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    • 8. 发明申请
    • Merging synopses to determine number of distinct values in large databases
    • 合并摘要以确定大型数据库中不同值的数量
    • US20080120275A1
    • 2008-05-22
    • US11796110
    • 2007-04-25
    • Thierry CruanesUri ShaftHong SuBenoit DagevilleSunil P. ChakkappenMohamed Zait
    • Thierry CruanesUri ShaftHong SuBenoit DagevilleSunil P. ChakkappenMohamed Zait
    • G06F17/30
    • G06F17/30442Y10S707/99931Y10S707/99943Y10S707/99945
    • A method and apparatus for merging synopses to determine a database statistic, e.g., a number of distinct values (NDV), is disclosed. The merging can be used to determine an initial database statistic or to perform incremental statistics maintenance. For example, each synopsis can pertain to a different partition, such that merging the synopses generates a global statistic. When performing incremental maintenance, only those synopses whose partitions have changed need to be updated. Each synopsis contains domain values that summarize the statistic. However, the synopses may initially contain domain values that are not compatible with each other. Prior to merging the synopses the domain values in each synopsis is made compatible with the domain values in the other synopses. The adjustment is made such that each synopsis represents the same range of domain values, in one embodiment. After “compatible synopses” are formed, the synopses are merged by taking the union of the compatible synopses.
    • 公开了用于合并概要以确定数据库统计量的方法和装置,例如多个不同值(NDV)。 合并可用于确定初始数据库统计信息或执行增量统计维护。 例如,每个概要可以涉及不同的分区,以便合并概要会生成全局统计量。 执行增量维护时,只需要更新其分区已更改的概要文件。 每个概要包含总结统计量的域值。 但是,这些概要可能最初包含彼此不兼容的域值。 在合并概要之前,每个概要中的域值与其他概要中的域值兼容。 在一个实施例中进行调整,使得每个概要表示相同范围的域值。 在形成“兼容简介”之后,通过兼容兼容简报的合并来合并概要。
    • 10. 发明授权
    • Method for computing near neighbors of a query point in a database
    • 用于计算数据库中查询点的近邻的方法
    • US6148295A
    • 2000-11-14
    • US560
    • 1997-12-30
    • Nimrod MegiddoUri Shaft
    • Nimrod MegiddoUri Shaft
    • G06F17/30G06K9/62
    • G06F17/30598G06F17/30256G06F17/30327G06F17/30483G06K9/6276Y10S707/99933Y10S707/99934Y10S707/99935
    • A method for determining k nearest-neighbors to a query point in a database in which an ordering is defined for a data set P of a database, the ordering being based on l one-dimensional codes C.sub.1, . . . , C.sub.1. A single relation R is created in which R has the attributes of index-id, point-id and value. An entry (j,i,C.sub..epsilon.j (p.sub.i)) is included in relation R for each data point p.sub.i .EPSILON.P, where index-id equals j, point-id equals i, and value equals C.sub..epsilon.j (p.sub.i). A B-tree index is created based on a combination of the index-id attribute and the value attribute. A query point is received and a relation Q is created for the query point having the attributes of index-id and value. One tuple is generated in the relation Q for each j, j=1, . . . , l, where index-id equals j and value equals C.sub..epsilon.j (q). A distance d is selected. The index-id attribute for the relation R of each data point p.sub.i is compared to the index-id attribute for the relation Q of the query point. A candidate data point p.sub.i is selected when the comparison of the relation R of a data point p.sub.i to the index-id attribute for the relation Q of the query point is less than the distance d. Lower bounds are calculated for each cube of the plurality of cubes that represent a minimum distance between any point in a cube and the query point. Lastly, k candidate data points p.sub.i are selected as k nearest-neighbors to the query point.
    • 一种用于确定数据库中的查询点的k个最近邻的方法,其中为数据库的数据集P定义排序,排序基于l个一维码C1。 。 。 ,C1。 创建单个关系R,其中R具有index-id,point-id和value的属性。 对于每个数据点pi EPSILON P,其中index-id等于j,point-id等于i,并且值等于C epsilon(pi),则在关系R中包括条目(j,i,C epsilon j(pi))。 基于index-id属性和value属性的组合创建B树索引。 接收到一个查询点,并为具有index-id和value属性的查询点创建一个关系Q。 在每个j,j = 1的关系Q中产生一个元组。 。 。 ,l,其中index-id等于j,值等于C epsilon(q)。 选择距离d。 将每个数据点pi的关系R的index-id属性与查询点的关系Q的index-id属性进行比较。 当数据点pi的关系R与查询点的关系Q的index-id属性的比较小于距离d时,选择候选数据点pi。 对于表示多维数据集中的任何点与查询点之间的最小距离的多个立方体中的每个立方体计算下限。 最后,将k个候选数据点pi选为查询点的k个最近邻。