Multidimensional-array-based grouping aggregation calculating method in column storage database

A multi-dimensional array and calculation method technology, applied in the field of database management, can solve the problems of not using access efficiency, achieve good platform portability and adaptability, eliminate storage overhead, and improve efficiency

Active Publication Date: 2013-09-11
RENMIN UNIVERSITY OF CHINA
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Problems solved by technology

This pre-materialization strategy does not take advantage of the access efficiency of column storage one column at a time, so it is necessary to provide grouping and aggregation operations based on column storage in the column storage database

Method used

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  • Multidimensional-array-based grouping aggregation calculating method in column storage database
  • Multidimensional-array-based grouping aggregation calculating method in column storage database
  • Multidimensional-array-based grouping aggregation calculating method in column storage database

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Embodiment Construction

[0028] In multidimensional OLAP, multidimensional arrays are used to store original multidimensional data sets, and its sparse data storage will cause serious storage efficiency problems. Multidimensional arrays are more suitable for direct mapping access to multidimensional data than hash tables. The grouping attribute also has the characteristics of a multidimensional data set. Since the grouping operation generates multidimensional data in the process of flowing a large number of records into a small number of groups, there are few null values ​​in the array and the storage efficiency is high. Multiple grouping attributes constitute a natural multi-dimensional data cube, and each unit of the data cube corresponds to a specific grouping item. Through the multi-dimensional cube structure, the combination value (group item) of any grouping attribute can be directly mapped to the unique array unit of the multi-dimensional array, while the hash map in contrast cannot reflect the...

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Abstract

The invention discloses a multidimensional-array-based grouping aggregation calculating method in a column storage database. The multidimensional-array-based grouping aggregation calculating method includes that in the grouping aggregation calculating process, a hash table is divided into a plurality of multidimensional arrays, and each array unit indicates a multidimensional grouping vector; the grouping attributes of output records are mapped to be multidimensional array subscripts; and aggregation attribute values are sent to the corresponding grouping aggregation multidimensional array units for aggregation calculating according to the multidimensional array subscripts of the grouping attributes. By adopting the multidimensional-array-based grouping aggregation calculating method, the multidimensional arrays are adopted to correspond to the grouping attributes by aid of the multidimensional data characteristics of the grouping attributes, and storage expanse and harsh detection expanse of the harsh table are eliminated; and the complex harsh table is changed to be simple arrays, complex grouping aggregation calculating is changed to be simple array subscript accessing, and therefore the method improves the efficiency, adapts to the processing characteristics of multi-core processors and multi-core co-processors and has good platform portability and adaptability.

Description

technical field [0001] The present invention relates to a database grouping aggregation calculation method, in particular to a multi-core processor and / or multi-core coprocessor platform technical characteristics, in column storage database based on multi-dimensional array grouping aggregation calculation method, which belongs to the database management technology field. Background technique [0002] OLAP (Online Analytical Processing) is the most important application of database systems, and improving the performance of OLAP query processing is one of the key research issues in the database field. OLAP query processing usually includes multi-table joins and group aggregation calculations. Improving the performance of these operations is the key to improving OLAP response speed. At present, with the rapid growth of data volume and the continuous improvement of analytical query processing requirements, as well as multi-core processors and many-core co-processor platforms (s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 张延松张宇王珊
Owner RENMIN UNIVERSITY OF CHINA
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