Data compression method, decompression method, system and related device for graph data

A compression method and technology for graph data, applied in file systems, file system functions, special data processing applications, etc., can solve problems such as large decoding logic, time-consuming, and difficulty in copying multiple node information in parallel, and increase processing bandwidth. Effect
CN111046002BActive Publication Date: 2022-08-02INSPUR BEIJING ELECTRONICS INFORMATION IND
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Patents(China)
Current Assignee / Owner
INSPUR BEIJING ELECTRONICS INFORMATION IND
Publication Date
2022-08-02

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Abstract

The present application provides a method for compressing graph data, including: obtaining original graph data and determining a node pair of each edge in the original graph data; grouping the same source nodes in the node pair according to preset grouping rules; A source node; store the corresponding FIFO according to the group type of each group; add labels to the source node data of the source node and the destination node data of the destination node; poll and store the FIFO to obtain compressed graph data. The present application enables source nodes with different numbers of corresponding destination nodes to adopt different compression rates, only one source node is reserved in the same group, and there is no need to store duplicate source nodes. It can support large-scale parallel decompression of graph data and greatly increase the bandwidth of graph data processing. The present application also provides a data compression system for a graph computing system, a computer-readable storage medium, and a data compression terminal, which have the above beneficial effects.
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Description

technical field

[0001] The present application relates to the field of data storage, and in particular, to a compression method, decompression method, compression system and related devices for graph data. Background technique

[0002] In the era of big data, a large amount of data interacts with each other to form a large-scale graph, which is widely used in various algorithms such as PageRank. At present, the scale of graphs often reaches the order of tens of millions to hundreds of millions of nodes, and the edge (connection between nodes and nodes) information of the graph reaches the scale of billions. Usually, Internet graph data is in a sparse matrix format. The storage methods that can be used include COO and CSR. COO adopts the triple format of <source node, destination node, weight>. Considering that a node is represented by 4 bytes, then a Edges require 12 bytes of storage. CSR considers that nodes in the same row have the same address and only stores the ...

Claims

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