A performance testing method and device for a big data platform

Abstract

An embodiment of the invention discloses a big data platform performance detection method and device, and relates to the network technical field. The method has the steps of collecting the first class performance index data of the big data platform under the current operation state to acquire the first class performance index data sequence O; according to the first class performance index data sequence O and a hidden Markov model optimal value lambda 1, calculating P (O|lambda 1); judging whether the P (O|lambda 1) is smaller than a preset threshold; if yes, determining that the big data platform is in an abnormal state, and if not, determining that the big data platform is in a normal state. In the embodiment of the invention, the big data platform performance test is carried out by the hidden Markov model, so the detection precision is improved.

Description

technical field [0001] The invention relates to the field of network technology, in particular to a performance detection method and device of a big data platform. Background technique [0002] For nearly half a century, the concept of "big data" has been applied to various fields and has become a new driving force that can change the world. In order to use data more effectively, researchers have developed big data platforms to calculate the increasing amount of data information generated by society. However, in the operation of the big data platform, many performance problems, such as CPU (Central Processing Unit, central processing unit) abnormality, memory abnormality, etc., will affect us to obtain accurate data. [0003] In order to solve the performance problems existing in the operation of the big data platform, a performance detection method of the big data platform is established. The basic flow of the big data platform performance testing method is as follows: ...

AI Technical Summary

Problems solved by technology

[0027] In the existing big data platform performance detection methods, ARIMA (Autoregressive Integrated Moving Average Model, Autoregressive Integrated Moving Average Model) is used to establish the performance model under normal conditions, because the ARIMA model is a time series prediction model, The time series forecasting model predicts the future value based on the past and present values ​​of the time series, so when the performance index is a linear relationship, the performance detection method of the big data platform established by the ARIMA model has a higher detection accuracy; but when the performance index When the relationship is nonlinear, the detection accuracy of the big data platform performance detection method established by using the ARIMA model is low

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