CN105302885A - Full-text data extraction method and device - Google Patents
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- CN105302885A CN105302885A CN201510671050.7A CN201510671050A CN105302885A CN 105302885 A CN105302885 A CN 105302885A CN 201510671050 A CN201510671050 A CN 201510671050A CN 105302885 A CN105302885 A CN 105302885A
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- 238000013075 data extraction Methods 0.000 title claims abstract description 33
- 238000000605 extraction Methods 0.000 claims abstract description 41
- 238000002372 labelling Methods 0.000 claims abstract description 4
- 238000007405 data analysis Methods 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 4
- 230000006870 function Effects 0.000 description 16
- 239000000284 extract Substances 0.000 description 12
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- G06F16/90—Details of database functions independent of the retrieved data types
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Abstract
The invention discloses a full-text data extraction method and device. The method comprises the following steps: analyzing network packet data into session data; judging whether the entity part of the session data accords with a preset data format or not, and carrying out data format labelling on the session data if the entity part of the session data accords with the preset data format; carrying out multimode matching on the session data which accords with the preset data format, judging whether a preset characteristic string is hit or not and obtaining the hitting position of the preset characteristic string when the preset characteristic string is hit; and determining an extraction function corresponding to the session data according to the data format label of the session data and the hitting position of the preset characteristic string, and carrying out data extraction on the session data according to the extraction function. According to the full-text data extraction method and device, the technical effect of improving the full-text data extraction efficiency of mass data is realized.
Description
Technical field
The embodiment of the present invention relates to mobile and large technical field of data processing, particularly relates to a kind of extracting method and device of full-text data.
Background technology
The high speed development of internet, makes data penetrate into each industry and operation function field, becomes the important factor of production gradually, and incident is that the mankind can the mass data for the treatment of and analysis.In medium-sized or above city as Beijing, Shanghai, the Various types of data produced in network behavior every day is more than PB level.Such as application program of mobile phone (Application, APP) the submission data having several TB every day produce, containing the information such as longitude and latitude, mobile phone string number, subscriber identification card card number, mobile phone unique identifier in these data, and these information are very useful in security control industry, therefore magnanimity extracts these information becomes an important and job for complexity.
Traditional full text extracting method mainly contains two kinds: a kind of is extracting method based on template, and this method is applicable to the information extraction of specific website, but for the data that changeable mobile phone A PP and different web sites produce, seems helpless; Another kind extracts entire contents based on regular expression, and that this method is applicable to off-line, that data volume is less full text extracts, once submit data in the face of the APP of magnanimity, efficiency comparison is low.Therefore these two kinds of methods are in big data quantity situation, and meeting at substantial manpower, and inefficiency, can not satisfy the demand in big data quantity situation.
Summary of the invention
The invention provides a kind of extracting method and device of full-text data, to realize the full-text data extraction efficiency improving mass data.
First aspect, embodiments provides a kind of extracting method of full-text data, comprising:
Be session data by network package Data Analysis;
Judge whether the entity part of described session data meets preset data form, if then carry out data layout mark to described session data;
Multimode matching is carried out to the session data meeting preset data form, judges whether to hit default feature string, and obtain when hitting and presetting feature string the hit location presetting feature string;
According to the data layout mark of described session data and the hit location of described default feature string, determine the extraction function of the correspondence of described session data, and according to described extraction function, data extraction is carried out to described session data.
Second aspect, the embodiment of the present invention additionally provides a kind of extraction element of full-text data, comprising:
Parsing module, for being session data by network package Data Analysis;
Labeling module, for judging whether the entity part of described session data meets preset data form, if then carry out data layout mark to described session data;
Multimode matching module, for carrying out multimode matching to the session data meeting preset data form, judges whether to hit default feature string, and obtains when hitting and presetting feature string the hit location presetting feature string;
Data extraction module, for according to the data layout mark of described session data and the hit location of described default feature string, determines the extraction function of the correspondence of described session data, and carries out data extraction according to described extraction function to described session data.
