CN105956017A - Massive associated data processing system - Google Patents
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- CN105956017A CN105956017A CN201610255406.3A CN201610255406A CN105956017A CN 105956017 A CN105956017 A CN 105956017A CN 201610255406 A CN201610255406 A CN 201610255406A CN 105956017 A CN105956017 A CN 105956017A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
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Abstract
The invention relates to the technical field of Internet information processing, and especially relates to a massive associated data processing system. The system realizes automatic analysis of associated information of massive targets, and provides effective technical support for target background analysis, market popularization, risk prediction, and risk prevention and control. The system comprises a data storage module, a one-degree association calculation module, and an n-degree association calculation module, etc., wherein the one-degree association calculation module and the n-degree association calculation module are respectively connected with the data storage module. The data storage module is used for storage of basic data and processed data. The one-degree association calculation module extracts the basic data from the data storage module according to set fields, and expands one-degree associated data of the target information according to the basic data. The n-degree association calculation module expands n-degree associated data of the target information according to the same information in two key value pairs in the one-degree associated data, and stores the n-degree associated data in the data storage module for next step processing.
Description
Technical field
The present invention relates to Internet technical field, process system particularly to a kind of magnanimity associated data
System.
Background technology
Along with development and the progress of science and technology of society, the contact between individuality or group becomes more
Adding closely, contact closely promotes fast propagation and the growth of information, and the world today is already
Entering the information age, along with explosive growth and the accumulation of information, big data age is the most recent
Face, data volume is big and value density low be but the difficulty perplexing the utilization of such mass data information excavating
Topic, inside the data of magnanimity, obtains the information that people are concerned about, the most accurately just as sea
It is difficult that pin is dragged at the end；Meanwhile in the face of the information of magnanimity, how to go to analyze certain category information it
Between dependency, and analyze information intrinsic value behind with this, just at layer higher, deeper
The value of data message is embodied in face, and in big data analysis, dependency is more important than cause effect relation,
But the data in the face of such magnanimity, it is desirable to analyze the association between data fast and accurately and close
System, the most difficult.
Actually in the information ocean of numerous and complicated, the contact between some information often than with
Contact between other information will the most much, and these to have certain information being closely connected past
Toward reflection is real-life particular kind of relationship between men or between group, these
Particular kind of relationship can make it influence each other in relevant society or economic activity or pin down；From
For spreading network information angle, grasp the informational linkage node of some keys for social management
With business activity, there is great positive effect, because for the angle of Information Communication, these
Information (or risk) spread speed of important informational linkage node or coverage can compare
Other information points are the widest；Such analysis can be used in such as public sentiment supervision, pathophoresis
Control or the field such as advertisement putting.
For another one angle, for specific information object, how to analyze this target with
Incidence relation between other targets has actual meaning in a lot of fields, because having
The target of incidence relation often has bigger than individually simple individuality when carrying out various activity
The face that affects, and have the target of incidence relation externally set up various movable time, by interior
Mutually pining down or supporting of the incidence relation in portion, can be more multiple than the event trace of simple target
Miscellaneous.And in actual life, the incidence relation between information object is extremely complex, and typically
Being hiding, people can not be perceived by surface activity or surface information, is more difficult to
Find out whether this target has incidence relation, or which kind of incidence relation with other targets.?
Under such circumstances, the socio-economic activity of people can be brought very by these implicit incidence relations
The most potential value or risk.The implicit associations analyzing these closes the data surface tying up to magnanimity
Front will become more difficult, if these tasks are realized one by one by individual, huge by expending
Manpower and time cost；It is badly in need of a kind of processing system, helps analyst this huge to realize
Loaded down with trivial details calculating process, it is provided that this analysis result.
Summary of the invention
It is an object of the invention to overcome the deficiency in the presence of prior art, it is provided that a kind of magnanimity
Associated data processing system, native system can be arranged as required in magnanimity internet information
Analyze target, and then analyze whether have between different target incidence relation and be which kind of close
Connection relation, the degree of depth for data message is excavated and application provides the very reliable way easily of one
Footpath.
For achieving the above object, the present invention provides a kind of magnanimity associated data processing system, including
Data memory module, once associated computing module and n degree association computing module, wherein said
Once associating calculating to associate computing module with n degree and be connected with data memory module respectively；
The described computing module that once associating is according to original from data memory module of field arranged
Extracting data goes out basic data, chooses content corresponding to one of them field in basic data and makees
For target information, it is target information once associated data by Information expansion corresponding for other fields；
Described n degree incidence relation computing module is according to identical letter in not identical degree associated data group
Interest statement unit expands the n degree associated data of target information, and described n degree associated data is stored in
In data memory module, wherein n ＞ 1.
