HBase fault prediction method, system and equipment based on decision function model and medium

Abstract

The invention relates to an HBase fault prediction method, system and device based on a decision function model and a medium, and belongs to the technical field of distributed storage, and the method comprises the steps: collecting monitoring item data of HBase in various fault scenes, classifying the monitoring item data according to each fault scene, and determining a plurality of monitoring items corresponding to each fault scene; based on the plurality of monitoring items corresponding to each fault scene, a decision function model corresponding to each fault scene is established, and a prediction conclusion of each decision function model is associated with a threshold range of the plurality of monitoring items corresponding to each fault scene; and obtaining the value of each monitoring item in the HBase environment, correspondingly inputting the values of the plurality of monitoring items corresponding to each fault scene into the decision function model corresponding to each fault scene, and obtaining a prediction conclusion corresponding to each fault scene. According to the method, automatic analysis of fault conclusions is realized, fault analysis efficiency is improved, faults can be classified and processed, and accuracy of prediction results is improved at the same time.

Description

technical field [0001] The present application relates to the technical field of distributed storage, in particular to an HBase failure prediction method, system, device and medium based on a decision function model. Background technique [0002] HBase is an open source distributed data storage system developed based on the Google Bigtable paper, which needs to run on Hdfs (an open source distributed file system). HBase is one of the most widely used distributed storage software in the big data ecosystem. Many large and medium-sized enterprises in China use HBase to store various massive offline and real-time data. However, HBase exceptions and failures have become O&M problems for companies using HBase. For example, a financial Internet company in China once had large-scale business interruptions due to HBase exceptions. [0003] Therefore, HBase fault monitoring is very important, so every company has a monitoring solution for HBase. However, due to the complexity of HBa...

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Problems solved by technology

[0004] The embodiment of the present application provides an HBase fault prediction method, system, device and medium based on a decision function model, so as to at least solve the problem of hysteresis and low efficiency in the related art by artificially analyzing HBase faults

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