Neighbor storage method based on data mapping algorithm

Abstract

The invention discloses a neighbor storage method based on a data mapping algorithm. The neighbor storage method comprises the following steps: utilizing a spectral Hash algorithm to carry out Hash mapping on a high-dimensional data sample to obtain the k-dimensional binary system Hash code of each high-dimensional data item; utilizing a Z-curve method to convert the k-dimensional binary system Hash code of each high-dimensional data item to obtain the Z-Value value of each high-dimensional data item; utilizing a Chord method to construct a distributed node network, wherein the distributed node network consists of a Chord ring and m node servers distributed on the Chord ring; mapping and storing the Z-Value value of each high-dimensional data item into the node servers, and updating a node server routing table which obtains a stored node; and according to the high-dimensional data item to be queried, determining the Z-Value value of the high-dimensional data item to be queried, and searching the node server routing table of each node clockwise to find the node server where the high-dimensional data item is positioned. The neighbor storage method can realize neighbor storage and also can lower the switching expenditure of the node server, improve query accuracy, improve the operation efficiency of the whole system and lower network bandwidth when dependence query is carried out.

Description

technical field [0001] The invention relates to a neighbor storage method based on a data mapping algorithm, and belongs to the technical field of data mining and machine learning. Background technique [0002] With the rapid development of the Internet, the era of exponential growth of massive data has arrived. The explosive growth of massive resources is a great test for the existing storage system. In the face of high-dimensional and massive data, how to effectively store massive data and efficiently query effective data information is a problem worth studying. [0003] In order to more efficiently solve the storage problem of massive data, distributed storage came into being. The mainstream distributed storage technology is the P2P system. According to the point-to-point and distributed characteristics of P2P technology, it is added to the cloud storage system to effectively solve the bottleneck problem of the central server of the centralized cloud storage system. D...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a neighbor storage method based on the data mapping algorithm, which combines the spectral hash algorithm with the data mapping algorithm to map the data into the distributed storage network , which solves the problem of excessive system query overhead during correlation query when distributed storage in large-scale data scenarios, and improves data query efficiency

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