公开(公告)号：US09064364B2

公开(公告)日：2015-06-23

申请号：US10690778

申请日：2003-10-22

Applicant: Naoki Abe ,  Carl E. Abrams ,  Chidanand V. Apte ,  Bishwaranjan Bhattacharjee ,  Kenneth A. Goldman ,  Matthias Gruetzner ,  Matthew A. Hilbert ,  John Langford ,  Sriram K. Padmanabhan ,  Charles P. Tresser ,  Kathleen M. Troidle ,  Philip S. Yu

Inventor： Naoki Abe ,  Carl E. Abrams ,  Chidanand V. Apte ,  Bishwaranjan Bhattacharjee ,  Kenneth A. Goldman ,  Matthias Gruetzner ,  Matthew A. Hilbert ,  John Langford ,  Sriram K. Padmanabhan ,  Charles P. Tresser ,  Kathleen M. Troidle ,  Philip S. Yu

IPC: G06Q20/02 ,  G07F7/10 ,  G06F21/62 ,  G06F21/72 ,  G06Q20/34 ,  G07F19/00

CPC classification number: G06Q20/4016 ,  G06F21/121 ,  G06F21/602 ,  G06F21/6218 ,  G06F21/6245 ,  G06F21/72 ,  G06F2221/07 ,  G06F2221/2101 ,  G06Q20/341 ,  G06Q20/3829 ,  G06Q2220/00 ,  G07F7/1008 ,  G07F7/1083 ,  G07F19/207 ,  H04L63/04

Abstract: Various embodiments for maintaining security and confidentiality of data and operations within a fraud detection system. Each of these embodiments utilizes a secure architecture in which: (1) access to data is limited to only approved or authorized entities; (2) confidential details in received data can be readily identified and concealed; and (3) confidential details that have become non-confidential can be identified and exposed.

Abstract translation: 用于维护欺诈检测系统内的数据和操作的安全性和机密性的各种实施例。 这些实施例中的每一个都利用安全架构，其中：（1）对数据的访问仅限于批准或授权的实体; （2）接收到的数据的机密细节可以很容易地识别和隐藏; 和（3）可以识别和暴露出非机密的机密细节。

公开(公告)号：US08990173B2

公开(公告)日：2015-03-24

申请号：US12056979

申请日：2008-03-27

Applicant: Bishwaranjan Bhattacharjee ,  Lipyeow Lim ,  Timothy Ray Malkemus ,  George Andrei Mihaila

Inventor： Bishwaranjan Bhattacharjee ,  Lipyeow Lim ,  Timothy Ray Malkemus ,  George Andrei Mihaila

IPC: G06F7/00 ,  H03M7/30

CPC classification number: H03M7/30

Abstract: Techniques are disclosed for selecting a delete-safe compression method for a plurality of delta encoded data values (e.g., delta encoded integers or deltas). For example, a computer-implemented method for selecting an optimal delete-safe compression algorithm from among two or more compression algorithms for use on a plurality of delta encoded data values includes the following steps. The maximum number of data values eliminated by each of the two or more compression algorithms is computed. For the plurality of delta encoded data values to be compressed, the minimum size of the plurality of delta encoded data values before compression thereof is computed. A delete-safe threshold value is computed based on the minimum size of the plurality of delta encoded data values. Then, the compression algorithm is selected from the two or more compression algorithms that achieves the delete-safe threshold value.

Abstract translation: 公开了用于为多个增量编码的数据值（例如，增量编码的整数或三角形）选择删除安全的压缩方法的技术。 例如，用于从用于多个增量编码数据值的两个或更多个压缩算法中选择最佳删除安全压缩算法的计算机实现的方法包括以下步骤。 计算由两个或更多个压缩算法中的每一个消除的数据值的最大数目。 对于要压缩的多个delta编码数据值，计算其压缩之前的多个Δ编码数据值的最小大小。 基于多个增量编码数据值的最小大小来计算删除安全阈值。 然后，从实现删除安全​​阈值的两个或更多个压缩算法中选择压缩算法。

公开(公告)号：US08458191B2

公开(公告)日：2013-06-04

申请号：US12724211

申请日：2010-03-15

Applicant: Bishwaranjan Bhattacharjee ,  Kavitha Srinivas ,  Octavian Udrea

Inventor： Bishwaranjan Bhattacharjee ,  Kavitha Srinivas ,  Octavian Udrea

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30595

Abstract: A method (and structure) of storing schema-less data of a dataset in a relational database, includes constructing a hash table for the schema-less data, using a processor on a computer. Data in the dataset is stored in a tuple format including a subject along with at least one other entity associated to the subject. Each row of the hashtable will be dedicated to a subject of the dataset, and at least one of the at least one other entity associated with the subject in the row is to be stored in a pair-wise manner in that row of the hashtable. In an exemplary embodiment, RDF data that uses triples (subject, predicate, object) is stored with the predicate/object stored in the pair-wise manner in its associated subject row.

