System and method for data filtering

Abstract

The invention provides a system and a method for data filtering. The system for data filtering comprises an extracting unit, a selecting unit, a filtering condition generating unit and a data filtering analyzing unit. The extracting unit is used for extracting attributive characters of source data and sending the attributive characters to the selecting unit. The selecting unit selects at least one attributive character based on which data filtering is performed and sends the selected attributive character to the filtering condition generating unit. The filtering condition generating unit generates at least one filtering module in one-to-one correspondence with the at least one attributive character based on the selected at least one attributive character and combines the at least one filtering module to generate the filtering condition. The data filtering analyzing unit filters the source data based on the filtering condition to generate target data. The system for data filtering is capable of ensuring free recombination on the condition that data characteristics are changed, thereby being capable of efficiently adapting to changes of the data characteristics.

Description

technical field [0001] The invention relates to the technical field of information processing, in particular to a data filtering system and method based on module free reorganization. Background technique [0002] There are three types of existing data filtering: [0003] The first filtering method is completely static, and is based on the established filtering conditions in the program instructions when performing data filtering; [0004] The second is that the filtering method is fully open dynamic filtering. For example, if a filtering condition is <=9, "<=" as the filtering parameter and "9" as the filtering parameter value will accept any input from the outside, but once the external The input filtering parameters do not conform to the logical attributes of the filtered data item, which will cause data filtering to fail. For example, the value of the filtered data item is a time string, but the filter condition is dynamically set to be less than a certain integer...

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Problems solved by technology

[0004] The second is that the filtering method is a fully open dynamic filtering. For example, if a filtering condition is <=9, "<=" as a filtering parameter and "9" as a filtering parameter value will accept any input from the outside, but once the external The input filtering parameters do not conform to the logical attributes of the filtered data item, which will cause data filtering to fail. For example, the value of the filtered data item is a time string, but the filter condition is dynamically set to be less than a certain integer value;

In the existing technology, when processing data filtering, the selection of filtering parameters is limited through template prototypes, and the filtering method of receiving filtering parameter values ​​and dynamically entering the system is the most common, but the filtering templates are usually customized in advance and tightly coupled with the application system itself , can not freely reorganize and adjust the order of filter items according to the characteristics of actual data, and cannot meet the development and changes of the business. When the filtering requirements are constantly changing, the subsequent analysis data will generate data redundancy to a certain extent, and lose its filtering and screening. the meaning of

[0007] In addition, because the existing data filtering mechanism is usually based on a predetermined filtering template and tightly coupled with the application system, it cannot separate the status quo for free reorganization. As a result, once the business changes and the data analysis mechanism generates new requirements, The loss will be a large-scale source program revision at the system level and cause repeated investment in application system resources

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