The present invention is by carrying out the judgement of preset data form to the session data after parsing, the invalid data filtering of preset data form can not met, therefore data extraction time is shortened, in addition, by carrying out multimode matching to the session data meeting preset data form, further reduce to extract and search match time in data procedures, improve the full-text data extraction efficiency of mass data.
Accompanying drawing explanation
The schematic flow sheet of the extracting method of a kind of full-text data that Fig. 1 provides for the embodiment of the present invention one;
The schematic flow sheet of the extracting method of a kind of full-text data that Fig. 2 provides for the embodiment of the present invention two;
The extraction element of a kind of full-text data that Fig. 3 provides for the embodiment of the present invention three;
Fig. 4 is the topological structure schematic diagram of the full-text data extraction that the embodiment of the present invention three provides.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail.Be understandable that, specific embodiment described herein is only for explaining the present invention, but not limitation of the invention.It also should be noted that, for convenience of description, illustrate only part related to the present invention in accompanying drawing but not entire infrastructure.
Embodiment one
The schematic flow sheet of the extracting method of a kind of full-text data that Fig. 1 provides for the embodiment of the present invention one, the method can be performed by the extraction element of full-text data, this device can be realized by the mode of hardware and/or software, and concrete described method comprises following operation:
S110, be session data by network package Data Analysis.
The data that the method that the present embodiment provides is applicable to various protocols communication are extracted, and are described in detail below with HTML (Hypertext Markup Language) (HyperTextTransferProtocol, HTTP) data instance.First be the session data of text formatting by the network package Data Analysis obtained from data source.For http data, http protocol stack is adopted to resolve to HTTPPOST session data.Session data after parsing comprises HTTP head and HTTP entity part.Resolve according to http protocol stack and be reduced into HTTPPOST session data, need first to build transmission control protocol (TransmissionControlProtocol, TCP) flow, and then resolve by http session, such as, utilize open source software snort to realize this kind of function.
S120, judge whether the entity part of described session data meets preset data form, if then carry out data layout mark to described session data.
Be, after session data, the entity part of described session data is identified network package Data Analysis, judge whether the entity part of described session data meets preset data form.Described preset data form can personal settings as required.Generally, select preset data form as required, need the data extracted generally only to be included in preset data form, this operation, can not meet the session data filtering of preset data form.Therefore can avoid extracting invalid data, save data extraction time.When the entity part of described session data meets preset data form, data layout mark is carried out to described session data, belong to which kind of preset data form to identify described session data.
S130, multimode matching is carried out to the session data meeting preset data form, judge whether to hit default feature string, and obtain when hitting and presetting feature string the hit location presetting feature string.
Wherein preset feature string and can pass through configuration file management, the quantity of described default feature string is greater than or equal to 1.Described default feature string can be such as " phonenumber " (telephone number), " MAC " (hardware address) and " mac " etc.Optionally, multimode matching is being carried out to the session data meeting preset data form, judge whether to hit default feature string, and before obtaining when hitting and presetting feature string the hit location presetting feature string, also comprise: by presetting feature string described in configuration file management.Preset feature string by configuration file management, can add flexibly, delete, multimode matching algorithm used in the present invention can be such as AC algorithm, can also use other algorithms of increasing income.
Obtain default feature string by reading configuration file, then carry out the generation of multimode matching algorithm state tree, thus finally realize follow-up multimode matching operation.
S140, hit location according to the data layout of described session data mark and described default feature string, determine the extraction function of the correspondence of described session data, and carry out data extraction according to described extraction function to described session data.
The present invention is directed to different data format to extract and extract function one to one.According to the data layout mark of described session data and the hit location of described default feature string, determine the extraction function of the correspondence of described session data, the extraction function then utilizing described session data corresponding carries out data extraction.
