Quick retrieval method based on graph data structure

Abstract

The invention discloses a quick retrieval method based on a graph data structure. The method comprises the following steps that: (1) data source collection: through manual importing, forming the basicstructure of a graph in memory, monitoring a plurality of data collection systems in real time through distributed message middleware, and when a data collection system receives a data source updatechange request, feeding back the information to a distributed system for real-time update; (2) retrieval request query: monitoring a graph data query request generated by the query system in real timeby the distributed message middleware, and when the request is received, distributing the request to a plurality of distributed nodes to be executed in parallel, and quickly returning to the query system; (3) graph data retrieval: according to the request of the message middleware, carrying out parallel computing retrieval by each distributed node; and (4) retrieval result sending: carrying out integration on the result of the distributed nodes on the basis of memory parallel query retrieval, and sending query results to message requesters through multiple threads.

Description

technical field [0001] The invention relates to the technical field of big data retrieval, in particular to a fast retrieval method based on a graph data structure. Background technique [0002] In the information age, persisting data into a relational database is a very traditional way of persisting data. However, with the advent of the era of big data, this data storage method brings great challenges to the query and retrieval of big data. The difficulties are mainly reflected in cumbersome operation, slow speed, slow real-time update retrieval, etc. In order to solve this problem, the applicant provides a technical solution, which realizes the storage and association of multi-source data through the connected graph structure, and realizes the distributed storage and parallel retrieval query of graph data with the help of distributed parallel computing technology, and Updating the data source only needs to re-change the structure and connection attributes of the graph dat...

AI Technical Summary

Problems solved by technology

[0002] In the information age, persisting data into a relational database is a very traditional way of persisting data. However, with the advent of the era of big data, this data storage method brings great challenges to the query and retrieval of big data. Difficulties, mainly reflected in cumbersome operation, slow speed, slow real-time update retrieval, etc.

Images