知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

60 records (took 0.034 seconds)

    IN-MEMORY COLUMN-LEVEL MULTI-VERSIONED GLOBAL DICTIONARY FOR IN-MEMORY DATABASES
    54.
    发明申请
    IN-MEMORY COLUMN-LEVEL MULTI-VERSIONED GLOBAL DICTIONARY FOR IN-MEMORY DATABASES 审中-公开

    公开(公告)号：US20170109406A1

    公开(公告)日：2017-04-20

    申请号：US15294460

    申请日：2016-10-14

    Applicant: Oracle International Corporation

    Inventor： Shasank K. Chavan ,  Prashant Gaharwar ,  Ajit Mylavarapu ,  Dina Thomas ,  Dennis Lui ,  Sheldon A.K. Lewis ,  Roger D. Macnicol

    IPC: G06F17/30 ,  G06F7/24

    CPC classification number: G06F16/24561 ,  G06F16/221 ,  G06F16/3347

    Abstract: Techniques are described herein for sharing a dictionary across multiple in-memory compression units (IMCUs). After a dictionary is used to encode a first column vector in a first IMCU, the same dictionary is used to encode a second column vector in a second IMCU. The entries in the dictionary are in sort order to facilitate binary searching when performing value-to-code look-ups. If, during the encoding of the second column vector, values are encountered for which the dictionary does not already have codes, then a “sort-order-boundary” is established after the last entry in the dictionary, and entries for the newly encountered values are added to the dictionary, after the sort-order-boundary. To facilitate value-to-code look-ups, the new entries are also sorted relative to each other, creating a second “sort order set”. A new version of the dictionary may be created when the number of sort order sets in the first version of the dictionary reaches a configurable threshold.

    TECHNIQUES FOR MAINTAINING COLUMN VECTORS OF RELATIONAL DATA WITHIN VOLATILE MEMORY
    58.
    发明申请
    TECHNIQUES FOR MAINTAINING COLUMN VECTORS OF RELATIONAL DATA WITHIN VOLATILE MEMORY 审中-公开
    维护相关数据在波形存储器中的列向量的技术

    公开(公告)号：US20130275473A1

    公开(公告)日：2013-10-17

    申请号：US13916284

    申请日：2013-06-12

    Applicant: Oracle International Corporation

    Inventor： Lawrence J. Ellison ,  Amit Ganesh ,  Vineet Marwah ,  Jesse Kamp ,  Anindya C. Patthak ,  Shasank K. Chavan ,  Michael J. Gleeson ,  Allison L. Holloway ,  Manosiz Bhattacharyya

    IPC: G06F17/30

    CPC classification number: G06F17/30315 ,  G06F9/3887 ,  G06F17/30339 ,  G06F17/30595

    Abstract: Techniques are provided for more efficiently using the bandwidth of the I/O path between a CPU and volatile memory during the performance of database operation. Relational data from a relational table is stored in volatile memory as column vectors, where each column vector contains values for a particular column of the table. A binary-comparable format may be used to represent each value within a column vector, regardless of the data type associated with the column. The column vectors may be compressed and/or encoded while in volatile memory, and decompressed/decoded on-the-fly within the CPU. Alternatively, the CPU may be designed to perform operations directly on the compressed and/or encoded column vector data. In addition, techniques are described that enable the CPU to perform vector processing operations on the column vector values.

    Abstract translation: 在执行数据库操作期间，提供了技术来更有效地使用CPU和易失性存储器之间的I / O路径的带宽。 来自关系表的关系数据作为列向量存储在易失性存储器中，其中每个列向量包含表的特定列的值。 可以使用二进制可比较的格式来表示列向量中的每个值，而不管与列相关联的数据类型如何。 列向量可以在易失性存储器中被压缩和/或编码，并且在CPU内部实时解压缩/解码。 或者，CPU可以被设计为直接对压缩和/或编码的列向量数据执行操作。 另外，描述使CPU能够对列向量值执行向量处理操作的技术。

Patent Agency Ranking