Zipper table generation method, device and equipment and medium

Abstract

The invention discloses a zipper table generation method, device and equipment and a medium. The method comprises the following steps: reading a historical characteristic value corresponding to a historical data record of a target data table in a data warehouse at a historical moment; obtaining a current data record, corresponding to the historical data record, of the target data table at the current moment; splicing the data content of each field in the current data record into a second character string, and performing Hash algorithm operation on the second character string to generate a current characteristic value; judging whether the historical characteristic value is different from the current characteristic value or not; and if yes, generating a zipper table in which historical datarecords are recorded. According to the method, the overall occupation of operation resources of cluster equipment in the zipper table generation process is relatively reduced, so that the overall operation stability of the big data platform is ensured, and the operation and maintenance pressure is reduced. In addition, the invention further provides a zipper table generation device and equipment and a medium, and the beneficial effects are the same as those mentioned above.

Description

technical field [0001] The invention relates to the field of databases, in particular to a method, device, equipment and medium for generating a zipper list. Background technique [0002] With the advent of the era of big data, major enterprises often need to build their own big data platform, and the data warehouse based on the big data platform is one of the important applications under the big data platform. A data warehouse is a strategic collection that provides all types of data support for the decision-making process at all levels of the enterprise. The collection is subject-oriented, integrated, time-varying, and non-volatile. [0003] In actual scenarios, there are often a large number of data records stored in the data table of the data warehouse, and the content of the data records in the data table often changes with the passage of time. In the application process of the data table, the user It is usually necessary to trace back the data records in the data tabl...

AI Technical Summary

Problems solved by technology

Since the current comparison of corresponding data records between data tables at adjacent times is performed field by field, and in actual scenarios, data records in data tables often contain many fields, so the current When comparing corresponding data records between data tables at adjacent times, it needs to occupy a large amount of computing resources of the cluster equipment, making it difficult to ensure the overall operation stability of the big data platform, which can easily cause great pressure on operation and maintenance

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