The embodiment of the present invention is by carrying out the judgement of preset data form to the session data after parsing, the invalid data filtering of preset data form can not met, therefore data extraction time is shortened, in addition, by carrying out multimode matching to the session data meeting preset data form, further reduce to extract and search match time in data procedures, improve the full-text data extraction efficiency of mass data.The data extraction method that the embodiment of the present invention provides not only is applicable to specific website, the data of off-line are extracted, the data being more suitable for not appointed website, large discharge are extracted, single processing threads is per second can process nearly 10000 effective http sessions, reaches the object that magnanimity extracts full-text data.
Embodiment two
The schematic flow sheet of the extracting method of a kind of full-text data that Fig. 2 provides for the embodiment of the present invention two, as shown in Figure 2, described method comprises:
S210, be session data by network package Data Analysis.
S220, judge whether the entity part of described session data meets preset data form.
If so, then executable operations S230 and S250 successively, otherwise return executable operations S240 and S220 successively.
S230, data layout mark is carried out to described session data.
S240, subsequent network packet data is resolved to session data.
S250, multimode matching is carried out to the session data meeting preset data form, judge whether to hit default feature string.
When hitting default feature string, executable operations S260, S270, S280 and S290 successively, otherwise return executable operations S240 and S220 successively.
The hit location of S260, the default feature string of acquisition, and field label corresponding to feature string is preset in hit.
Wherein, preset feature string by configuration file management, concrete, configuration file format can by setting as follows:
Feature string field label
ImsiIMSI
Phone_imsiIMSI
Feature string " Imsi " and " Phone_imsi " have same field label " IMSI ".Wherein IMSI represents international mobile subscriber identity.
S270, hit location according to the data layout of described session data mark and described default feature string, determine the extraction function of the correspondence of described session data, and carry out data extraction according to described extraction function to described session data.
S280, the field label corresponding according to the default feature string of hit, be normalized the data after extracting.
During the same field label of different characteristic string correspondence, the data extracted are same class.Such as the field label of feature string " MAC " and " mac " is MAC.Namely the data extracted by feature string " MAC " and " mac " all characterize hardware address.And be different by the data layout that feature string " MAC " and " mac " extract.Described normalization refers to and the different-format of same data is converted into same form, such as: mac address has in the data: aa-bb-cc-dd-ee-ff, aa=bb=cc=dd=ee=ff, aa:bb:cc:dd:ee:ff.After normalized, uniform format is: aa-bb-cc-dd-ee-ff.
S290, extraction data are carried out structuring process and exports.
Concrete, by setting specified format, the data extracted by aforesaid operations are combined into structural data by specified format, and export, to use.
The embodiment of the present invention is by becoming session data by network package Data Analysis, then the form of session data entity is judged, mark simultaneously, if not preset data form, then carry out the extraction flow process of next network package data, if, then then multimode matching is carried out to session data, and the position of backout feature string, according to the position of feature string, the form of session data, call corresponding extraction function, one by one data are extracted, decreased in data extraction procedure by multimode matching and search match time, by the judgement of preset data form, avoid the extraction to invalid data, therefore the extraction of mass data is applicable to, and data extraction efficiency is high.
On the basis of above-described embodiment, optionally, described preset format comprises: at least one in Key-Value formula, Mutipart form, json form and xml form.
Wherein, the sample of Key-Value formula, Mutipart form, json form and xml form is as follows:
Key-Value formula: name=test1 & password=test2 & mac=aa-bb-cc-dd-ee-ff
Mutipart form:
------------7dc120151b0954
Content-Disposition:form-data；name＝"mac"
aa-bb-cc-dd-ee-ff
Json form:
{"name":"test1","passwd":"test2","mac":"aa:bb:cc:dd:ee:ff"}
Xml form: <? xmlversion=" 1.0 " encoding=" UTF-8 "? ><root>
<name>test1</name><mac>aa-bb-cc-dd-ee-ff</mac></root>
Embodiment three
The extraction element of a kind of full-text data that Fig. 3 provides for the embodiment of the present invention three, as shown in Figure 3, described device comprises:
Parsing module 31, for being session data by network package Data Analysis;
Labeling module 32, for judging whether the entity part of described session data meets preset data form, if then carry out data layout mark to described session data;
Multimode matching module 33, for carrying out multimode matching to the session data meeting preset data form, judges whether to hit default feature string, and obtains when hitting and presetting feature string the hit location presetting feature string;
Data extraction module 34, for according to the data layout mark of described session data and the hit location of described default feature string, determines the extraction function of the correspondence of described session data, and carries out data extraction according to described extraction function to described session data.
