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Parallel processing method and system for uncertain contour query based on n-of-n flow model

An n-of-n, parallel processing technology, applied in the field of contour query parallel processing, can solve problems such as the inability to meet the real-time query processing requirements of large-scale uncertain data streams, achieve efficient parallel query processing, maximize parallel efficiency, realize The effect of load balancing

Active Publication Date: 2021-07-16
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

However, the existing n-of-N contour query methods for uncertain data streams are mainly designed and implemented for centralized processing environments, which cannot meet the real-time query processing requirements of large-scale uncertain data streams. Efficient Uncertain Contour Query Parallel Processing Method for N-flow Model

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  • Parallel processing method and system for uncertain contour query based on n-of-n flow model
  • Parallel processing method and system for uncertain contour query based on n-of-n flow model
  • Parallel processing method and system for uncertain contour query based on n-of-n flow model

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Embodiment Construction

[0042] see figure 1 In this embodiment, the implementation steps of the parallel processing method for uncertain contour query based on the n-of-N flow model include:

[0043] 1) Initialize the global sliding window DS N And each computing node P in the computing node set P i Corresponding to the local local sliding window, judge whether there is a new flow data tuple (stream data tuple of uncertain flow data) arrives, and jump to perform step 2 when a new flow data tuple arrives);

[0044] 2) According to W=W+e new -e old Global sliding window DS for update maintenance N , where W is the global sliding window DS N the size of e new is the newly arrived stream data tuple e new the size of e old For the global sliding window DS N Because the newly arrived stream data tuple e new Stream data tuples expired with the arrival of e old the size of;

[0045] 3) The newly arrived stream data tuple e new Mapped to the corresponding computing node P in the computing node se...

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Abstract

The invention discloses a parallel processing method and system for uncertain contour query based on an n-of-N flow model. The invention aims at efficient n-of-N contour query of large-scale uncertain data streams, and will perform the query in the global sliding window The query processing task of the data tuple is divided into multiple local local sliding windows according to a certain task mapping rule, and the query processing tasks of the local local sliding window are distributed to multiple computing nodes. Perform parallel query processing, and return query results after processing all data tuples. The present invention can realize load balancing among computing nodes, maximize parallel efficiency, support parallel query of large-scale computing node numbers, and realize efficient n-of-N query parallel processing.

Description

technical field [0001] The present invention relates to a parallel processing technology for contour query based on n-of-N flow model, in particular to a parallel processing method and system for uncertain contour query based on n-of-N flow model, which is suitable for multi-objective decision-making and market analysis , data mining, recommendation system, environmental monitoring, econometrics and other application fields. Background technique [0002] Uncertain flow data is a general term for a type of flow data whose value cannot be directly and accurately determined. It exists in many practical applications such as location-based services, radio frequency identification (RFID) networks, commodity trading networks, and radar monitoring systems. Efficient and complex query analysis of uncertain data streams has become a key research direction in the field of big data analysis, and it is of great significance in real life. [0003] Contour query (i.e. Skyline query) is us...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/24
Inventor 李小勇刘军李小玲任开军邓科峰任小丽赵娟
Owner NAT UNIV OF DEFENSE TECH
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