Dispatch link fault determination method and device, equipment and storage medium

Abstract

The invention discloses a dispatch link fault determination method and device, equipment and a storage medium. The method comprises the steps of responding to a fault analysis task of a dispatch link, generating a query statement for a column database, the query statement comprising query parameters of a target field, the target field being a driver identification field and / or an order identification field, the column database being used for storing order dispatching log data obtained by analyzing, shunting and splitting log data of an online car-hailing order dispatching system based on a message queue and a streaming processing framework; on the basis of the query parameters of the target field and an index mechanism of the column database, carrying out aggregation query on an order dispatching log table in the column database to obtain a target order dispatching log associated with the query statement, and enabling the order dispatching log table to take the target field as an index primary key; and determining a fault node of the dispatch link according to the target order dispatching log. By utilizing the technical scheme of the invention, the efficiency of aggregation query of order dispatching logs can be improved, so that the dispatch link fault node can be quickly positioned.

Description

technical field [0001] The present application relates to the field of computer technology, and in particular to a method, device, equipment and storage medium for determining a dispatch link fault. Background technique [0002] At present, the fault analysis of the dispatch link is aimed at quickly locating the link node of the dispatch failure when the dispatch failure feedback is received, and analyzing the cause of the dispatch link breakpoint. There are two main types of existing technical solutions: the first type of technical solution is mainly for log storage and query, such as ELK (ElasticSearch, Logstash, Kibana) real-time log analysis platform; the second type of technical solution uses embedded programs to bury points collection. [0003] However, on the one hand, when ELK processes a large amount of data, the aggregation statistics speed and response speed are slow; at the same time, ELK uses a timer to detect changes in the dispatch system database before sync...

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Problems solved by technology

[0003] However, on the one hand, when ELK processes a large amount of data, the aggregation statistics speed and response speed are slow; at the same time, ELK uses a timer to detect changes in the dispatch system database before synchronizing data, which will cause delays and cannot realize real-time storage and query; At the same time, due to the poor aggregation query capability of ELK, it is not suitable for multi-aggregation query scenarios

On the other hand, using the method of embedded program for buried point collection will affect the performance of the program. For some programs with a very large amount of logs, using this way of coupling with the business system for buried point collection will easily affect the normal operation of the business system

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