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    • 3. 发明授权
    • Method for creating an in-memory physical dictionary for data compression
    • 用于创建用于数据压缩的内存中物理字典的方法
    • US07460033B2
    • 2008-12-02
    • US11617610
    • 2006-12-28
    • Balakrishna Raghavendra IyerPiotr M. PlachtaWolfram SauerSteven W. White
    • Balakrishna Raghavendra IyerPiotr M. PlachtaWolfram SauerSteven W. White
    • H03M7/34
    • H03M7/3088
    • Some aspects of the invention provide methods for creating an in-memory physical dictionary for data compression. To that end, in accordance with aspects of the present invention, a new heuristic is defined for converting each of the plurality of logical nodes into a corresponding physical node forming a plurality of physical nodes; then place each of the physical nodes into the physical dictionary while traversing the dictionary tree in descending visit count order. Each physical node is placed in its nearest ascendant's cache-line with sufficient space. If there is no space in any of the ascendant's cache-line, then the physical node is placed into a new cache-line, unless a pre-defined packing threshold has been reached, in which case the physical node is placed in the first available cache-line.
    • 本发明的一些方面提供了用于创建用于数据压缩的内存中物理字典的方法。 为此,根据本发明的方面,新的启发式被定义为将多个逻辑节点中的每一个转换成形成多个物理节点的对应的物理节点; 然后将每个物理节点放入物理字典,同时以递减的访问次序顺序遍历字典树。 每个物理节点都放置在其最接近的上升缓存行,并具有足够的空间。 如果任何上升缓存行中没有空格,则物理节点将被放置到新的高速缓存行中,除非已达到预定义的打包阈值,在这种情况下,物理节点被置于第一个可用的 缓存线。
    • 7. 发明授权
    • Query optimization through the use of multi-column statistics to avoid the problems of non-indexed column correlation
    • 查询优化通过使用多列统计来避免非索引列相关的问题
    • US06272487B1
    • 2001-08-07
    • US09277612
    • 1999-03-26
    • Thomas Abel BeavinBalakrishna Raghavendra IyerAkira ShibamiyaHong Sang TieMin Wang
    • Thomas Abel BeavinBalakrishna Raghavendra IyerAkira ShibamiyaHong Sang TieMin Wang
    • G06F1730
    • G06F17/30469Y10S707/99932
    • The system, method, and program of this invention collects multi-column statistics, by a database management system, to reflect a relationship among multiple columns of a table in a relational database. These statistics are stored in the system catalog, and are used during query optimization to obtain an estimate of the number of qualifying rows when a query has predicates on multiple columns of a table. A multi-column linear quantile statistic is collected by dividing the data of multiple columns into sub-ranges where each sub-range has approximately an even distribution of data, and determining a frequency and cardinality of each sub-range. A multi-column polygonal quantile statistic is collected by dividing the data of multiple columns into sub-spaces where each sub-space contains approximately the same number of tuples, and determining a frequency and cardinality of each sub-space. The system catalog is accessed for the stored multi-column linear quantile statistic for a query having a single range predicate and at least one equal predicate to determine the selectivity value for the predicates of the query. The system catalog is accessed for the stored multi-column polygonal quantile statistic for a query having more than one range predicate. These statistics are used in various ways to determine the selectivity value for the predicates of the query.
    • 本发明的系统,方法和程序通过数据库管理系统收集多列统计,以反映关系数据库中的表的多个列之间的关系。 这些统计信息存储在系统目录中,并且在查询优化期间使用,以便当查询在表的多个列上进行谓词时获得限定行数的估计。通过划分数据来收集多列线性分位数统计量 的多个列组成子范围,其中每个子范围具有大致均匀的数据分布,以及确定每个子范围的频率和基数。 通过将多列的数据划分为子空间,其中每个子空间包含大致相同数量的元组,并确定每个子空间的频率和基数,收集多列多边形分位数统计量。系统目录被访问 对于具有单个范围谓词和至少一个相等谓词的查询的存储的多列线性分位数统计量来确定查询的谓词的选择性值。 对于具有多个范围谓词的查询,为存储的多列多边形分位数统计量访问系统目录。 这些统计信息以各种方式用于确定查询谓词的选择性值。
    • 9. 发明授权
    • Reordering of complex SQL queries involving groupbys, joins, outer joins
and full outer joins
    • 重新排序复杂的SQL查询,包括groupbys,连接,外连接和完整的外连接
    • US5960427A
    • 1999-09-28
    • US905106
    • 1997-08-01
    • Piyush GoelBalakrishna Raghavendra Iyer
    • Piyush GoelBalakrishna Raghavendra Iyer
    • G06F17/30
    • G06F17/30471G06F17/30454Y10S707/99932Y10S707/99934
    • A method, apparatus, and article of manufacture for query simplification by applying generalized inference propagation and generalized transitive closure in SQL queries having selection, projection, join, outer join, and intersection operations. The disclosed transformations and enumeration method unify and solve the problems of 1) unnesting join aggregate queries, and 2) complete enumeration of queries containing outer joins, when the outer join predicate references an aggregated value, or the predicate references more than two base relations in a query subtree. The system first eliminates redundant sub-expressions and modifies expensive binary operations to inexpensive binary operations, then converts complex predicates to simple predicates by application of a generalized selection (GS) operator.
    • 通过在具有选择,投影,连接,外连接和交叉操作的SQL查询中应用广义推理传播和广义传递闭包来查询简化的方法,装置和制造。 所公开的转换和枚举方法统一并解决了1)不连接聚合查询的问题,以及2)当外部连接谓词引用聚合值时,或者谓词引用两个以上的基础关系,完整枚举包含外部联接的查询 一个查询子树。 系统首先消除冗余子表达式,并将昂贵的二进制操作修改为廉价的二进制操作,然后通过应用广义选择(GS)运算符将复数谓词转换为简单谓词。
    • 10. 发明授权
    • Parallel bottom-up construction of radix trees
    • 平行自下而上建设的基数
    • US5826262A
    • 1998-10-20
    • US621757
    • 1996-03-22
    • Thuan Quang BuiScott Dennis HeltBalakrishna Raghavendra IyerGary Ross Ricard
    • Thuan Quang BuiScott Dennis HeltBalakrishna Raghavendra IyerGary Ross Ricard
    • G06F17/30
    • G06F17/30625Y10S707/99932Y10S707/99937
    • A method for partitioning keys onto radix tree logical pages and a parallel index page build algorithm in order to provide radix tree build speedup proportional to the number of processors on the system and controlled efficient page utilization. Also, since keys are intelligently partitioned so that a complete set of keys is inserted into a logical page, there is no page overflow during the tree construction and thus page splitting is eliminated. Since radix index trees are really groups of logical pages in which each logical page contains a small tree, the tree is built (with respect to the logical pages) from the bottom up, while within each individual logical page the tree is constructed from the top down. The space required for a logical page is pre-allocated to allow construction of limbs to begin without waiting for the build of their underlying pages to complete.
    • 一种将键分解到基数树逻辑页面的方法和一个并行的索引页构建算法,以便提供与系统上的处理器数量成比例的基数树构建速度,并控制有效的页面利用率。 另外,由于密钥被智能地分割,使得一整套密钥被插入到逻辑页面中,所以在树构造期间没有页面溢出,因此页面拆分被消除。 由于基数索引树是真正的逻辑页面组,其中每个逻辑页面都包含一个小树,所以从底部向上构建树(相对于逻辑页面),而在每个单独的逻辑页面中,树从顶部构建 下。 逻辑页面所需的空间被预先分配,以允许构建四肢开始,而无需等待其底层页面的构建才能完成。