公开(公告)号：US08521788B2

公开(公告)日：2013-08-27

申请号：US13708060

申请日：2012-12-07

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: G06F7/00

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.

公开(公告)号：US20130151568A1

公开(公告)日：2013-06-13

申请号：US13708060

申请日：2012-12-07

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.