Complicated query method based on attributes

Abstract

The invention relates to the technical field of massive data query management, in particular to a complicated query method based on attributes which is specially applicable to fabric data management and can effectively improve the fabric management efficiency. The method is characterized in that a data storage database is initially built, wherein each attribute corresponds to a field of an integer type; each attribute value is saved as the nth power of 2, and bitwise AND operation is used during query, wherein the query method comprises the steps that attribute values to be searched are summed during query, a retrieval value is obtained by means of & operation of SQL, query is conducted in the storage database through the retrieval value, and a fabric with the attributes to be searched is obtained. By means of the complicated query method based on the attributes, the query efficiency can be greatly improved, script complexity is reduced, the efficiency of fabric data management is improved, and thus the design and production efficiencies are improved.

Description

Technical field: [0001] The invention relates to the technical field of massive data query management, in particular to an attribute-based complex query method that is especially suitable for fabric data management and can effectively improve fabric management efficiency. Background technique: [0002] We often need to save certain entity information in the computer system. An entity may have multiple categories of attributes. For example, for a clothing fabric, in addition to single-value attributes, such as name, price, etc., it may also contain multiple values. Attributes, such as season attributes, fabric pattern attributes, feel attributes, etc. Each attribute corresponds to multiple options. For example, a fabric can be applied to spring and summer at the same time, then its seasonal attribute has two values: spring and summer. When we have a lot of fabric data, such as millions of fabrics, how to save these attributes and quickly find fabrics that meet specific attri...

AI Technical Summary

Problems solved by technology

The first method is convenient to save, but it cannot be accurately queried, and it is also difficult to conduct data summary analysis

The second method is slightly more complicated to save, and can be accurately queried and analyzed, but requires a large storage space. At the same time, due to the need to link multiple tables when querying, the performance is very poor, and the query and analysis speed is extremely slow, which is not suitable for large amounts of data. storage and analysis