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Hypergraph partition algorithm-based related data storage method

A technology for related data and graph division, applied in the field of big data processing, can solve problems such as inconsistent network speed, severe network load, and delay

Inactive Publication Date: 2017-10-20
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

As an emerging technology, big data processing technology still has many shortcomings in many places, such as the delay caused by calling distributed data, the serious network load caused by huge data throughput and inconsistent network speed, etc.

Method used

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  • Hypergraph partition algorithm-based related data storage method
  • Hypergraph partition algorithm-based related data storage method
  • Hypergraph partition algorithm-based related data storage method

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Embodiment Construction

[0018] The basic idea of ​​this patent is that, for a certain demand pattern, a binary relationship between the demand pattern and the storage data nodes of the data center is established according to the data required by the demand pattern. According to the binary relationship and the proposed metric, a function mapping relationship in which data is stored in data nodes is constructed. The details are as follows.

[0019] 1. Data items and nodes

[0020] X represents a set of m data items stored on the data node, and each task needs to transmit d different data items from the set X. Suppose the pattern demand space is The demand pattern in practical applications is only a subset of this space, with express. Such as figure 1 shown. There are five data items in the legend, three different demand patterns.

[0021] Y represents a set containing n storage nodes. Initially, assume that each data item x∈X is stored in a unique node y∈Y. Let the rule of storing the crawle...

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Abstract

The invention relates to a hypergraph partition algorithm-based related data storage method. The method comprises the steps of calling a task needed to be subjected to data processing as a demand mode, wherein the demand mode needs multiple pieces of data stored in a data center node; after the demand mode is determined, predicting a demand rate; according to the setting of the demand rate, selecting a measurement standard, namely, a hypergraph partition standard; building a hypergraph model; performing a coarse partition process; performing an initialization process; and performing an optimization process: randomly selecting fission nodes for k sub-graphs, performing fission recovery in sequence, constructing a series of hypergraphs, until the scale reaches the scale of original un-weighted hypergraphs, and obtaining k optimized sub-graphs.

Description

technical field [0001] The invention belongs to the technical field of big data processing, and relates to a related data storage method. Background technique [0002] With the rapid development and popularization of the Internet, the amount of global data has shown explosive growth, and we have entered an era of information explosion. In the face of massive and complex data, it is normal for the amount of information processing to reach TB level or even PB level, and the concept of big data came into being. Compared with traditional data, people summarize the characteristics of big data into four Vs, namely large data volume (Volume), fast speed (Velocity), multiple types (Variety) and low value density (Value). The large amount of data can still be alleviated to a certain extent by expanding storage, but the requirement of timely response, data diversity and data uncertainty cannot be solved by traditional data processing methods. In order to cope with the difficulties a...

Claims

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Application Information

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IPC IPC(8): G06F9/50
CPCG06F9/5011
Inventor 王宝亮张光荣常鹏张荧允
Owner TIANJIN UNIV
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