Preferred as one, described system uses the collection gang fight of the big data processing shelf of Hadoop
Structure.
Further, described system will once be associated computing module associated with n degree by host node
After the task automatic segmentation of computing module, distribution is located in each node of cluster internal parallel
Reason.
Further, described data memory module is HDFS.
Further, described system also includes client, described client and described host node phase
Even.
Further, the described computing module that once associating is associated by described client with described n degree
The task of computing module loads in described host node.
Further, N degree associated data is extracted by described client by described host node
Come, wherein N >=1.
Further, described system also includes HBase data base, and described HBase data are used
In storage N degree associated data.
Further, described system also includes that initial data acquisition module, described initial data obtain
Delivery block obtains web data by reptile, and the web data got is stored in HDFS
In.
Compared with prior art, beneficial effects of the present invention: one magnanimity associated data of the present invention
Processing system, from the basic data of magnanimity, the related keyword information of extraction and analysis target, profit
With information unit identical in different basic datas, the relevant information with implicit contact is excavated
Out, process for relevant data and data mining provides a kind of brand-new approach.In addition book
Invention system uses the framework of the big data processing shelf of cloud computing platform, is come real by host node
The automatic segmentation of current task and distribution, achieve sea in the case of being indifferent to bottom running
The parallel processing of amount associated data, the cutting of task and calling by big data processing shelf of resource
In host node be automatically obtained, data volume is big, and treatment effeciency is high.
Accompanying drawing illustrates:
Fig. 1 is the modular structure schematic diagram of this magnanimity associated data processing system.
Fig. 2 is the operation principle schematic diagram of present system.
Fig. 3 is present system associated data extension principle schematic diagram.
Fig. 4 is system structure schematic diagram in embodiment 1.
Fig. 5 is the basic data schematic diagram extracted in embodiment 1.
Fig. 6 is 1 degree of incidence relation schematic diagram in embodiment 1.
Fig. 7 is two degree of incidence relation schematic diagrams in embodiment 1.
Fig. 8 is three degree of incidence relation schematic diagrams in embodiment 1.
Should be appreciated that accompanying drawing of the present invention is schematically, do not represent concrete step and path.
Detailed description of the invention
Below in conjunction with test example and detailed description of the invention, the present invention is described in further detail.
But this should not being interpreted as, the scope of the above-mentioned theme of the present invention is only limitted to below example, all bases
The technology realized in present invention belongs to the scope of the present invention.
The present invention provides a kind of magnanimity associated data processing system, as shown in Figure 1: include data
Memory module, once associate computing module and n degree association computing module, wherein said once
Association calculating associates computing module with n degree and is connected with data memory module respectively；
The described computing module that once associating is according to original from data memory module of field arranged
Extracting data goes out basic data, chooses content corresponding to one of them field in basic data and makees
For target information, it is target information once associated data by Information expansion corresponding for other fields；
Described n degree incidence relation computing module is according to identical letter in not identical degree associated data group
Interest statement unit expands the n degree associated data of target information, and described n degree associated data is stored in
In data memory module, wherein n ＞ 1.
What present system achieved the N degree incidence relation of target information automatically analyzes wherein N
>=1, the degree of depth for data message is excavated and application provides the very reliable instrument easily of one,
For target background analysis, marketing, the market segments, risk profile and prevention and control etc. provide one
Plant novel effective way.
Concrete, present system uses following methods to realize automatically analyzing of target association relation
Described method comprises the step that realizes as shown in Figure 2 and Figure 3:
(1) correspondence is extracted according in the field pieces of data from initial data arranged
Information, forms corresponding basic data；
(2) in a basic data, the first information and the second information are comprised, wherein the second letter
Breath is the once related information of the first information；The second information and is comprised in the second basic data
Three information, wherein said 3rd information is the once related information of described second information；By described
3rd Information expansion becomes two degree of related informations of the described first information；
(3) as comprised the 4th information and the 3rd information in the 3rd basic data, wherein the 4th
Information is the once related information of the 3rd information, by two degree that the 4th Information expansion is the first information
Related information；
The like, expand the n degree related information with the first information as starting point and correspondence
Associated path, wherein n ＞ 1.
The wherein said first information, the second information, the 3rd information and the 4th information refer to information
Content, the not order of representative information.(can be risen with target information as starting point by the inventive method
The selection of point is arranged according to analyzing needs), expand other letters being associated with target step by step
Breath and corresponding associated path, by associated path can be apparent from demonstrate analysis target with
The approach that specifically associates between related information.
