Patent
Multi-dimensional OLAP (On Line Analytical Processing) inquiry processing method facing column storage data warehouse
Yansong Zhang,Shan Wang +1 more
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TLDR
In this article, a multi-dimensional OLAP (On Line Analytical Processing) inquiry processing method facing a column storage data warehouse is presented. But the method is not suitable for the case of large data sets.Abstract:
The invention discloses a multi-dimensional OLAP (On Line Analytical Processing) inquiry processing method facing a column storage data warehouse. In the multi-dimensional OLAP inquiry processing method, the OLAP inquiry is decomposed into a bitmap filtering operation, a grouping operation and an aggregation operation. In the bitmap filtering operation, firstly, the predication is executed on a dimension table and a predicate vector bitmap is generated; and a connection operation is converted into a direct dimension table record access operation by surrogate key address mapping so as to implement access according to the positions. In the grouping operation, the pre-generation of grouping units is carried out on fact table records which meet the filtering conditions according to grouping attributes in an SQL (Structured Query Language) command and increasing IDs (identity) are distributed. In the aggregation operation, the grouping aggregation calculation which is carried out according to a grouping item of a grouping filtering vector of a fact table is implemented by carrying out column scanning on the metric attribute of the fact table for once. According to the invention, all OLAP processing tasks can be completed only by carrying out column scanning on the fact table for once, so that the cost of repeatedly scanning is avoided.read more
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Apparatus, systems and methods for data storage and/or retrieval based on a database model-agnostic, schema-agnostic and workload-agnostic data storage and access models
TL;DR: In this article, a database access model and storage structure that efficiently support concurrent OLTP and OLAP activity independently of the data model or schema used, is described, and the storage structure and access model presented avoid the need to design schemas for particular workloads or query patterns.
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