公开(公告)号：US20080005104A1

公开(公告)日：2008-01-03

申请号：US11427290

申请日：2006-06-28

Applicant: Gary W. Flake ,  William H. Gates ,  Eric J. Horvitz ,  Joshua T. Goodman ,  Surajit Chaudhuri ,  Trenholme J. Griffin ,  Oliver Hurst-Hiller ,  Kenneth A. Moss

Inventor： Gary W. Flake ,  William H. Gates ,  Eric J. Horvitz ,  Joshua T. Goodman ,  Surajit Chaudhuri ,  Trenholme J. Griffin ,  Oliver Hurst-Hiller ,  Kenneth A. Moss

IPC: G06F17/30

CPC classification number: G06Q30/02 ,  G06F16/9537

Abstract: A localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. Further, a system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.Another aspect of the disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user.

Abstract translation: 公开了一种本地化的营销系统，其提供与包括邻近度的商家标准匹配的用户的折扣优惠。 此外，可以采用用于主动探测具有不同参数和监测响应的用户群体的系统来收集数据以识别提供给用户以获得期望结果的最佳折扣和期限。 本公开的另一方面涉及网络搜索，并且更具体地涉及影响结果内容以增加相关性。 可以通过基于用户位置和/或上下文信息（例如，用户特征/简档，先前交互/使用时间，当前事件和第三方状态/上下文）重新配置查询和/或过滤结果来影响所得到的内容。 ）。 此外，本公开提供了在指定的web内容的至少一个子集上的查询执行，例如由用户指定的。

公开(公告)号：US07299226B2

公开(公告)日：2007-11-20

申请号：US10465148

申请日：2003-06-19

Applicant: Nicolas Bruno ,  Murali Krishna ,  Ming-Chuan Wu ,  Surajit Chaudhuri

Inventor： Nicolas Bruno ,  Murali Krishna ,  Ming-Chuan Wu ,  Surajit Chaudhuri

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30469 ,  G06F17/30333 ,  Y10S707/962 ,  Y10S707/99935 ,  Y10S707/99936 ,  Y10S707/99937

Abstract: A method of estimating cardinality of a join of tables using multi-column density values and additionally using coarser density values of a subset of the multi-column density attributes. In one embodiment, the subset of attributes for the coarser densities is a prefix of the set of multi-column density attributes. A number of tuples from each table that participate in the join may be estimated using densities of the subsets. The cardinality of the join can be estimated using the multi-column density for each table and the estimated number of tuples that participate in the join from each table.

Abstract translation: 使用多列密度值估计表连接的基数的方法，并且另外使用多列密度属性的子集的较粗密度值。 在一个实施例中，用于较粗密度的属性子集是多列密度属性集合的前缀。 可以使用子集的密度来估计参与加入的每个表中的一些元组。 可以使用每个表的多列密度和参与每个表的连接的元组的估计数量来估计连接的基数。

公开(公告)号：US07299220B2

公开(公告)日：2007-11-20

申请号：US10815061

申请日：2004-03-31

Applicant: Surajit Chaudhuri ,  Vivek Narasayya ,  Prasanna Ganesan

Inventor： Surajit Chaudhuri ,  Vivek Narasayya ,  Prasanna Ganesan

IPC: G06F17/30

CPC classification number: G06F17/30489 ,  G06F17/30306 ,  Y10S707/99932 ,  Y10S707/99934 ,  Y10S707/99935

Abstract: A database object summarization tool is provided that selects a subset of database objects subject to filtering constraints such as a partial order or optimization of some attribute. A dominance primitive filters out tuples that are dominated according to a partial order constraint by another tuple. A representation primitive selects a representative subset of tuples such than an optimization criteria is met.

Abstract translation: 提供了一种数据库对象摘要工具，该工具选择受过滤约束（如某些属性的部分顺序或优化）的数据库对象的子集。 优势原语过滤掉由另一个元组根据部分顺序约束所主导的元组。 表示基元选择满足优化标准的元组的代表性子集。

公开(公告)号：US07287019B2

公开(公告)日：2007-10-23

申请号：US10453992

申请日：2003-06-04

Applicant: Rahul Kapoor ,  Venkatesh Ganti ,  Surajit Chaudhuri

Inventor： Rahul Kapoor ,  Venkatesh Ganti ,  Surajit Chaudhuri

IPC: G06F17/30

CPC classification number: G06F17/30303 ,  G06F2216/03 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935 ,  Y10S707/99936

Abstract: A process for finding a similar data records from a set of data records. A database table or tables provide a number of data records from which one or more canonical data records are identified. Tokens are identified within the data records and classified according to attribute field. A similarity score is assigned to data records in relation to other data records based on a similarity between tokens of the data records. Data records whose similarity score with respect to each other is greater than a threshold form one or more groups of data records. The records or tuples form nodes of a graph wherein edges between nodes represent a similarity score between records of a group. Within each group a canonical record is identified based on the similarity of data records to each other within the group.