The embodiment of the present invention is by carrying out the judgement of preset data form to the session data after parsing, the invalid data filtering of preset data form can not met, therefore data extraction time is shortened, in addition, by carrying out multimode matching to the session data meeting preset data form, further reduce to extract and search match time in data procedures, improve the full-text data extraction efficiency of mass data.The data extraction method that the embodiment of the present invention provides not only is applicable to specific website, the data of off-line are extracted, and the data being more suitable for not appointed website, large discharge are extracted, and reaches the object that magnanimity extracts full-text data.
On the basis of above-described embodiment, optionally, described multimode matching module, also presets field label corresponding to feature string for obtaining hit when hitting and presetting feature string.
Described device also comprises: normalized module, for presetting field label corresponding to feature string according to hit, is normalized the data after extracting.
On the basis of above-described embodiment, optionally, described device also comprises: structuring processing module, for extraction data being carried out structuring process and exporting.
On the basis of above-described embodiment, optionally, described preset format comprises: at least one in Key-Value formula, Mutipart form, json form and xml form.
On the basis of above-described embodiment, optionally, described device also comprises: preset feature string administration module, presets feature string for passing through described in configuration file management.
The said goods can perform the method that any embodiment of the present invention provides, and possesses the corresponding functional module of manner of execution and beneficial effect.
The topological structure schematic diagram that the full-text data that Fig. 4 provides for the embodiment of the present invention extracts.As shown in Figure 4, whole system need to be used for extracting in full server, converge shunting device, multiple mutual routing device at least one database server, backbone network.Multiple mutual routing device wherein in backbone network is data source, provides raw data.The data that data source produces are by converging shunting device mirror image, and then mirror image data is exported to and extracted server in full by convergence shunting device.Extract the extraction element that server comprises the full-text data described in above-described embodiment in full, and carry out data extraction by the extracting method of the full-text data described in the various embodiments described above.
Implementation process needs following steps:
(1), raw data shunting
Utilize convergence shunting device to carry out data distribution on router link, need up, the whole mirror image of downlink traffic, to ensure the complete of a session data.
(2), extract server in full to build
Extract the preferred multinuclear of server, large inner server in full, utilize multi-core parallel concurrent process, improve handling property, extract on server at full text and install extraction procedure in full, installation data carries program simultaneously, also can carry with the FTP service of routine.
(3), database server is built
Build database server according to data scale, if data scale is little, can mysql be used, oracle; If data volume is comparatively large, then need to build distributed memory system, as Hadoop.
(4) extraction procedure in full, is started
Start extraction procedure in full, extraction procedure carries out data extraction according to the extracting method of the full-text data described in the various embodiments described above in full, and the data after extracting are outputted in data center in corresponding database server, use for follow-up different operation system.
In addition, extracting flow to increase data, suitably can increase the quantity extracting server in full.
Note, above are only preferred embodiment of the present invention and institute's application technology principle.Skilled person in the art will appreciate that and the invention is not restricted to specific embodiment described here, various obvious change can be carried out for a person skilled in the art, readjust and substitute and can not protection scope of the present invention be departed from.Therefore, although be described in further detail invention has been by above embodiment, the present invention is not limited only to above embodiment, when not departing from the present invention's design, can also comprise other Equivalent embodiments more, and scope of the present invention is determined by appended right.
