储系统的核心节点并且具有不参与分布式存储系统的一个或多个其他辅助节点的架构。 此外，作为执行群集的动态缩放的一部分，可以选择和使用仅临时可用的计算节点，例如在正在进行的程序执行期间可能从群集中移除的计算节点以被放置到其他用途， 也可能与在整个持续使用集群时可用的其他计算节点的费用不同（例如，较低的费用）可用。

    Use of temporarily available computing nodes for dynamic scaling of a cluster
    10.
    发明授权
    Use of temporarily available computing nodes for dynamic scaling of a cluster 有权
    使用临时可用的计算节点进行动态缩放的集群

    公开(公告)号：US08966030B1

    公开(公告)日：2015-02-24

    申请号：US14231435

    申请日：2014-03-31

    Applicant: Amazon Technologies, Inc.

    Inventor： Peter Sirota ,  Richard J. Cole ,  Vaibhav Aggarwal ,  Andrew J. Hitchcock ,  Jai Vasanth

    IPC: G06F15/177 ,  H04L29/08

    CPC classification number: G06F9/4881 ,  G06F9/5011 ,  G06F9/5061 ,  G06F2209/5011 ,  H04L67/10

    Abstract: Techniques are described for managing distributed execution of programs, including by dynamically scaling a cluster of multiple computing nodes performing ongoing distributed execution of a program, such as to increase and/or decrease computing node quantity. An architecture may be used that has core nodes that each participate in a distributed storage system for the distributed program execution, and that has one or more other auxiliary nodes that do not participate in the distributed storage system. Furthermore, as part of performing the dynamic scaling of a cluster, computing nodes that are only temporarily available may be selected and used, such as computing nodes that might be removed from the cluster during the ongoing program execution to be put to other uses and that may also be available for a different fee (e.g., a lower fee) than other computing nodes that are available throughout the ongoing use of the cluster.

    Abstract translation: 描述了用于管理程序的分布式执行的技术，包括通过动态地缩放执行程序的正在进行的分布式执行的多个计算节点的集群，例如增加和/或减少计算节点数量。 可以使用具有每个参与用于分布式程序执行的分布式存储系统的核心节点并且具有不参与分布式存储系统的一个或多个其他辅助节点的架构。 此外，作为执行群集的动态缩放的一部分，可以选择和使用仅临时可用的计算节点，例如在正在进行的程序执行期间可能从群集中移除的计算节点以被放置到其他用途， 也可能与在整个持续使用集群时可用的其他计算节点的费用不同（例如，较低的费用）可用。

Patent Agency Ranking