Abstract translation: 一种在关系数据库中存储数据集的无模式数据的方法（和结构）包括使用计算机上的处理器来构建无模式数据的散列表。 数据集中的数据以包含主题的元组格式以及至少一个与对象关联的其他实体存储。 哈希表的每一行将专用于数据集的主题，并且与行中的主题相关联的至少一个其他实体中的至少一个将以成对方式存储在散列表的该行中。 在示例性实施例中，使用三元组（主题，谓词，对象）的RDF数据与以关联对象行中的成对方式存储的谓词/对象一起存储。

公开(公告)号：US07516117B2

公开(公告)日：2009-04-07

申请号：US11509050

申请日：2006-08-24

Applicant: Bishwaranjan Bhattacharjee ,  Timothy Ray Malkemus ,  Ioana Roxana Stanoi

Inventor： Bishwaranjan Bhattacharjee ,  Timothy Ray Malkemus ,  Ioana Roxana Stanoi

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30442 ,  Y10S707/99932 ,  Y10S707/99933

Abstract: A method for accelerating range queries using periodic monotonic properties of non-monotonic functions including mapping a base column x to an existing index on a column y that is correlated with column x through a periodic piecewise monotonic function F(x), rewriting an index construction statement to force the existing index on column y to track a periodic piecewise monotonic property by assigning identical values of F(x) to different periods to different ranges to create an annotated index, and rewriting range queries over the annotated index on F(x) by modifying a derived predicate.

Abstract translation: 一种使用非单调函数的周期性单调性质加速范围查询的方法，包括通过周期性片段单调函数F（x）将基列x映射到与列x相关的列y上的现有索引，重写索引结构 声明强制列y上的现有索引通过将相同的F（x）值分配给不同的周期到不同的范围来跟踪周期性片段单调属性来创建注释索引，并通过F（x）上的注释索引重写范围查询， 通过修改派生谓词。

公开(公告)号：US20080208802A1

公开(公告)日：2008-08-28

申请号：US11679076

申请日：2007-02-26

Applicant: Bishwaranjan Bhattacharjee ,  Timothy Ray Malkemus ,  Sean W. McKeough ,  Jo-anne Mona Louise Kirton ,  Sherman Lau

Inventor： Bishwaranjan Bhattacharjee ,  Timothy Ray Malkemus ,  Sean W. McKeough ,  Jo-anne Mona Louise Kirton ,  Sherman Lau

IPC: G06F17/30

CPC classification number: G06F17/30327

Abstract: A method and system utilizes a hierarchical bitmap structure to represent deleted data sets. Each level in the hierarchical bitmap structure may have progressively larger size and represent finer granularity of number of data blocks than its parent level. A method in one aspect may comprise allocating a first level bitmap having size equal to a register on a processor, each bit in the first level bitmap representing a plurality of blocks of data in a database, and allocating one or more pointers corresponding to said plurality of bits in the first level bitmap, said one or more pointers being allocated to point to a sub bitmap generated after a data block is deleted but before the index corresponding to the data block is cleaned.

Abstract translation: 一种方法和系统利用分层位图结构来表示删除的数据集。 分级位图结构中的每个级别可以具有逐渐更大的大小并且表示比其父级别更多的数据块的粒度。 一方面的方法可以包括：分配具有等于处理器上的寄存器的大小的第一级位图，第一级位图中的每一位表示数据库中的多个数据块，并且分配与所述多个对应的一个或多个指针 所述一个或多个指针被分配以指向在数据块被删除之后但在与数据块相对应的索引被清除之前生成的子位图。

公开(公告)号：US07236974B2

公开(公告)日：2007-06-26

申请号：US10425760

申请日：2003-04-29

Applicant: Bishwaranjan Bhattacharjee ,  Leslie A. Cranston ,  Matthew A. Huras ,  Timothy R. Malkemus ,  Catherine S. McArthur ,  Sriram K. Padmanabhan ,  Michael J. Winer