Claims (10)
1. an extracting method for full-text data, is characterized in that, comprising:
Be session data by network package Data Analysis;
Judge whether the entity part of described session data meets preset data form, if then carry out data layout mark to described session data;
Multimode matching is carried out to the session data meeting preset data form, judges whether to hit default feature string, and obtain when hitting and presetting feature string the hit location presetting feature string;
According to the data layout mark of described session data and the hit location of described default feature string, determine the extraction function of the correspondence of described session data, and according to described extraction function, data extraction is carried out to described session data.
2. method according to claim 1, it is characterized in that, multimode matching is being carried out to the session data meeting preset data form, is judging whether to hit default feature string, and when obtaining when hitting and presetting feature string the hit location presetting feature string, also comprise:
Obtain hit when hitting and presetting feature string and preset field label corresponding to feature string;
In the hit location of the described data layout according to described session data mark and described default feature string, determine the extraction function of the correspondence of described session data, and after according to described extraction function data extraction being carried out to described session data, also comprise:
Preset field label corresponding to feature string according to hit, the data after extracting are normalized.
3. method according to claim 1, it is characterized in that, in the hit location according to the data layout of described session data mark and described default feature string, determine the extraction function of the correspondence of described session data, and after according to described extraction function data extraction being carried out to described session data, also comprise:
Extraction data are carried out structuring process and exports.
4. method according to claim 1, is characterized in that, described preset format comprises: at least one in Key-Value formula, Mutipart form, json form and xml form.
5. method according to claim 1, it is characterized in that, multimode matching is being carried out to the session data meeting preset data form, is judging whether to hit default feature string, and before obtaining when hitting and presetting feature string the hit location presetting feature string, also comprise:
By presetting feature string described in configuration file management.
6. an extraction element for full-text data, is characterized in that, comprising:
Parsing module, for being session data by network package Data Analysis;
Labeling module, for judging whether the entity part of described session data meets preset data form, if then carry out data layout mark to described session data;
Multimode matching module, for carrying out multimode matching to the session data meeting preset data form, judges whether to hit default feature string, and obtains when hitting and presetting feature string the hit location presetting feature string;
Data extraction module, for according to the data layout mark of described session data and the hit location of described default feature string, determines the extraction function of the correspondence of described session data, and carries out data extraction according to described extraction function to described session data.
7. device according to claim 6, is characterized in that, described multimode matching module also presets field label corresponding to feature string for obtaining hit when hitting and presetting feature string;
Described device also comprises: normalized module, for presetting field label corresponding to feature string according to hit, is normalized the data after extracting.
8. device according to claim 6, is characterized in that, also comprises:
Structuring processing module, for carrying out structuring process by extraction data and exporting.
9. device according to claim 6, is characterized in that, described preset format comprises: at least one in Key-Value formula, Mutipart form, json form and xml form.
10. device according to claim 6, is characterized in that, also comprises:
Presetting feature string administration module, presetting feature string for passing through described in configuration file management.
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| CN105868311A (en) * | 2016-03-25 | 2016-08-17 | 浪潮通信信息系统有限公司 | Data analyzing method and device |
| CN106033298A (en) * | 2016-05-03 | 2016-10-19 | 海致网络技术（北京）有限公司 | Data extracting method and system |
| CN106547915A (en) * | 2016-11-29 | 2017-03-29 | 上海轻维软件有限公司 | Intelligent data extracting method based on model library |
| CN106776794A (en) * | 2016-11-23 | 2017-05-31 | 北京锐安科技有限公司 | A kind of method and system for processing mass data |
| CN109905372A (en) * | 2019-01-24 | 2019-06-18 | 李惠英 | Transmission system Data Transport Protocol identifying and analyzing method |
| CN109981563A (en) * | 2019-01-23 | 2019-07-05 | 国家新闻出版广电总局广播电视规划院 | A kind of automatic intelligent method for digging of radio and television key message infrastructure network security breaches |
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| CN105868311A (en) * | 2016-03-25 | 2016-08-17 | 浪潮通信信息系统有限公司 | Data analyzing method and device |
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|---|---|
| CN105302885B (en) | 2019-12-06 |
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