Abstract translation: 从一组数据记录中查找类似数据记录的过程。 数据库表或表提供了一些数据记录，从中可以识别一个或多个规范数据记录。 在数据记录中识别令牌，并根据属性字段进行分类。 基于数据记录的令牌之间的相似度，将相似性得分分配给与其他数据记录有关的数据记录。 其相似度相对于彼此的数据记录大于阈值形成一组或多组数据记录。 记录或元组形成图的节点，其中节点之间的边表示组之间的相似性得分。 在每个组内，基于数据记录在组内的彼此的相似性来识别规范记录。

公开(公告)号：US20060282436A1

公开(公告)日：2006-12-14

申请号：US11123901

申请日：2005-05-06

Applicant: Surajit Chaudhuri ,  Venkatesh Ganti ,  Kaushik Shriraghav

Inventor： Surajit Chaudhuri ,  Venkatesh Ganti ,  Kaushik Shriraghav

IPC: G06F7/00

CPC classification number: G06F17/30536 ,  Y10S707/99932

Abstract: A system that facilitates estimating functional relationships associated with one or more columns in a database comprises a sampling component that receives a random sample of records within the database. An estimate generator component calculates an estimate of strength of functional relationships based at least in part upon the received samples. For example, the estimate generator component can calculate an estimate of strength of a column as a key column based at least in part upon the received samples.

公开(公告)号：US20060282404A1

公开(公告)日：2006-12-14

申请号：US11149968

申请日：2005-06-10

Applicant: Surajit Chaudhuri ,  Ravishankar Ramamurthy ,  Kaushik Shriraghav

Inventor： Surajit Chaudhuri ,  Ravishankar Ramamurthy ,  Kaushik Shriraghav

IPC: G06F17/30

CPC classification number: G06F17/30522 ,  G06F17/30474 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99934 ,  Y10S707/99935

Abstract: Techniques for estimating the progress of database queries are described herein. In a first implementation, a respective lower-bound parameter is associated with each node in an operator tree that representing a given database query, and the progress of the database query at a given point is estimated based upon the lower-bound parameters. In a second implementation, the progress of the query is estimated by associating respective lower-bound and upper-bound parameters with each node in the operator tree. The progress of the query at the given point is then estimated based on the lower-bound and upper-bound parameters. The progress estimate is computed by dividing the work done so far by the sums of the above averages for each node in the tree.

Abstract translation: 本文描述了用于估计数据库查询的进度的技术。 在第一实现中，相应的下限参数与表示给定数据库查询的运算符树中的每个节点相关联，并且基于下限参数来估计给定点处的数据库查询的进度。 在第二个实现中，通过将相应的下限和上限参数与运算符树中的每个节点相关联来估计查询的进度。 然后，基于下限和上限参数估计给定点处的查询进度。 进度估计是通过将迄今为止完成的工作除以树中每个节点的上述平均值的总和来计算的。

公开(公告)号：US07149735B2

公开(公告)日：2006-12-12

申请号：US10603035

申请日：2003-06-24

Applicant: Surajit Chaudhuri ,  Venkatesh Ganti ,  Luis Gravano

Inventor： Surajit Chaudhuri ,  Venkatesh Ganti ,  Luis Gravano

IPC: G06F17/30

CPC classification number: G06F17/30985 ,  Y10S707/99936

Abstract: A method of estimating selectivity of a given string predicate in a database query. In the method selectivities of substrings of various substring lengths are estimated. For example, the selectivity of substrings between length l (or some constant q) to the length of the given string predicate may be estimated. The method then selects a candidate sub string for each sub string length based on estimated selectivities of the substrings. The estimated selectivities of the candidate substrings are combined. The combined estimated selectivity of the candidate substrings is returned as the estimated selectivity of the given string predicate.

Abstract translation: 在数据库查询中估计给定字符串谓词的选择性的方法。 在方法中，估计各种子串长度的子串的选择性。 例如，可以估计长度l（或一些常数q）与给定字符串谓词的长度之间的子串的选择性。 然后，该方法基于所估计的子串的选择性来选择每个子串长度的候选子串。 合并候选子串的估计选择性。 候选子串的组合估计选择性作为给定字符串谓词的估计选择性返回。

公开(公告)号：US20060242102A1

公开(公告)日：2006-10-26

申请号：US11111015

申请日：2005-04-21

Applicant: Nicolas Bruno ,  Surajit Chaudhuri

Inventor： Nicolas Bruno ,  Surajit Chaudhuri

IPC: G06F17/30

CPC classification number: G06F16/22

Abstract: A system that facilitates automatic selection of a physical configuration of a database comprises an optimizer component that determines simulated physical structures and creates a hypothetical configuration based thereon. A reduction component progressively reduces size of the configuration until the hypothetical configuration is associated with a size below a threshold. For example, the simulated physical structures can be based at least in part upon a workload.

