Dynamic data transferring method based on graph databases and graph database cluster

A dynamic data and database technology, applied in the field of data processing, can solve the problem of not being able to improve the linear expansion of read performance, and achieve the effect of avoiding the bottleneck of writing

Active Publication Date: 2018-02-06
北京知道未来信息技术有限公司
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Problems solved by technology

[0006] However, most of the existing graph databases use the operation mode of synchronous writing and concurrent reading between single nodes.
Obviously, although this method can realize the linear expansion of the storage capacity and write performance of the graph database, it cannot improve the linear expansion of the read performance and has limitations.

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  • Dynamic data transferring method based on graph databases and graph database cluster
  • Dynamic data transferring method based on graph databases and graph database cluster

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Embodiment Construction

[0029] working principle:

[0030] The storage capacity of graph databases is heavily dependent on hardware resources, especially Neo4j databases, and the data storage capacity of single-node databases is facing an upper limit bottleneck. It is normal for existing graph databases to form a cluster with multi-node graph databases. The present invention implements dynamic migration of data between multiple nodes by introducing an arbitration module. When the data capacity of a single-node database faces a bottleneck, the arbitration module realizes the dynamic migration of the database, and dynamically migrates the data on the node with high pressure to the node with low data pressure, so as to realize the data balance between each node and achieve the best graph Data storage and query performance.

[0031] The invention relates to dynamic data migration of graph databases.

[0032] One scenario is that when the storage capacity of an enterprise's graph database faces a capaci...

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Abstract

The invention provides a dynamic data transferring method based on graph databases. The method includes the steps of dividing metadata into to-be-expanded data and non-to-be-expanded data according tothe relation of metadata of different types in the graph databases when the capacity of the graph databases serving as nodes in a cluster exceeds a preset threshold, and recording the to-be-expandeddata in to-be-expanded graph databases serving as newly-added nodes of the cluster. By introducing an arbitration module, the dynamic transferring of data between the multiple single-node graph databases is realized. When the capacity of data of a certain single-node graph database faces a bottleneck, database dynamic transferring is realized through the arbitration module, data on the nodes largein pressure is dynamically transferred to the nodes small in data pressure, and therefore the data balance among all the nodes is realized, the graph data storage capacity and the write performance linearity are increased, and meanwhile a corresponding graph database cluster is provided.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a graph database, and in particular to a graph database-based dynamic data migration method and a graph database cluster. Background technique [0002] Graph database refers to a type of NoSQL database, which is a non-relational database that uses graph theory to store relational information between entities. [0003] For example, the relationship between people in a social network, in the graph database, each person is represented as a point, and the relationship between people is represented by the edges between points and points. Traditional relational databases are not ideal for storing "relational" data, and often have the defects of complex and slow queries, while graph databases can perfectly make up for this defect. [0004] There are many existing graph databases, including but not limited to: Neo4j, Arangodb, Orientdb and other graph databases. [0005] Common...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/214G06F16/2237G06F16/288G06F16/51
Inventor 陈效友刘理鑫
Owner 北京知道未来信息技术有限公司
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