Quick statistical method based on two-dimensional table of relational database system

Abstract

The invention discloses a quick statistical method based on a two-dimensional table of a relational database system. The quick statistical method comprises the following steps: constructing an initialstatistical result table; updating the initial statistical result table to obtain a real-time statistical result table; and querying the statistical result table to obtain the total number of real-time data records corresponding to the table name. The method mainly aims at a two-dimensional table for storing mass data in a relational database system, and when the data size of the two-dimensionaltable needing to count the total number of data records is increased or decreased, real-time addition and subtraction calculation of a statistical value of the total number of data records is triggered by defining and inserting a statistical result table of the total number of initial data records in advance; therefore, the result of the total number of the data records of the two-dimensional table to be counted is obtained in real time and stored, the time consumed for counting the total number of the data records of the two-dimensional table is optimized, the counting time is shortened, andthe counting efficiency and accuracy of the total number of the data records are improved.

Description

technical field [0001] The invention relates to the technical field of relational databases, in particular to a fast statistical method based on a two-dimensional table of a relational database system. Background technique [0002] The relational database system is an important technology for storing user information, business information, reports and other data, and is used in various industries such as the Internet, big data, e-commerce, and e-government. The two-dimensional table in the relational database system, as the main carrier of data storage, meets people's various needs for persistent storage and real-time query of relational data. However, with the rapid development of the Internet and the big data industry, the amount of business data recorded in two-dimensional tables in relational database systems has exploded exponentially, and the total amount of data in two-dimensional tables occupies more and more storage space. [0003] In this context, for two-dimensio...

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Problems solved by technology

[0003] In this context, for two-dimensional tables that store massive amounts of data in relational database systems, use the traditional, conventional, SQL-99 standard-based structural query language (SQL language) COUNT () statistical function to count the total number of records , all the data records in the table will be scanned, and the larger the data volume, the longer the scanning time will appear.

However, the COUNT() function of this method needs to scan all the records, which leads to longer and longer statistical execution time, which seriously affects the speed of people's acquisition of the total number of real-time statistical data records, so that it cannot meet people's needs.

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