CN102323957B - Distributed parallel Skyline query method based on vertical dividing mode - Google Patents
Distributed parallel Skyline query method based on vertical dividing mode Download PDFInfo
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Abstract
The invention discloses a distributed parallel Skyline query method based on a vertical dividing mode and aims to provide a new Skyline query method for fully developing the parallelism of Skyline query processing and improving efficiency. The invention adopts the technical scheme that: the method comprises the following steps that: a distributed parallel computing environment which consists of a coordination node and N computing nodes is constructed, wherein the coordination node has a task scheduling program and a result analysis processing program, and the computing nodes have query processing programs; the coordination node executes the task scheduling program and distributes a Skyline query processing task to each computing node; each computing node executes the query processing program, receives the Skyline query processing task from the coordination node and performs Skyline query processing; and the coordination node executes the result analysis processing program to collect a Skyline set LS of all computing nodes and performs Skyline query processing on the Skyline set LS to obtain a final Skyline query result. By adoption of the method, load balancing between the computing modes can be effectively guaranteed, the accuracy of the Skyline query result is guaranteed, and query efficiency is improved.
Description
Technical field
The present invention relates to the distributed parallel disposal route of Skyline inquiry, especially based on the efficient distributed parallel Skyline querying method of data vertical division pattern.
Background technology
Skyline inquiry is one of key problem of needing to be resolved hurrily of Mass Data Management field.The Skyline inquiry is meant from the set of data objects S of a given D dimension selects a sub-set, and any data object in this subclass all can not be controlled by any other data object among the S.So-called control relation is meant in the set of data objects S of D dimension; If data object p is superior to another data object q at least on a certain dimension; And data object p on other dimensions all unlike data object q poor (p be superior to or equal q), data object p can control data object q so.The Skyline inquiry is one of typical method that solves at present multi-objective optimization question, and the important technical of Skyline inquiry having become data analysis and information extraction all has important application at numerous areas such as city navigation, market analysis, environmental monitorings.
In recent years, the fast development of Along with computer technology, network technology and the communication technology, people obtain, the ability of storage and Data transmission strengthens day by day, and the scale of data sharply expands, and " big data " arise at the historic moment as the product of information explosion.Continuous increase along with the data set scale; It is complicated more that the data processing of Skyline inquiry becomes; To the also sharp increase of demand of storage resources and computational resource, the treatment effeciency of Skyline inquiry becomes the key factor that influences data analysis and information extraction effect gradually.
Along with the continuous development of network calculations patterns such as cluster calculating, grid computing, equity calculating, cloud computing, the distributed parallel computing technique has reached its maturity, and becomes one of effective technical way that improves mass data processing efficient gradually.Distributed parallel calculates calculation task is distributed on the resource pool of great amount of calculation mechanism one-tenth, makes various application systems can obtain computing power, storage space and various software service as required.The distributed parallel computing technique is combined with the Skyline inquiry of mass data, can improve query processing efficient through the concurrency that the exploitation inquiry is calculated.
At present, the pattern of DATA DISTRIBUTION mainly comprises horizontal division pattern and vertical division pattern.The horizontal division pattern is meant DATA DISTRIBUTION on a plurality of nodes, and the data of each node storage are the parts of whole data set, and the data of each node storage are the complete data objects that covers whole dimensions.The vertical division pattern is meant that DATA DISTRIBUTION is on a plurality of nodes; The data of each node storage are the parts of whole data set; And the data of each node storage are all data objects all data on one or more dimension, rather than complete data object.Existing distributed parallel Skyline querying method (W.-T.Balke based on the vertical division pattern; U.G ü ntzer; J.Zheng.Efficient Distributed Skylining for Web Information Systems.In Proc of the Int.Conf.on Extending Database Technology (EDBT ' 04), Heraklion, Crete; Greece; 2004,256-273.) DATA DISTRIBUTION with different dimensions is stored on each computing node, and each computing node is responsible for the dimension data of storage is separately sorted; The unified then coordinator node that sends to, coordinator node is responsible for carrying out the Skyline query processing based on the ranking results of each computing node.This shows; A large amount of query processing tasks mainly concentrates on coordinator node; The concurrency of Skyline query processing is not fully developed; The data-handling capacity of computing node is not fully used, thereby causes the treatment effeciency of distributed parallel Skyline querying method very limited, is difficult to the actual demand of abundant satisfying magnanimity data analysis and information extraction.
