Mass data querying method

Abstract

The invention discloses a mass data querying method, belonging to the information technology field. The method comprises: a) dividing the mass data entity table according to the given time spans into sub-areas; b) establishing a two-dimensional statistical table for attribute names in the entity table, wherein one dimension represents all the given time spans in the time interval, the other dimension represents the attribute data in the attribute column of the attribute names, and the contents in the statistical table represent the name of entity table of certain attribute data existing in certain time span; c) during querying, acquiring a collection of the entity table sub-areas in the time interval according to the statistical table for the attribute name and the time interval given in the querying condition, if the querying condition comprises the statistically treated attribute name; and d) narrowing the mass data scope according to the collection and then carrying out query. The method of the invention can be used for mass data query in large-scale systems such as charging query systems of telecommunications industry, large website transaction platform and the like.

Description

technical field [0001] The invention relates to database data query, in particular to a massive data query method with improved query performance, and belongs to the field of information technology. Background technique [0002] Query is the only way for users to obtain information from the database, and it is also the main function of general application systems, and the query efficiency of the system is also one of the key indicators to measure its practicability. In industries such as telecommunications and the Internet, with the development of informatization, the data to be processed by enterprises has grown explosively, and the amount of data has reached terabytes and petabytes. As the amount of data increases, the load on the system is increasing. Without increasing the cost of hardware, the performance of user query data decreases accordingly. How to give full play to the maximum performance of the existing system so that the query speed can meet the practical requi...

AI Technical Summary

Problems solved by technology

[0020] This method aims at the situation that the traditional methods in the massive data query can no longer meet the performance requirements, effectively uses the idle time of the system to count the data that needs to be queried, and minimizes the disk IO access during the query to improve the query speed

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