Object processing method and device

Abstract

The invention discloses an object processing method and an object processing device and belongs to the technical field of computers. The method comprises the steps of obtaining an object from a receiving queue; assigning a processing unit for the object from at least one processing unit; obtaining a load of the processing unit which is assigned for the object; if the load is greater than a cache threshold value, adding the object into a cache queue; carrying out delay processing on the object according to the cache queue. According to the object processing method and the object processing device, the problems that when a lot of requests simultaneously need a Redis example with a Redis port for processing in the background art, the requests are overstocked, the requests are overtime, and the business access is unavailable are solved; when the load of the processing unit (for example the Redis example with the Redis port) is over high, the object, corresponding to the processing unit, in the receiving queue is added into the cache queue, and then the object is subjected to the delay processing, the overstock problem is prevented from being caused in the receiving queue, the mutual influence of objects corresponding to different processing units is avoided, and the processing speed is guaranteed.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an object processing method and device. Background technique [0002] Redis is an open source, network-enabled, memory-based key-value (key-value pair) database. The data types supported by Redis include string (string), list (linked list), set (set), zset (ordered set) and hash (hash type). In the process of accessing the Redis database, it can be roughly divided into two types: read request and write request. [0003] Please refer to figure 1 , which shows a schematic diagram involved in accessing the Redis database. Taking read requests as an example, m read requests are stored in the request queue 12, where m≥1. In order to cope with large-scale business access, multiple Redis instances 14 need to be deployed, and each Redis instance 14 occupies a Redis port. The read requests in the request queue 12 are processed by n threads corresponding to the request queue 12, whe...

AI Technical Summary

Problems solved by technology

[0004] In the process of realizing the present invention, the inventors found that the above-mentioned technology has at least the following problems: when the key hash distribution of the m read requests stored in the request queue 12 is uneven, or there are a large number of read requests with the same When reading the key, the load of the Redis instance corresponding to a certain Redis port will be too high

Since the Redis instance only supports single-threaded serial processing of read requests, this makes it impossible to process a large number of read requests in a timely manner, resulting in a backlog of requests, request timeouts, and unavailable business access

Images