Therefore; How to be directed against the essential characteristic of mass data and Skyline inquiry thereof; Resources characteristic in conjunction with the distributed parallel computing environment; Design guarantees the correctness of Skyline efficiency of query and Query Result based on the efficient distributed parallel Skyline querying method of vertical division pattern, has become hot research problem parallel and the distribution process field.
Summary of the invention
The technical matters that the present invention will solve is: to the existing not high problem of distributed parallel Skyline querying method treatment effeciency based on the vertical division pattern; A kind of distributed parallel Skyline querying method based on the vertical division pattern is proposed; Fully develop the concurrency of Skyline query processing; Under the prerequisite of the correctness that guarantees Query Result, significantly improve the Skyline efficiency of query.
Technical scheme of the present invention may further comprise the steps:
The first step makes up a distributed parallel computing environment, and it is made up of a plurality of nodes, but each node all is the computing machine of an independent operating, and each node is through network equipment interconnection.
Node in the distributed parallel computing environment is divided into two types: coordinator node and computing node.The distributed parallel computing environment comprises a coordinator node; Coordinator node is responsible for storing the numbering of all concentrated data objects of raw data; Be responsible for and user interactions; Receive the query requests that the user submits to, distribute query processing task and collect the query processing result to each computing node, and return Query Result to the user.The distributed parallel computing environment comprises that (N is the dimension number that raw data is concentrated data object to N computing node; N is a positive integer); Each computing node is responsible for storing all data on the dimension of raw data set; Computing node is carried out query processing task, and returns the query processing result to coordinator node.Operating system, ICP/IP protocol software all are installed on coordinator node and the computing node, have disposed network environment.
Task dispatch and interpretation of result handling procedure are installed on the coordinator node.Task dispatch receives the Skyline query requests that the user submits to, to each computing node distribution Skyline query processing task.The interpretation of result handling procedure is responsible for collecting the Skyline query processing result of computing node, and the Skyline query processing result of all computing nodes of collecting is carried out the Skyline query processing again to obtain final Skyline Query Result.Inquiry processing program is installed on the computing node.Inquiry processing program is responsible for receiving the Skyline query requests from coordinator node, and the raw data set of storing on the computing node is carried out the Skyline query processing.
In second step, the coordinator node scheduler program of executing the task is to each computing node distribution Skyline query processing task; Each computing node is carried out inquiry processing program, receives the Skyline query processing task from coordinator node, walks abreast and carries out the Skyline query processing.
2.1 the task dispatch of coordinator node receives the Skyline query requests that the user submits to;
2.2 the task dispatch of coordinator node is to all computing node distribution Skyline query processing tasks.Concrete steps are following:
(M is a data object numbering sum with all M data object numbers of raw data set 2.2.1 task dispatch is according to the number N of computing node; M is a positive integer) be divided into N impartial data object number of size and gather; Each data object numbering set comprises the individual data object number in [M/N] individual perhaps ([M/N]+1), and [M/N] expression is no more than the maximum integer of M/N;
2.2.2 task dispatch is distributed the Skyline query requests to all computing nodes, and to data object number set of each computing node distribution.
2.3 the inquiry processing program of each computing node receives the Skyline query processing task from coordinator node; According to the Skyline query requests that receives the set of data objects of being responsible for separately (set that the data object numbering set corresponding data objects of promptly receiving constitutes) is carried out the Skyline query processing, concrete steps are following:
2.3.1 inquiry processing program receives from the Skyline query requests of coordinator node and the set of data object numbering;
2.3.2 the set of inquiry processing program initial interrogation result is called for short Skyline set
2.3.3 inquiry processing program obtains whole dimension datas of all data objects the set of data objects that computing node is responsible for from other computing nodes, forms local (i.e. computing node under this inquiry processing program) raw data set Set;
2.3.4 inquiry processing program is judged the control relation that all data objects among the local raw data set Set carry out between the data object one by one, the data object of not controlled by any other data object among the Set is put among the Skyline set LS, that is,
Judge each data object DO and the control relation between the every other data object among the Set among the local raw data set Set; If DO is not controlled by any other data object among the Set; Then DO is put into the Skyline set LS of computing node, that is, and LS=LS+{DO};
2.3.5 gathering LS with Skyline, inquiry processing program returns to coordinator node.