Preferred as one, described system uses the collection gang fight of the big data processing shelf of Hadoop
Structure.Described system associates computing module by once associating computing module with n degree by host node
After task automatic segmentation, distribution and parallel processing in each node of cluster internal, and will process
Result is stored in described data memory module after integrating.
The calculating of incidence relation of the present invention realizes with the big data processing shelf of cloud computing platform,
Can process to the target parallel of magnanimity simultaneously, say, that from basic data to N degree
The calculating of related information, is all multiple target the most also column processing.Can be seen that along with the degree of association
The increase step by step of N, complexity and the data dimension of calculating are continuously increased, and the most complicated number
The big data processing shelf of cloud computing platform is passed through (under such as Hadoop according to processing procedure
The big data processing shelf such as MapReduce and Spark) it is able to the most quickly realize；
MapReduce and Spark etc. are big, and data processing shelf can make user have only to according to calculation block
The Interface design upper strata instruction that frame provides, in the case of being indifferent to bottom running, processes
Framework calls the related resource of inside automatically according to upper strata instruction, and by task automatic segmentation,
The different nodes being assigned to inside process, it is achieved that the parallel of data efficiently calculates, at place
The most automatically it is supplied to user after result being integrated after having managed；Tasks make progress height is certainly
Dynamicization, is greatly saved manpower, improves the treatment effeciency of data.
Further, described data memory module is HDFS.HDFS is as under Hadoop
The distributed file system in face, has Error Tolerance, is suitable for being deployed on cheap machine,
Run and maintenance cost is relatively low.HDFS is highly suitable for large-scale dataset simultaneously；Use
HDFS stores pending data can meet mass data storage, the needs of high fault tolerance,
And for using other processing modes of Hadoop to provide convenience.
Further, described system also includes client, described client and described host node phase
Even.The described computing module that once associating is associated computing module with described n degree by described client
Task loads in described host node.
Further, N degree associated data is extracted by described client by described host node
Come.In big data processing shelf, general host node and child node are server, service utensil
There are the advantages such as stable performance, disposal ability are strong, reliable, safe, expansible, can manage.But
It is the expensive of server, needs the maintenance of specialty；The maintenance of general server is with server
The mode of trustship is carried out；The method of operation of server is accessed by client, can be effective
Task exploitation is separated with tasks carrying, the operational efficiency of safeguards system, can carry out remote simultaneously
The operation of journey, is not limited the use space length of the system of extending by distance.
Further, described system also includes HBase data base, and described HBase data are used
In storage N degree associated data.Computing module and the pass online of n degree was once being associated through described
Calculating the N degree associated data after resume module has been structurized data, by these structurings
Data be stored in the HBase data base of relationship type and can more preferably and faster be read out.
Further, described system also includes that initial data acquisition module, described initial data obtain
Delivery block obtains web data by reptile, and the web data got is stored in HDFS
In.The source of described initial data can be the data crawled as required from interconnection, interconnection
In comprise extensively abundant information source, from the Internet, crawl relevant information as required, and
The information of acquisition is carried out advanced treating, and process of refinement and good application for information provide one
Plant brand-new approach.
Embodiment 1
The present embodiment uses system connected mode as shown in Figure 4, and (framework of Hadoop, can
Use MapReduce or Spark Computational frame), by client, enforcement was once associated
Computing module associates the program of computing module and loads in host node server with n degree, at big number
According to processing under framework, described host node is assigned to each from node serve by after task automatic segmentation
On device perform, original data storage in HDFS distributed file system, the main joint of HDFS
The host node that point calculates with incidence relation is identical, HDFS from the calculating of node and incidence relation
Identical from node, same node runs different processes and realizes different functions.
The Computing Principle of incidence relation is as follows: assume (to set through field in initial data
The field put includes: the first field, the second field, the 3rd field and the 4th field) extract,
The data extracted comprise 3 basic datas as shown in Figure 5, wherein first foundation
The letter corresponding to the first field, the second field, the 3rd field and the 4th field that packet contains
Breath content is followed successively by: A, B, D, E；The first field of comprising in Article 2 basic data,
Second field, the 3rd field and the information content corresponding to the 4th field are followed successively by: C, B,
F and G；The first field of comprising in Article 3 information, the second field, the 3rd field and
Information content corresponding to 4th field is followed successively by: H, F, I, J.Assume the first field
Corresponding content is as the starting point of association analysis, then first foundation data can be formed: A-B, A-D,
The once incidence relation of A-E, wherein B, D, E are the once related information of A, simultaneously
A is also the once related information of B, D, E；Second basic data can be formed C-B, C-F,
The once incidence relation of C-G, wherein B, F, G are the once related information of C, simultaneously
C is also the once related information of B, F, G；3rd basic data can be formed: H-F, H-I,
The once incidence relation of H-J, wherein F, I, J are the once related information of H, and H is also simultaneously
For the once related information of F, I, J, structurized two row as described in Figure 6.