Abstract translation: 促进数据库的物理配置的自动选择的系统包括确定模拟物理结构并基于此创建假设配置的优化器组件。 缩减组件逐渐减小配置的大小，直到假设配置与小于阈值的大小相关联。 例如，模拟的物理结构可以至少部分地基于工作负载。

公开(公告)号：US20060085484A1

公开(公告)日：2006-04-20

申请号：US10966563

申请日：2004-10-15

Applicant: Alexander Raizman ,  Arunprasad Marathe ,  Djana Milton ,  Dmitry Sonkin ,  Lubor Kollar ,  Maciej Sarnowicz ,  Manoj Syamala ,  Raja Duddupudi ,  Sanjay Agrawal ,  Surajit Chaudhuri ,  Vivek Narasayya

Inventor： Alexander Raizman ,  Arunprasad Marathe ,  Djana Milton ,  Dmitry Sonkin ,  Lubor Kollar ,  Maciej Sarnowicz ,  Manoj Syamala ,  Raja Duddupudi ,  Sanjay Agrawal ,  Surajit Chaudhuri ,  Vivek Narasayya

IPC: G06F17/30

CPC classification number: G06F16/2282 ,  G06F16/2272

Abstract: An automated physical database design tool may provide an integrated physical design recommendation for horizontal partitioning, indexes and indexed views, all three features being tuned together (in concert). Manageability requirements may be specified when optimizing for performance. User-specified configuration may enable the specification of a partial physical design without materialization of the physical design. The tuning process may be performed for a production server but may be conducted substantially on a test server. Secondary indexes may be suggested for XML columns. Tuning of a database may be invoked by any owner of a database. Usage of objects may be evaluated and a recommendation for dropping unused objects may be issued. Reports may be provided concerning the count and percentage of queries in the workload that reference a particular database, and/or the count and percentage of queries in the workload that reference a particular table or column. A feature may be provided whereby a weight may be associated with each statement in the workload, enabling relative importance of particular statements to be specified. An in-row length for a column may be specified. If a value for the column exceeds the specified in-row length for that column, the portion of the value not exceeding the specified in-row length may be stored in the row while the portion of the value exceeding the specified in-row length may be stored in an overflow area. Rebuild and reorganization recommendations may be generated.

Abstract translation: 自动化物理数据库设计工具可以为水平划分，索引和索引视图提供集成的物理设计建议，所有这三个特征被一起调谐（一致）。 在优化性能时可以指定可管理性要求。 用户指定的配置可以实现部分物理设计的规范，而不会实现物理设计。 可以对生产服务器执行调整过程，但是可以基本上在测试服务器上进行。 可以针对XML列建议辅助索引。 数据库的任何拥有者都可以调用数据库。 可以评估对象的使用，并且可以发出用于丢弃未使用对象的建议。 可以提供关于引用特定数据库的工作负载中的查询的计数和百分比的报告，和/或引用特定表或列的工作负载中的查询的计数和百分比。 可以提供特征，其中权重可以与工作负载中的每个语句相关联，使得能够指定特定语句的相对重要性。 可以指定列的行内长度。 如果列的值超过该列的指定行内长度，则不超过指定行内长度的部分可能存储在行中，而超出指定行内长度的值的部分可能会 存储在溢出区域。 可能会生成重建和重组建议。

公开(公告)号：US20060085410A1

公开(公告)日：2006-04-20

申请号：US11296036

申请日：2005-12-07

Applicant: Surajit Chaudhuri ,  Vivek Narasayya ,  Rajeev Motwani ,  Mayur Datar

Inventor： Surajit Chaudhuri ,  Vivek Narasayya ,  Rajeev Motwani ,  Mayur Datar

IPC: G06F17/30

CPC classification number: G06F17/30536 ,  G06F17/30489 ,  Y10S707/99931 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99942

Abstract: A method of estimating the Results of a database query are estimated by performing a sampling of weighted tuples in a database based on a probability of usage of tuples required in executing a workload. A probability is associated with each tuple sampled. And, can aggregate is computed over values in each sampled tuple while multiplying by the inverses of the probabilities associated with each tuple sampled.

Abstract translation: 通过基于执行工作负载所需的元组的使用概率，对数据库中的加权元组进行抽样来估计估计数据库查询结果的方法。 每个元组采样的概率相关。 并且，可以在每个采样的元组中的值上计算可以聚合，同时乘以与每个元组采样相关联的概率的逆。