In the 3rd step, the interpretation of result handling procedure of coordinator node is collected the Skyline set LS of all computing nodes, and it is carried out the Skyline query processing, obtains final Skyline Query Result.
3.1 the interpretation of result handling procedure is collected the Skyline set LS of all computing nodes;
3.2 the interpretation of result handling procedure merges the Skyline set LS of all computing nodes, obtains new data set NS;
3.3 the Skyline of initialization coordinator node gathers
3.4 the interpretation of result handling procedure carries out the Skyline query processing to NS; Promptly; Control relation among each data object N_DO among the judgement NS and the NS between the every other data object if N_DO is not controlled by any other data object among the NS, is put into N_DO the Skyline set GS of coordinator node so; That is GS=GS+{N_DO};
3.5 gathering GS with Skyline, the interpretation of result handling procedure returns to the user.
Compared with prior art, the present invention has following technological merit:
1. 2.2.1 step of the present invention and 2.2.2 step coordinator node distribute query processing task according to the balanced number of computing node, effectively guarantee the load balancing between the computing node, for the concurrency of fully developing the Skyline query processing lays the foundation.
2. exchange dimension data each other between 2.3.3 each computing node of step of the present invention, form local raw data set separately; 2.3.4 of the present invention each computing node of step carries out the Skyline query processing to separately local raw data set simultaneously; Under the prerequisite of the correctness that guarantees Skyline query processing result; Develop the concurrency of Skyline query processing to greatest extent, improved Skyline query processing efficient.
Description of drawings
Fig. 1 is the distributed parallel computing environment structural drawing that the first step of the present invention makes up.
Fig. 2 is the Software deployment figure of distributed parallel computing environment of the present invention.
Fig. 3 is a general flow chart of the present invention.
Fig. 4 is that execute the task scheduler program, each computing node of the present invention second step coordinator node carried out the process flow diagram of inquiry processing program.
Fig. 5 is that the Skyline of all computing nodes of the present invention's the 3rd step coordinator node execution result analysis and processing program collection gathers LS, carries out the Skyline query processing to obtain the process flow diagram of final Skyline Query Result.
Embodiment
Fig. 1 is the structural drawing of the distributed parallel computing environment of first step structure of the present invention.The node of distributed parallel computing environment is made up of coordinator node and computing node.Coordinator node and computing node all are the computing machines that comprise processor, storer, disk and network interface.Link to each other through interconnection network between coordinator node and the computing node.
Fig. 2 is the Software deployment figure of distributed parallel computing environment of the present invention.Operating system, ICP/IP protocol software, task dispatch and interpretation of result handling procedure are installed on the coordinator node.Wherein the above two are common softwares, can from the software package of public publication, obtain; Both are special softwares of the present invention for the backs.Operating system software, ICP/IP protocol software, inquiry processing program are installed on the computing node.Wherein the above two are common softwares, can from the software package of public publication, obtain; Inquiry processing program is a special software of the present invention.
Fig. 3 is a general flow chart of the present invention.Idiographic flow is following:
The first step makes up a distributed parallel computing environment, and it is made up of a plurality of nodes, but each node all is the computing machine of an independent operating, and each node is through network equipment interconnection.
In second step, the coordinator node scheduler program of executing the task is to each computing node distribution Skyline query processing task; Each computing node is carried out inquiry processing program, receives the Skyline query processing task from coordinator node, walks abreast and carries out the Skyline query processing.
In the 3rd step, the interpretation of result handling procedure of coordinator node is collected the Skyline set LS of all computing nodes, and it is carried out the Skyline query processing, obtains final Skyline Query Result.
