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    DYNAMIC DATA SET REPLICA MANAGEMENT
    11.
    发明申请
    DYNAMIC DATA SET REPLICA MANAGEMENT 审中-公开
    动态数据集复制管理

    公开(公告)号：US20150019829A1

    公开(公告)日：2015-01-15

    申请号：US14500553

    申请日：2014-09-29

    Applicant: Amazon Technologies, Inc.

    Inventor： Swaminathan Sivasubramanian ,  Bradley E. Marshall ,  Tate Andrew Certain ,  Nicholas J. Maniscalco

    IPC: G06F3/06

    CPC classification number: G06F3/061 ,  G06F3/065 ,  G06F3/0665 ,  G06F3/067 ,  G06F17/30575 ,  G06F17/30595 ,  G06F17/30607 ,  G06F2003/0692

    Abstract: Systems and methods dynamically manage replicas of data sets. A collection of data stores is used to redundantly store one or more replicas of one or more data sets. The replicas may be used to respond to read requests from multiple sources. Upon identification of a need to allocate storage space to a data object, space used by one or more of the replicas is allocated to the data object. Various parameters may be utilized in the selection of one or more replicas whose storage space can be allocated to the data object. The parameters may be based at least in part on characteristics of the one or more data sets relative to one another.

    Abstract translation: 系统和方法动态管理数据集的副本。 数据存储的集合用于冗余地存储一个或多个数据集的一个或多个副本。 复制品可用于响应来自多个来源的读取请求。 在识别需要向数据对象分配存储空间时，一个或多个副本使用的空间被分配给数据对象。 可以在选择一个或多个可以将数据对象分配存储空间的副本时使用各种参数。 参数可以至少部分地基于一个或多个数据集相对于彼此的特性。

    SPECULATIVE READS
    12.
    发明申请
    SPECULATIVE READS 审中-公开
    参考阅读

    公开(公告)号：US20140365732A1

    公开(公告)日：2014-12-11

    申请号：US14468270

    申请日：2014-08-25

    Applicant: Amazon Technologies, Inc.

    Inventor： Swaminathan Sivasubramanian ,  Bradley Eugene Marshall ,  Tate Andrew Certain ,  Nicholas J. Maniscalco

    IPC: G06F12/08 ,  G06F9/38

    CPC classification number: G06F12/0862 ,  G06F9/38 ,  G06F9/3832 ,  G06F9/3863 ,  G06F12/0866 ,  G06F2212/6026

    Abstract: Patterns of access and/or behavior can be analyzed and persisted for use in pre-fetching data from a physical storage device. In at least some embodiments, data can be aggregated across volumes, instances, users, applications, or other such entities, and that data can be analyzed to attempt to determine patterns for any of those entities. The patterns and/or analysis can be persisted such that the information is not lost in the event of a reboot or other such occurrence. Further, aspects such as load and availability across the network can be analyzed to determine where to send and/or store data that is pre-fetched from disk or other such storage in order to reduce latency while preventing bottlenecks or other such issues with resource availability.

    Abstract translation: 访问和/或行为的模式可以被分析和持久化，以用于从物理存储设备预取数据。 在至少一些实施例中，数据可以跨卷，实例，用户，应用程序或其他此类实体进行聚合，并且可以分析数据以尝试确定任何这些实体的模式。 可以保持模式和/或分析，使得在重新启动或其他此类事件的情况下信息不会丢失。 此外，可以分析诸如网络上的负载和可用性之类的方面以确定在哪里发送和/或存储从磁盘或其他此类存储器预取的数据，以便在防止瓶颈或其他此类问题的资源可用性的同时减少延迟 。

    Speculative reads
    18.
    发明授权
    Speculative reads 有权
    推测阅读

    公开(公告)号：US08819390B1

    公开(公告)日：2014-08-26

    申请号：US13794616

    申请日：2013-03-11

    Applicant: Amazon Technologies, Inc.

