Data cleaning method of OTRS system based on storage process

Abstract

The invention discloses a data cleaning method of an OTRS system based on a storage process, and relates to the technical field of data cleaning. The data cleaning method includes the steps: circularly taking out historical data records in the second vernier; storing the first historical data record into a statistical result intermediate table; judging whether queue types of front and back historical data records are the same or not; if not, storing the latter historical data record into a statistical result intermediate table; if so, judging whether owners of front and back historical data records are the same or not; if not, storing the next historical data record into a statistical result intermediate table, and if so, judging whether record managers of the previous historical data record and the next historical data record are the same; if not, storing the next historical data record into a statistical result intermediate table; if so, judging whether the difference value of the creation time in the previous historical data record and the next historical data record is larger than a preset value or not; if so, storing the difference value into a statistical result intermediatetable; and if not, continuing to take out historical data from the second cursor to return to the queue type judgment process until data cleaning is completed.

Description

technical field [0001] The invention discloses a data cleaning method, relates to the technical field of data cleaning, and in particular relates to a data cleaning method of an OTRS system based on a stored procedure. Background technique [0002] With the rapid development of the economy, cloud services are more and more widely used in daily life. Work order processing, as the core component of cloud service operation and maintenance, is an open source defect tracking management system software. Its pure Web operation interface, good Mail system integration, problem ticket generation interface, and timely and efficient processing of tickets make OTRS play an irreplaceable role in cloud service operation and maintenance engineering. [0003] However, in the OTRS system, a large amount of duplicate data will be generated every time the queue, owner, and person in charge are transferred, and the statistical analysis of the work order in the OTRS system is very complicated, so...

AI Technical Summary

Problems solved by technology

[0003] However, in the OTRS system, a large amount of duplicate data will be generated every time the queue, owner, and person in charge are transferred, and the statistical analysis of the work order in the OTRS system is very complicated, so the data needs to be cleaned before the statistical analysis of the work order

In the existing method, it is necessary to find queue information such as the owner, person in charge, creation time, and end time of each queue in the work order history, and then compare the difference between the previous record and the last record, and then clean it. The operation steps are cumbersome, error-prone, inefficient, and cannot completely filter out duplicate data

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