Fig. 4 is that execute the task scheduler program, each computing node of the present invention second step coordinator node carried out the process flow diagram of inquiry processing program.Idiographic flow is following:
2.1 the task dispatch of coordinator node receives the Skyline query requests that the user submits to;
2.2 the task dispatch of coordinator node is to all computing node distribution Skyline query processing tasks.Concrete steps are following:
2.2.1 task dispatch is divided into N impartial data object number set of size according to the number N of computing node with all M data object numbers of raw data set, each data object numbering is gathered and is comprised the individual data object number in [M/N] individual perhaps ([M/N]+1);
2.2.2 task dispatch is distributed the Skyline query requests to all computing nodes, and to data object number set of each computing node distribution.
2.3 the inquiry processing program of each computing node receives the Skyline query processing task from coordinator node; According to the Skyline query requests that receives the set of data objects of being responsible for separately (set that the data object numbering set corresponding data objects that promptly receives constitutes) is carried out the Skyline query processing, concrete steps are following:
2.3.1 the inquiry processing program of computing node receives from the Skyline query requests of coordinator node and the set of data object numbering;
2.3.2 the set of the inquiry processing program initial interrogation result of computing node is called for short Skyline set
2.3.3 the inquiry processing program of computing node obtains whole dimension datas of all data objects the set of data objects that computing node is responsible for from other computing nodes, forms local (i.e. computing node under this inquiry processing program) raw data set Set;
2.3.4 the inquiry processing program of computing node is judged the control relation that all data objects in the set of data objects of being responsible for carry out between the data object one by one, obtains Skyline set LS;
2.3.5 gathering LS with Skyline, the inquiry processing program of computing node returns to coordinator node.
Fig. 5 is that the Skyline of all computing nodes of the present invention's the 3rd step coordinator node execution result analysis and processing program collection gathers LS, carries out the Skyline query processing to obtain the process flow diagram of final Skyline Query Result.Idiographic flow is following:
3.1 the interpretation of result handling procedure is collected the Skyline set LS of all computing nodes;
3.2 the interpretation of result handling procedure merges the Skyline set LS of all computing nodes, obtains new data set NS;
3.3 the Skyline of initialization coordinator node gathers
3.4 the interpretation of result handling procedure carries out the Skyline query processing to NS; Promptly; Control relation among each data object N_DO among the judgement NS and the NS between the every other data object if N_DO is not controlled by any other data object among the NS, is put into N_DO the Skyline set GS of coordinator node so; That is GS=GS+{N_DO};
3.5 gathering GS with Skyline, the interpretation of result handling procedure returns to the user.
Claims (1)
1. distributed parallel Skyline querying method based on the vertical division pattern is characterized in that may further comprise the steps:
The first step makes up a distributed parallel computing environment, and it is made up of a plurality of nodes, but each node all is the computing machine of an independent operating, and each node is through network equipment interconnection; Node comprises a coordinator node and N computing node, and N is the dimension number that raw data is concentrated data object, and N is a positive integer; Coordinator node is responsible for storing the numbering of all concentrated data objects of raw data, is responsible for and user interactions, receives the query requests that the user submits to, distributes query processing task and collects the query processing result to each computing node, and return Query Result to the user; All data on the dimension of each computing node storage raw data set, computing node is carried out query processing task, and returns the query processing result to coordinator node; Operating system, ICP/IP protocol software all are installed on coordinator node and the computing node, have disposed network environment; Task dispatch and interpretation of result handling procedure are installed on the coordinator node; Task dispatch receives the Skyline query requests that the user submits to; To each computing node distribution Skyline query processing task; The interpretation of result handling procedure is responsible for collecting the Skyline query processing result of computing node, and the Skyline query processing result of all computing nodes of collecting is carried out the Skyline query processing again to obtain final Skyline Query Result; Inquiry processing program is installed on the computing node, and inquiry processing program is responsible for receiving the Skyline query requests from coordinator node, and the raw data set of storing on the computing node is carried out the Skyline query processing;