    Inventor： Swaminathan Sivasubramanian ,  Bradley Eugene Marshall ,  Tate Andrew Certain ,  Nicholas J. Maniscalco

    IPC: G06F12/00 ,  G06F13/00 ,  G06F13/28 ,  G06F9/26 ,  G06F9/34 ,  G06F15/16 ,  G06F12/08 ,  G06F9/38 ,  G06F12/02

    CPC classification number: G06F12/0862 ,  G06F9/38 ,  G06F9/3832 ,  G06F9/3863 ,  G06F12/0866 ,  G06F2212/6026

    Abstract: Patterns of access and/or behavior can be analyzed and persisted for use in pre-fetching data from a physical storage device. In at least some embodiments, data can be aggregated across volumes, instances, users, applications, or other such entities, and that data can be analyzed to attempt to determine patterns for any of those entities. The patterns and/or analysis can be persisted such that the information is not lost in the event of a reboot or other such occurrence. Further, aspects such as load and availability across the network can be analyzed to determine where to send and/or store data that is pre-fetched from disk or other such storage in order to reduce latency while preventing bottlenecks or other such issues with resource availability.

    Abstract translation: 访问和/或行为的模式可以被分析和持久化，以用于从物理存储设备预取数据。 在至少一些实施例中，数据可以跨卷，实例，用户，应用程序或其他此类实体进行聚合，并且可以分析数据以尝试确定任何这些实体的模式。 可以保持模式和/或分析，使得在重新启动或其他此类事件的情况下信息不会丢失。 此外，可以分析诸如网络上的负载和可用性之类的方面以确定在哪里发送和/或存储从磁盘或其他此类存储器预取的数据，以便在防止瓶颈或其他此类问题的资源可用性的同时减少延迟 。

    Load rebalancing for shared resource
    19.
    发明授权
    Load rebalancing for shared resource 有权
    负载重新平衡共享资源

    公开(公告)号：US08769238B1

    公开(公告)日：2014-07-01

    申请号：US13896223

    申请日：2013-05-16

    Applicant: Amazon Technologies, Inc.

    Inventor： Swaminathan Sivasubramanian ,  Bradley Eugene Marshall ,  Tate Andrew Certain ,  Nicholas J. Maniscalco

    IPC: G06F12/00 ,  G06F13/00 ,  G06F13/28 ,  G06F9/46

    CPC classification number: G06F9/5077 ,  G06F3/06 ,  G06F3/0613 ,  G06F3/0647 ,  G06F3/067 ,  G06F9/5083 ,  G06F13/00 ,  G06F13/28

    Abstract: Various aspects of a data volume or other shared resource are determined and updated dynamically for purposes such as to provide guaranteed qualities of services. For example, the number of partitions in a data volume and/or the way in which data is stored across those partitions can be updated dynamically without significantly impacting the customer using the volume. The data stored to the volume can be striped or otherwise distributed across a number of logical areas, which then can be distributed across the partitions. Separate mappings can be used for the data in each logical area, and the logical areas in each partition, such that when moving a logical area only a single mapping has to be updated, regardless of the amount of data in that logical area. Further, logical areas can be moved between partitions without the need to repartition or redistribute the data in the data volume.

    Abstract translation: 数据卷或其他共享资源的各个方面被动态地确定和更新，以便提供保证的服务质量。 例如，数据卷中的分区数量和/或跨这些分区存储数据的方式可以动态更新，而不会对使用该卷的客户造成明显的影响。 存储到卷的数据可以被分段或分布在多个逻辑区域上，然后可以分布在分区上。 可以对每个逻辑区域中的数据和每个分区中的逻辑区域使用单独的映射，使得当移动逻辑区域时，只需要更新单个映射，而不管该逻辑区域中的数据量如何。 此外，逻辑区域可以在分区之间移动，而不需要重新分区或重新分发数据卷中的数据。

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