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    • 13. 发明申请
    • Incremental Cardinality Estimation for a Set of Data Values
    • 一组数据值的增量基数估计
    • US20060288022A1
    • 2006-12-21
    • US11463294
    • 2006-08-08
    • Walid RjaibiPeter Haas
    • Walid RjaibiPeter Haas
    • G06F7/00
    • G06F17/30469Y10S707/941Y10S707/959Y10S707/99937Y10S707/99942Y10S707/99943Y10S707/99944Y10S707/99945Y10S707/99953
    • A system and method for incrementally maintaining column cardinality estimates in database management systems. In one embodiment, the system includes system catalog table containing a cardinality estimate for a column that is extended to include an appropriate data structure. A modified linear counting technique is used in a first embodiment of a method for column cardinality estimation. The cardinality estimate is produced by an initial scan of the data but is then further maintained without requiring a full scan of the data. Data changes are reflected incrementally in modifications to the initial cardinality estimate, keeping the cardinality statistics more current with respect to the database condition. The technique of the invention typically provides a capability for a database management system to produce more efficient search plans providing more effective responses to user queries through the use of improved cardinality statistics.
    • 一种用于在数据库管理系统中逐行维护列基数估计的系统和方法。 在一个实施例中,系统包括系统目录表,其包含扩展为包括适当的数据结构的列的基数估计。 在列基数估计方法的第一实施例中使用经修改的线性计数技术。 基数估计是通过数据的初始扫描产生的,然后进一步维持,而不需要对数据进行全面扫描。 在初始基数估计的修改中,数据变化逐渐反映出来,保持基数统计信息相对于数据库条件更新。 本发明的技术通常提供了一种数据库管理系统产生更有效的搜索计划的能力,通过使用改进的基数统计来提供对用户查询的更有效的响应。
    • 17. 发明申请
    • Method for discovering undeclared and fuzzy rules in databases
    • 在数据库中发现未申报和模糊规则的方法
    • US20050097072A1
    • 2005-05-05
    • US10697052
    • 2003-10-31
    • Paul BrownPeter Haas
    • Paul BrownPeter Haas
    • G06F7/00G06F17/30G06N5/04
    • G06N5/048G06F17/30539
    • A scheme is used to automatically discover algebraic constraints between pairs of columns in relational data. The constraints may be “fuzzy” in that they hold for most, but not all, of the records, and the columns may be in the same table or different tables. The scheme first identifies candidate sets of column value pairs that are likely to satisfy an algebraic constraint. For each candidate, the scheme constructs algebraic constraints by applying statistical histogramming, segmentation, or clustering techniques to samples of column values. In query-optimization mode, the scheme automatically partitions the data into normal and exception records. During subsequent query processing, queries can be modified to incorporate the constraints; the optimizer uses the constraints to identify new, more efficient access paths. The results are then combined with the results of executing the original query against the (small) set of exception records.
    • 一种方案用于自动发现关系数据中的列对之间的代数约束。 约束可能是“模糊的”,因为它们对大多数但不是全部的记录持有,并且列可以在同一个表或不同的表中。 该方案首先识别可能满足代数约束的列值对的候选集合。 对于每个候选者,该方案通过将统计直方图,分段或聚类技术应用于列值样本来构建代数约束。 在查询优化模式下,该方案自动将数据分割为正常和异常记录。 在随后的查询处理期间,可以修改查询以并入约束; 优化器使用约束来识别新的更有效的访问路径。 然后将结果与针对(小)异常记录集执行原始查询的结果相结合。