Inventor： Bishwaranjan Bhattacharjee ,  Leslie A. Cranston ,  Matthew A. Huras ,  Timothy R. Malkemus ,  Catherine S. McArthur ,  Sriram K. Padmanabhan ,  Michael J. Winer

IPC: G06F17/30

CPC classification number: G06F17/30592 ,  G06F17/30362 ,  Y10S707/99932 ,  Y10S707/99938 ,  Y10S707/99939

Abstract: A multi-level locking hierarchy for a relational database includes a locking level applied to a multi-dimensionally clustering table, a locking level applied to blocks within the table, and a locking level applied to rows within the blocks. The hierarchy leverages the multi-dimensional clustering of the table data for efficiency and to reduce lock overhead. Data is normally locked in order of coarser to finer granularity to limit deadlock. When data of finer granularity is locked, data of coarser granularity containing the finer granularity data is also locked. Block lock durations may be employed to ensure that a block remains locked if any contained row remains locked. Block level lock attributes may facilitate detection of at least one of a concurrent scan and a row deletion within a block. Detection of the emptying of a block during a scan of the block may bar scan completion in that block.

Abstract translation: 关系数据库的多级锁定层次结构包括应用于多维聚类表的锁定级别，应用于表中块的锁定级别以及应用于块内的行的锁定级别。 层次结构利用表数据的多维聚类来提高效率并减少锁定开销。 数据通常以更细和更细粒度的顺序锁定，以限制死锁。 当更细粒度的数据被锁定时，包含更细粒度数据的较粗粒度的数据也被锁定。 可以使用块锁定持续时间来确保如果任何包含的行保持锁定，则块保持锁定。 块级锁定属性可以有助于检测块内的并行扫描和行删除中的至少一个。 在块的扫描期间检测块的排空可能会阻止该块中的扫描完成。

公开(公告)号：US07080081B2

公开(公告)日：2006-07-18

申请号：US10122502

申请日：2002-04-15

Applicant: Ramesh C. Agarwal ,  Bishwaranjan Bhattacharjee ,  Leslie A. Cranston ,  Matthew A. Huras ,  Tony Wen Hsun Lai ,  Timothy R. Malkemus ,  Sriram K. Padmanabhan

Inventor： Ramesh C. Agarwal ,  Bishwaranjan Bhattacharjee ,  Leslie A. Cranston ,  Matthew A. Huras ,  Tony Wen Hsun Lai ,  Timothy R. Malkemus ,  Sriram K. Padmanabhan

IPC: G06F7/00

CPC classification number: G06F17/30592 ,  Y10S707/954 ,  Y10S707/957

Abstract: Multidimensional clustered tables are provided for efficient processing and management in a relational database management system. A multidimensional clustered table is one whose data is simultaneously clustered along one or more independent dimensions, or clustering keys, and physically organized into blocks or pages on disk. When such a table is created, one can specify one or more keys as dimensions along which to cluster the table's data. Each of the dimensions can consist of one or more columns. Further provided are efficient query processing and maintenance techniques for use in conjunction with multidimensional clustered tables.

Abstract translation: 提供了多维集群表，用于在关系数据库管理系统中进行有效的处理和管理。 一个多维集群表是一个数据同时沿着一个或多个独立维度或聚类键进行聚类，并在物理上组织成磁盘上的块或页面。 创建此类表时，可以将一个或多个键指定为将数据集合在一起的维度。 每个维度可以由一个或多个列组成。 还提供了与多维集群表一起使用的有效的查询处理和维护技术。

公开(公告)号：US09165021B2

公开(公告)日：2015-10-20

申请号：US12423247

申请日：2009-04-14

Applicant: Bishwaranjan Bhattacharjee ,  Mustafa Canim ,  George Andrei Mihaila

Inventor： Bishwaranjan Bhattacharjee ,  Mustafa Canim ,  George Andrei Mihaila

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30312 ,  G06F17/30424 ,  G06F17/30864

Abstract: A method, information processing system, and computer program storage product optimize the placement of database objects on a multiplicity of storage devices. A set of database objects are placed on a first storage device in a multiplicity of storage devices. Each storage device comprises differing characteristics. A query workload is run on the set of database objects that have been placed on the first storage device. Profiling information associated with the query workload that is running is collected. A subset of database objects is selected from the set of the database objects to be stored on a second storage device. The second storage device is a separate physical device from, and performs faster than, the first storage device. The subset of database objects is stored on the second storage device and all remaining database objects in the set of database objects on the first storage device.