In second step, the coordinator node scheduler program of executing the task is to each computing node distribution Skyline query processing task; Each computing node is carried out inquiry processing program, receives the Skyline query processing task from coordinator node, walks abreast and carries out the Skyline query processing:
2.1 the task dispatch of coordinator node receives the Skyline query requests that the user submits to;
2.2 the task dispatch of coordinator node is to all computing node distribution Skyline query processing tasks, concrete steps are following:
2.2.1 task dispatch is divided into all M data object numbers of raw data set according to the number N of computing node N data object number set of size equalization; Each data object numbering set comprises [M/N] individual perhaps [M/N]+1 data object number; M is a data object numbering sum; M is a positive integer, and [M/N] expression is no more than the maximum integer of M/N;
2.2.2 task dispatch is distributed the Skyline query requests to all computing nodes, and to data object number set of each computing node distribution;
2.3 the inquiry processing program of each computing node receives the Skyline query processing task from coordinator node; According to the Skyline query requests that receives the Skyline query processing is carried out in the set that the data object numbering set corresponding data objects of receiving constitutes, concrete steps are following:
2.3.1 inquiry processing program receives from the Skyline query requests of coordinator node and the set of data object numbering;
2.3.2 the set of inquiry processing program initial interrogation result is called for short Skyline set
2.3.3 inquiry processing program obtains whole dimension datas of all data objects the set of data objects that computing node is responsible for from other computing nodes, forms local raw data set Set;
2.3.4 inquiry processing program is judged the control relation that all data objects among the local raw data set Set carry out between the data object one by one; The data object of not controlled by any other data object among the Set is put among the Skyline set LS; Promptly; Judge each data object DO and the control relation between the every other data object among the Set among the local raw data set Set,, then DO is put into the Skyline set LS of computing node if DO is not controlled by any other data object among the Set; That is LS=LS+{DO};
2.3.5 gathering LS with Skyline, inquiry processing program returns to coordinator node;
In the 3rd step, the interpretation of result handling procedure of coordinator node is collected the Skyline set LS of all computing nodes, and it is carried out the Skyline query processing, obtains final Skyline Query Result:
3.1 the interpretation of result handling procedure is collected the Skyline set LS of all computing nodes;
3.2 the interpretation of result handling procedure merges the Skyline set LS of all computing nodes, obtains new data set NS;
3.3 the Skyline of initialization coordinator node gathers
3.4 the interpretation of result handling procedure carries out the Skyline query processing to NS; Promptly; Control relation among each data object N_DO among the judgement NS and the NS between the every other data object if N_DO is not controlled by any other data object among the NS, is put into N_DO the Skyline set GS of coordinator node so; That is GS=GS+{N_DO};
3.5 gathering GS with Skyline, the interpretation of result handling procedure returns to the user.
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| CN103150327A (en) * | 2012-12-21 | 2013-06-12 | 北京大学软件与微电子学院无锡产学研合作教育基地 | Skyline inquiry method based on multi-tenant data base in SaaS environment |
| CN103942197B (en) * | 2013-01-17 | 2018-06-26 | 阿里巴巴集团控股有限公司 | Data monitoring processing method and equipment |
| CN103207915B (en) * | 2013-04-18 | 2016-12-28 | 苏州大学 | A kind of reverse skyline query, Apparatus and system |
| CN104111936B (en) * | 2013-04-18 | 2017-12-05 | 阿里巴巴集团控股有限公司 | Data query method and system |
| US10198481B2 (en) | 2014-01-07 | 2019-02-05 | Indian Institute Of Technology Kanpur | Multiple criteria decision analysis in distributed databases |
| CN106599190A (en) * | 2016-12-14 | 2017-04-26 | 大连交通大学 | Dynamic Skyline query method based on cloud computing |
| CN106777093B (en) * | 2016-12-14 | 2021-01-01 | 大连大学 | Skyline inquiry system based on space time sequence data flow application |
| CN107967431A (en) * | 2017-12-20 | 2018-04-27 | 南京航空航天大学 | A kind of secret protection skyline querying methods on vertical distribution data set |
| CN109933710A (en) * | 2019-02-27 | 2019-06-25 | 生活空间(沈阳)数据技术服务有限公司 | A kind of data query method, apparatus and storage medium, program product |
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