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    • 22. 发明申请
    • PARTITION/TABLE ALLOCATION ON DEMAND
    • 分配/表分配需求
    • US20080313209A1
    • 2008-12-18
    • US11764131
    • 2007-06-15
    • Shrikanth ShankarAnanth RaghavanBadhri G. Varanasi
    • Shrikanth ShankarAnanth RaghavanBadhri G. Varanasi
    • G06F17/30G06F12/02
    • G06F17/30312G06F17/30486
    • A method and apparatus for the on-demand allocation of segments and creation of metadata for previously-created data storage spaces and partitions are provided. A space is created in a database. As part of this creation process, no segment is allocated for the space. Rather, metadata describing the space sufficiently to allocate the segment in the future is created and maintained by the database. Data is received indicating a new item. Based on the metadata, it is determined that the new item pertains to the space. In response to the determination, a segment is allocated for the space. Additional metadata necessary for normal database operations in relation to the space and newly-allocated segment may also be created at this time. The new item can then be stored in the space.
    • 提供了用于按需分配段并且为先前创建的数据存储空间和分区创建元数据的方法和装置。 在数据库中创建一个空格。 作为此创建过程的一部分,没有为该空间分配段。 相反,由数据库创建和维护描述足够分配该段的空间的元数据。 收到指示新项目的数据。 基于元数据,确定新项目与空间有关。 响应于确定,为该空间分配段。 此时也可以创建与空间和新分配段相关的正常数据库操作所需的附加元数据。 然后可以将新项目存储在空间中。
    • 26. 发明申请
    • Optimizing execution of a database query by using the partitioning schema of a partitioned object to select a subset of partitions from another partitioned object
    • 通过使用分区对象的分区方案来优化数据库查询的执行,以从另一个分区对象中选择分区的一个子集
    • US20050251511A1
    • 2005-11-10
    • US10857651
    • 2004-05-28
    • Shrikanth ShankarVikram Shukla
    • Shrikanth ShankarVikram Shukla
    • G06F7/00G06F17/30
    • G06F17/30454Y10S707/99933Y10S707/99934Y10S707/99935
    • One embodiment of the present invention provides a system that optimizes the execution of a database query involving a target partitioned-database-object. During system operation, the database receives a query. If the query has a predicate that includes a partition-mapping function that uses the partitioning schema of a partitioned database-object and a list of columns from one or more tables to express a mapping of the list of column values to the partitions of the partitioned database-object, the system determines the compatibility of the partitioning schemas of the target partitioned-database-object and the partitioned database-object. Next, if the partitioning schemas are compatible, and if the list of columns is compatible with the partitioning keys of the target partitioned-database-object and the partitioned database-object, the system attempts to identify a subset of partitions in the target partitioned-database-object that satisfy the predicate. Finally, if a subset of partitions is successfully identified, the system performs the query only on the identified subset of partitions, and not on the other partitions, thereby optimizing the execution of the query by reducing the number of partitions that need to be accessed.
    • 本发明的一个实施例提供了一种优化涉及目标分区数据库对象的数据库查询的执行的系统。 在系统操作期间,数据库接收查询。 如果查询具有包含分区映射函数的谓词,该函数使用分区数据库对象的分区模式和一个或多个表中的列列表,以将列值列表映射到分区的分区 数据库对象,系统确定目标分区数据库对象与分区数据库对象的分区模式的兼容性。 接下来,如果分区模式是兼容的,并且如果列列表与目标分区数据库对象和分区数据库对象的分区密钥兼容,则系统尝试识别目标分区数据库对象中的分区子集, 满足谓词的数据库对象。 最后,如果分区的子集被成功识别,则系统仅对所识别的分区子集执行查询,而不在其他分区上执行查询,从而通过减少需要访问的分区数来优化查询的执行。
    • 29. 发明申请
    • Systems and Methods for Auto-Scaling a Big Data System
    • 自动缩放大数据系统的系统和方法
    • US20160048415A1
    • 2016-02-18
    • US14459631
    • 2014-08-14
    • Joydeep Sen SarmaMayank AhujaSivaramakrishnan NarayananShrikanth Shankar
    • Joydeep Sen SarmaMayank AhujaSivaramakrishnan NarayananShrikanth Shankar
    • G06F9/50
    • G06F9/5083G06F9/5072
    • Systems and methods for automatically scaling a big data system are disclosed. Methods may include: determining, at a first time, a first optimal number of nodes for a cluster to adequately process a request; assigning an amount of nodes equal to the first optimal number; determining a rate of progress of the request; determining, at a second time based on the rate of progress a second optimal number of nodes; and modifying the number of nodes assigned to the cluster to equal the second optimal number. Systems may include: a cluster manager, to add and/or remove nodes; a big data system, to process requests that utilize the cluster and nodes, and an automatic scaling cluster manager, including: a big data interface, for communicating with the big data system; a cluster manager interface, for communicating with a cluster manager instructions for adding and/or removing nodes from a cluster used to process a request; and a cluster state machine.
    • 公开了用于自动缩放大数据系统的系统和方法。 方法可以包括:在第一时间确定簇的第一最佳数量的节点以充分地处理请求; 分配等于第一最优数的节点数; 确定请求的进度; 基于所述进展速度在第二时间确定第二最佳数量的节点; 以及修改分配给所述集群的节点数量等于所述第二最佳数量。 系统可以包括:群集管理器,用于添加和/或移除节点; 一个大数据系统,用于处理利用集群和节点的请求,以及一个自动扩展集群管理器,包括:一个大数据接口,用于与大数据系统进行通信; 集群管理器接口,用于与集群管理器通信用于从用于处理请求的集群中添加和/或移除节点的指令; 和集群状态机。