Task testing method and device, electronic equipment and storage medium

Abstract

The invention discloses a task testing method and device, electronic equipment and a storage medium. The invention relates to the field of testing, and discloses the task testing method which comprises the following steps of: obtaining an original data set, and performing format unification and scanning area division on the original data set to obtain a target data set; calculating an information gain rate of the target data in the target data set, and extracting feature data corresponding to the target data according to the information gain rate to obtain a feature data set; performing scheduling task allocation on the feature data set by utilizing a preset task scheduling framework to obtain a scheduling task, and loading a log label reading instruction in the scheduling task; running the scheduling task to obtain a running result, and identifying whether the running result contains a log label or not by utilizing the log label reading instruction; if the running result does not contain the log label, performing scheduling task allocation on the feature data set again; and if the log label is contained, returning the operation result to the corresponding downstream user. In addition, the invention also relates to a blockchain technology, and the feature data set can be stored in a blockchain. The task testing efficiency can be improved.

Description

technical field [0001] The invention relates to the field of testing, in particular to a task testing method, device, electronic equipment and computer-readable storage medium. Background technique [0002] The rapid development of the Internet has given birth to the era of big data, and the rise of the mobile Internet has made big data ubiquitous, and the Basic Data Set Project (BDSP) based on big data has also been born. The BDSP project can Applied to the data information management of enterprises, it helps enterprises to better assign and execute tasks. [0003] At present, after the execution of the midstream system tasks in the BDSP project is completed, the Hadoop platform log tag will be written to the downstream system for use and judgment. However, since the midstream system contains a large number of execution task results, manual detection is time-consuming It is relatively long, and at the same time, there are many test commands that need to be entered, which w...

AI Technical Summary

Problems solved by technology

[0003] At present, after the execution of the midstream system tasks in the BDSP project is completed, the Hadoop platform log tag will be written to the downstream system for use and judgment. However, since the midstream system contains a large number of execution task results, manual detection is time-consuming It is relatively long, and at the same time, there are more test commands that need to be entered, which will affect the efficiency of task result testing

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