Above-mentioned once associate on the basis of, according in the once incidence relation of A-B and C-B
Identical information unit B, is extended to two degree of related informations of A by C, with A as starting point,
Form the associated path of A-B-C.According to identical in the once incidence relation of C-B with A-B
Information unit B, is extended to two degree of related informations of C by A, with C as starting point, forms C-B-A
Associated path.According to information unit F identical in the once incidence relation of C-F with H-F,
H is extended to two degree of related informations of C；With C as starting point, form the association road of C-F-H
Footpath.According to information unit F identical in the once incidence relation of H-F with C-F, C is extended
Become two degree of related informations of H；With H as starting point, form the associated path of H-F-C.Formed
The associated data storage of two degree of incidence relations can use depositing as shown in Figure 7 with tables of data form
Storage structure.
Further, in above-mentioned two degree of associations and once on the basis of incidence relation, with A
For starting point according to the once related information of two degree of related information C of A, expansible go out A-B-C-F,
The associated path of A-B-C-G, wherein F and G is three degree of related informations of A.With C for rising
Point, according to the once related information of two degree of related information A and H of C, expansible go out,
C-B-A-E, C-B-A-D, C-F-H-I, the associated path of C-F-H-J, wherein D, E I, J
Three degree of related informations for C.Same with H as starting point, according to its two degree of related information C's
Once related information, can form the associated path of H-F-C-B, H-F-C-G, wherein B and G
Three degree of related informations for H.The data table memory of three degree of related informations is as shown in Figure 8.Value
Obtain it is to be noted that need to remove closed path, in terms of this is avoided during related information calculates
Error loop in calculation.
The calculating process of the explanation related information of being diagrammatically only by property of the present embodiment, indeed according to needs
Number of targets to be analyzed can reach ten thousand, 100,000, million magnitudes；And from above-described embodiment
It can be seen that along with the increase of the association number of degrees, the data volume of required calculating sharply increases, magnanimity
The amount of calculation of multidimensional related information of calculating target huger, and the present invention uses cloud computing
The big data processing shelf of platform, can be carried out magnanimity target parallel according to said method
Calculate, and then achieve incidence relation analysis and the excavation of magnanimity target information.
Although detailed description of the invention illustrative to the present invention is described above, in order to this
Technology neck artisans understand that the present invention, it should be apparent that the invention is not restricted to be embodied as
The scope of mode, from the point of view of those skilled in the art, as long as various change is in institute
Attached claim limits and in the spirit and scope of the present invention that determine, during these changes aobvious and
Being clear to, all utilize the innovation and creation of present inventive concept all at the row of protection.
Claims (9)
1. a magnanimity associated data processing system, it is characterised in that include that data store mould
Block, once associate computing module and n degree association computing module, wherein said once close online
Calculation associates computing module with n degree and is connected with data memory module respectively；
The described computing module that once associating is according to original from data memory module of field arranged
Extracting data goes out basic data, chooses content corresponding to one of them field in basic data and makees
For target information, it is target information once associated data by Information expansion corresponding for other fields；
Described n degree incidence relation computing module is according to identical letter in not identical degree associated data group
Interest statement unit expands the n degree associated data of target information, and described n degree associated data is stored in
In data memory module, wherein n ＞ 1.
2. the system as claimed in claim 1, it is characterised in that: described system uses Hadoop
The aggregated structure of big data processing shelf.
3. system as claimed in claim 2, it is characterised in that: described system passes through main joint
After point will once associate computing module and associate with n degree the task automatic segmentation of computing module, distribute
Parallel processing in each node of cluster internal.
4. system as claimed in claim 2 or claim 3, it is characterised in that: described data store
Module is HDFS.
5. system as claimed in claim 4, it is characterised in that: described system also includes visitor
Family end, described client is connected with described host node.
6. system as claimed in claim 5, it is characterised in that: described client is by described
Once associate the task that computing module associates computing module with described n degree and load on described main joint
In point.
7. system as claimed in claim 6, it is characterised in that: described client passes through institute
State host node N degree associated data to be extracted.
8. system as claimed in claim 7, it is characterised in that: also include HBase data
Storehouse, described HBase data base is used for storing N degree associated data.
9. system as claimed in claim 8, it is characterised in that: also include that initial data obtains
Delivery block, described initial data acquisition module obtains web data by reptile, and will get
Web data be stored in HDFS.
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Application publication date: 20160921 |