Abstract translation: 一种方法，信息处理系统和计算机程序存储产品优化数据库对象在多个存储设备上的放置。 一组数据库对象被放置在多个存储设备中的第一存储设备上。 每个存储设备包括不同的特征。 在已经放置在第一个存储设备上的数据库对象集上运行查询工作负载。 收集与正在运行的查询工作负载相关联的分析信息。 从要存储在第二存储设备上的数据库对象的集合中选择数据库对象的子集。 第二存储设备是与第一存储设备不同的并且执行得比第一存储设备更快的单独的物理设备。 数据库对象的子集存储在第二存储设备上，并且存储在第一存储设备上的数据库对象集合中的所有剩余的数据库对象。

公开(公告)号：US08126929B2

公开(公告)日：2012-02-28

申请号：US12057012

申请日：2008-03-27

Applicant: Bishwaranjan Bhattacharjee ,  Lipyeow Lim ,  Timothy Ray Malkemus ,  George Andrei Mihaila

Inventor： Bishwaranjan Bhattacharjee ,  Lipyeow Lim ,  Timothy Ray Malkemus ,  George Andrei Mihaila

IPC: G06F17/30

CPC classification number: G06F17/30958 ,  G06F17/30286

Abstract: Techniques are disclosed for encoding a variable length structure such that it facilitates forward and reverse scans of a list of such structures as needed. While the techniques are applicable to a wide variety of applications, they are particularly well-suited for use with structures such as those found in compressed database indexes. For example, a computer-implemented method for processing one or more variable length data structures includes the following steps. Each variable length data structure is obtained. Each variable length structure comprises one or more data block. A variable length encoding process is applied to the one or more blocks of each variable length data structure which comprises setting a continuation data value in each block to a first value or a second value, wherein the setting of the continuation data values enables bi-directional scanning of each variable length structure.

Abstract translation: 公开了用于编码可变长度结构的技术，使得其有助于正向和反向扫描所需的这种结构的列表。 虽然这些技术适用于各种各样的应用，但它们特别适用于诸如在压缩数据库索引中发现的结构。 例如，用于处理一个或多个可变长度数据结构的计算机实现的方法包括以下步骤。 获得每个可变长度数据结构。 每个可变长度结构包括一个或多个数据块。 可变长度编码处理被应用于每个可变长度数据结构的一个或多个块，其包括将每个块中的连续数据值设置为第一值或第二值，其中，连续数据值的设置允许双向 扫描每个可变长度结构。

公开(公告)号：US07937541B2

公开(公告)日：2011-05-03

申请号：US11548889

申请日：2006-10-12

Applicant: Bishwaranjan Bhattacharjee ,  Christian A. Lang ,  Timothy R. Malkemus ,  Sriram Padmanabhan ,  Kwai Wong

Inventor： Bishwaranjan Bhattacharjee ,  Christian A. Lang ,  Timothy R. Malkemus ,  Sriram Padmanabhan ,  Kwai Wong

IPC: G06F12/06

CPC classification number: G06F12/0866 ,  G06F12/123 ,  G06F17/30448

Abstract: Disclosed are a method, information processing system, and computer readable medium for scanning a storage medium table. The method includes retrieving location information associated with at least one other storage medium table scan. A storage medium table scan is started at a location within a storage medium table based on at least a location of the one other storage medium table scan. A weight is assigned to at least one storage medium block based on at least a current scanning location within the storage medium table relative to the location of the one other table scan. The method determines if a distance between the current scanning location and the location of the one other table scan is greater than a first given threshold. A current scanning operation is delayed, in response to the distance being greater than the given threshold, until the distance is below a second given threshold.

Abstract translation: 公开了一种用于扫描存储介质表的方法，信息处理系统和计算机可读介质。 该方法包括检索与至少一个其他存储介质表扫描相关联的位置信息。 基于至少另一个存储介质表扫描的位置，在存储介质表中的位置处开始存储介质表扫描。 基于至少一个存储介质表中的当前扫描位置相对于另一个表扫描的位置，将权重分配给至少一个存储介质块。 该方法确定当前扫描位置与另一个表扫描的位置之间的距离是否大于第一给定阈值。 响应于距离大于给定阈值，当前扫描操作被延迟，直到距离低于第二给定阈值。