Data query method, insertion method and deletion method

Abstract

The invention relates to a data query method which includes the steps that: a service node determines an adscription index node of a terminal according to the GUID of the terminal and the GUID of an index node, and the address information of the adscription data node of the terminal is acquired from the adscription index node; the service node calculates the GUID of the adscription data node according to the address information of the adscription data node, and the adscription heartbeat node of the adscription data node is determined according to the GUID of the adscription data node and the GUID of the index node; by the adscription heartbeat node, the service node acquires the status information of the adscription data node and sends a data query request to the adscription data node with the active status information. The invention also relates to a terminal data inserting method and further relates to a terminal data deleting method. By adopting the methods of the invention, fast data query, insertion and deletion can be realized.

Description

technical field [0001] The present invention relates to a data query method, an insertion method and a deletion method, in particular to a terminal data query method, an insertion method and a deletion method based on a distributed terminal data management framework. Background technique [0002] The traditional terminal data management adopts a centralized architecture, which has poor scalability and is not conducive to the expansion of hardware (capacity) and functions (applications); the existing terminal data management adopts a distributed architecture, which is divided into three layers. The front end (Front End, hereinafter referred to as FE), the back end (Back End, hereinafter referred to as BE), and the index layer (Index Server, hereinafter referred to as IS). Compared with the centralized architecture, its performance has been greatly improved. [0003] Front-end: It is a business node, responsible for specific business logic. The number of business nodes can be...

AI Technical Summary

Problems solved by technology

Index data query load distribution, such as figure 2 , each front-end has a built-in index node, each index node stores the index data of all users, and the index node only undertakes the query request of the front end, this method has the following defects, each index node needs to save the back-end Index data for all users, so index nodes are prone to storage bottlenecks

Index data storage distribution, such as image 3 , the index data is distributed on several index nodes, but each index node must undertake all user query requests from the front end, that is to say, the front end sends query requests to all index nodes by broadcasting, and has the query request specified The index node of the user index information will give a response, and the others do not need to give a response. This method has the following defects: because the front-end access to the index node is broadcast, so each index node needs to accept the front-end access, so making Index data query load increases for index nodes

Images