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    • 21. 发明申请
    • EFFICIENT LARGE-SCALE PROCESSING OF COLUMN BASED DATA ENCODED STRUCTURES
    • 基于列的数据编码结构的有效的大规模处理
    • US20100030748A1
    • 2010-02-04
    • US12270872
    • 2008-11-14
    • Amir NetzCristian Petculescu
    • Amir NetzCristian Petculescu
    • G06F7/06G06F17/30
    • G06F17/30492
    • The subject disclosure relates to efficient query processing over large scale data storage. An exemplary process includes retrieving a subset of columns implicated by a query as integer encoded and compressed sequences of values corresponding to different columns of data, defining query processing buckets that span over the subset of columns based on changes of compression type occurring in the integer encoded and compressed sequences of values of the subset of data and processing the query in memory on a bucket by bucket basis and processing the query based on type of current bucket when processing the integer encoded and compressed sequences of values. The column based organization of the data, and the application of a hybrid run length encoding and bit packing technique, enable a highly efficient and speedy query response in real-time.
    • 本公开涉及对大规模数据存储的有效查询处理。 示例性过程包括:将查询所涉及的列的子集作为对应于不同数据列的整数编码和压缩的值序列,基于经整数编码的压缩类型的变化定义跨越列的子集的查询处理桶 以及数据子集的值的压缩序列,并且逐桶地处理存储器中的查询,并且当处理整数编码和压缩的值序列时,基于当前存储桶的类型来处理查询。 数据的基于列的组织以及混合运行长度编码和位打包技术的应用实现了高效和快速的查询响应。
    • 23. 发明授权
    • System and method for analytically modeling data organized according to non-referred attributes
    • 根据非参考属性组织的分析建模数据的系统和方法
    • US07275022B2
    • 2007-09-25
    • US10199612
    • 2002-07-19
    • Amir NetzCristian PetculescuMosha PasumanskyRichard R. TkachukAlexander Berger
    • Amir NetzCristian PetculescuMosha PasumanskyRichard R. TkachukAlexander Berger
    • G06F17/10G06F7/60
    • G06F17/30592Y10S707/99933Y10S707/99943
    • A system and method for analytically modeling data organized according to non-referred attributes is disclosed. Data stored in a first and a second relational data table is analytically modeled in a data cube. The first table organizes a first type according to a first attribute. The second table organizes a second type according to the first attribute and a second attribute. A first measure is modeled according to the first type of the first table. A first dimension is modeled according to the first attribute of the first and second tables. A second dimension is modeled according to the second attribute of the second table. The first measure is tied to the first dimension according to the first attribute of the first table to allow the first measure to be analyzed by the first dimension according to the first attribute. The first measure is tied to the second dimension by, for each entry of the first dimension, allocating the entry to each entry of the second dimension in a predetermined manner.
    • 公开了一种用于根据非参考属性组织的分析建模数据的系统和方法。 存储在第一和第二关系数据表中的数据在数据立方体中被分析地建模。 第一个表根据第一个属性组织第一个类型。 第二表根据第一属性和第二属性组织第二类。 第一个度量根据第一个表的第一个类型进行建模。 根据第一和第二表的第一属性对第一维进行建模。 根据第二表的第二属性对第二维进行建模。 根据第一表的第一个属性,第一个度量与第一个维度相关联,以便根据第一个属性对第一个维度进行第一个维度的分析。 对于第一维度的每个条目,第一尺度与第二维度相关联,以预定方式将条目分配给第二维度的每个条目。
    • 26. 发明授权
    • Efficient large-scale processing of column based data encoded structures
    • 基于列的数据编码结构的高效大规模处理
    • US08626725B2
    • 2014-01-07
    • US12270872
    • 2008-11-14
    • Amir NetzCristian Petculescu
    • Amir NetzCristian Petculescu
    • G06F7/00G06F17/00G06F17/30
    • G06F17/30492
    • The subject disclosure relates to efficient query processing over large scale data storage. An exemplary process includes retrieving a subset of columns implicated by a query as integer encoded and compressed sequences of values corresponding to different columns of data, defining query processing buckets that span over the subset of columns based on changes of compression type occurring in the integer encoded and compressed sequences of values of the subset of data and processing the query in memory on a bucket by bucket basis and processing the query based on type of current bucket when processing the integer encoded and compressed sequences of values. The column based organization of the data, and the application of a hybrid run length encoding and bit packing technique, enable a highly efficient and speedy query response in real-time.
    • 本公开涉及对大规模数据存储的有效查询处理。 示例性过程包括:将查询所涉及的列的子集作为对应于不同数据列的整数编码和压缩的值序列,基于经整数编码的压缩类型的变化来定义跨越​​列的子集的查询处理桶 以及数据子集的值的压缩序列,并且逐桶地处理存储器中的查询,并且当处理整数编码和压缩的值序列时,基于当前存储桶的类型来处理查询。 数据的基于列的组织以及混合运行长度编码和位打包技术的应用实现了高效和快速的查询响应。