Graph data processing method and system for massive time series data
A technology of time series data and processing methods, which is applied in the fields of electrical digital data processing, special data processing applications, relational databases, etc., can solve the problem of insufficient consideration of graph data storage, the inability of graph data processing technology to express time series interaction, and graph data processing programming. Model calculation time and storage space waste, to achieve the effect of saving computing time, saving memory space, efficient storage and query performance
Active Publication Date: 2014-02-19
INST OF INFORMATION ENG CHINESE ACAD OF SCI
View PDF2 Cites 14 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0010] The technical problem to be solved by the present invention is to provide a graph data processing method and system for massive time-series data. The vertex-based graph data processing programming model has a huge waste of computing time and storage space.
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0065] The principles and features of the present invention will be described below with reference to the accompanying drawings. The examples cited are only used to explain the present invention, and are not used to limit the scope of the present invention.
[0066] Such as figure 1 As shown, a graph data processing method for massive time series data includes the following steps:
[0067] Step 1: Preprocess social network data, and abstract a graph structure with vertices representing characters and several timestamped edges representing the interaction between characters;
[0068] Step 2: According to celebrity effect, divide the graph structure into several graph structure blocks according to the predetermined Euclidean distance, and number the graph structure blocks and the vertices inside;
[0069] Step 3: Assign the graph structure blocks to different nodes for processing, and each node will import the graph structure blocks it gets into the corresponding location in the memory a...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention relates to a graph data processing method and system for massive time series data. The graph data processing method for the massive time series data comprises the steps of carrying out preprocessing on social network data, and abstracting a graph structure which uses vertexes to represent figures, and uses a plurality of edges with timestamps to represent the interactive relationship among the figures, wherein the representing method can effectively represent a social network relationship with an interactive sequential relationship; dividing the graph structure into a plurality of graph structure blocks according to the celebrity charm and a preset Euclidean distance, and numbering the graph structure blocks and the vertexes of the interiors of the graph structure blocks; leading the graph structure blocks in corresponding positions of a memory according to the organization mode of the memory, wherein the storage mode of the memory makes full use of the distribution characteristics of graph data, and efficient storage performance and efficient query performance can be achieved. According to the graph data processing method for the massive time series data, an original programming model using the vertexes as calculation units is improved on the basis of the principle that the calculation time and the memory space are saved, and a programming model using messages as calculation units is adopted, so that the calculation time is saved through the mode to a large extent, and the storage space is also saved.
Description
Technical field [0001] The invention relates to the field of large-scale graph data processing, in particular to a graph data processing method and system oriented to massive time series data. Background technique [0002] With the rapid development of the Internet in recent years, social networking platforms have also rapidly developed and become popular. The graph data is used to represent the relationship of the characters in the social network, and the graph algorithm can be used to mine the hidden information in the relationship of the social network. Therefore, with the development of social networks, graph data has once again ushered in an upsurge. [0003] However, with the gradual popularity of social networks, social network data is also showing an exponential growth trend. Therefore, it is impossible to use a stand-alone layout data processing program to analyze and process these large-scale map data. [0004] With the popularity of social networks and the large-scale s...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/288G06F16/958
Inventor 周薇高赟冉攀峰韩冀中
Owner INST OF INFORMATION ENG CHINESE ACAD OF SCI