CN109376152A - Big data system file data preparation method and system - Google Patents
Big data system file data preparation method and system Download PDFInfo
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Abstract
The present invention relates to a kind of big data system file data preparation method and system, computer equipment, computer storage mediums.The above method includes: the reading unit field from the data file of importing, and elements field is directed respectively into the field contents region of each field name, determines all kinds of fields and the tables of data including all kinds of fields；Determine that the first kind selectes field in tables of data, the identification first kind selectes the repetitive unit field in field, determines the repetition row in tables of data according to repetitive unit field, deletes each row repeated in row in addition to the first row；Determine that the second class selectes field in tables of data, the second class of identification selectes the null field in field, rejects correspondence row of the null field in tables of data；The completely ineffective row for identifying tables of data, has been calculated according to total line number of the line number of completely ineffective row and tables of data completely without effect ratio, determines the data preparation content before data analysis according to the completely ineffective ratio and the tables of data.
Description
Technical field
The present invention relates to technical field of information processing, more particularly to a kind of big data system file data preparation method and
System, computer equipment, computer storage medium.
Background technique
With the development of digital times, big data has become " the rigid estovers " of enterprise.Currently, big data industry is major
Urban development obtains very swift and violent, and a large amount of clothes, food and drink, amusement, the consumption traditional industries such as category are faced with severe transition liter
Grade test, therefore with greater need for the business decision with assistance enterprise progress rationality passed through to data.
In view of each business data field type and field number would generally difference, and these data are often deposited
Vacancy, repetition, it is invalid the problems such as, if to these data be not prepared processing and directly in related datas such as marketing platforms
Processing platform analysis can make the analysis result inaccuracy obtained, influence corporate decision maker and formulate big data marketing strategy, sometimes
Very severe consequence can even be brought.Therefore, in order to improve the accuracy rate that data processing platform (DPP) analyzes corresponding data,
The preparations such as need to be standardized data, clean and extend, above-mentioned data is made to become the number of structuring, rule
According to the result analyzed with this could improve corporate decision's enabling capabilities, be allowed to play due effect.And traditional data
The Data Preparations such as standardization, cleaning and/or extension usually require professional to be carried out by speciality platform, is easy to make in this way
Data preparation it is at high cost.
Summary of the invention
Based on this, it is necessary to be easy the technical problem for keeping data preparation at high cost for traditional scheme, provide a kind of big number
According to system file data preparation method and system, computer equipment, computer storage medium.
A kind of big data system file data preparation method, comprising:
The reading unit field from the data file of importing, elements field is directed respectively into the field of each field name
Hold region, determines the corresponding all kinds of fields of each field name and the tables of data including all kinds of fields；
It determines that the first kind selectes field in the tables of data, identifies that the first kind selectes the repetitive unit word in field
Section determines the repetition row in tables of data according to repetitive unit field, deletes each row repeated in row in addition to the first row；Its
In, it is to repeat elements field to belong to illegal a kind of field that the first kind, which selectes field,；
It determines that the second class selectes field in the tables of data, identifies that second class selectes the null field in field, pick
Except correspondence row of the null field in tables of data；
The completely ineffective row for identifying the tables of data, according to the line number of the completely ineffective row and total line number of tables of data
Completely ineffective ratio is calculated, is determined according to the completely ineffective ratio and the tables of data in the data preparation before data analysis
Hold；Wherein, the illegal row of the elements field of the selected field of third class in the completely ineffective behavioral data table.
Above-mentioned big data system file data preparation method, can from the data file of importing reading unit field, will
Elements field is directed respectively into the field contents region of each field name, with the corresponding all kinds of words of each field name of determination
Section and the tables of data including all kinds of fields determine that the first kind selectes field in the tables of data, to identify in tables of data
It repeats to go, deletes the above-mentioned each row repeated in row in addition to the first row, and determine that the second class selectes field in above-mentioned tables of data,
To identify that second class selectes the null field in field, correspondence row of the null field in tables of data is rejected, can also be known
Completely ineffective row in other tables of data, calculates completely ineffective ratio, determines the data preparation content before data analysis with this, can be with
Data Preparation before simplifying data analysis, reduces data preparation cost.
In one embodiment, the completely ineffective row of the identification tables of data, according to the row of the completely ineffective row
After the process completely without effect ratio has been calculated in several and tables of data total line number, can also include:
Field is selected according to the 4th class and determines extension title, reads institute from the elements field in the setting type field
State the corresponding extension content of extension title；Wherein, it is that can continue to expand other types field that the 4th class, which selectes field,
Field.
The field type that the present embodiment can make tables of data be included is more fully.
As one embodiment, the completely ineffective row of the identification tables of data, according to the row of the completely ineffective row
Several and tables of data total line number has been calculated after the process completely without effect ratio, further includes:
Effective field line number in identification extension content, total line number according to the effective field line number and extension content are true
Surely success rate is extended.
The present embodiment can illustrate validation checking rule (such as identification word of table or setting by related validation checking
Number, format and/or field logic) etc. modes identify the effective field in extension content, count the line number of above-mentioned effective field, with
It determines extension success rate, further improves the content of tables of data, keep Data Preparation more abundant.
In one embodiment, reading unit field in the data file from importing, elements field is directed respectively into
The field contents region of each field name determines the corresponding all kinds of fields of each field name and including all kinds of fields
Tables of data process before, further includes:
The data file that user uploads is imported, identifies the format of the data file；
If the format of the data file is the first setting format, the reading unit field from the data file of importing.
Present embodiment ensure that the importing efficiency of elements field.
As one embodiment, the data file for importing user and uploading identifies the mistake of the format of the data file
After journey, further includes:
If the format of the data file is the second setting format, use separator by the file in the data file
Content is divided into multiple elements fields.
File content in the data file is divided into multiple elements fields, Ke Yibao using separator by the present embodiment
Demonstrate,prove the subsequent accuracy for carrying out elements field importing.
It, will using separator if the format of the data file is the second setting format as one embodiment
File content in the data file is divided into after the process of multiple elements fields, further includes:
Identify whether the format of the data file and the elements field that the data file includes are legal respectively, if
It is, then the reading unit field from the data file of importing.
The present embodiment can guarantee the fairness in elements field reading process.
As one embodiment, the data file for importing user and uploading identifies the mistake of the format of the data file
Before journey, further includes:
Whether the data file that identification user uploads is the first setting format or the second setting format, if it is not, then showing
Warning prompt frame；Wherein, the warning prompt frame is the dialog box for prompting subscriber data file format illegal.
The present embodiment can guarantee the validity for the data file that user uploads, and help to improve subsequent reading elements field
Fairness.
A kind of big data system file data preparation system, comprising:
Elements field is directed respectively into each word for the reading unit field from the data file of importing by read module
The field contents region of name section determines the corresponding all kinds of fields of each field name and the data including all kinds of fields
Table；
First determining module identifies that the first kind is selected for determining that the first kind selectes field in the tables of data
Repetitive unit field in field determines the repetition row in tables of data according to repetitive unit field, deletes and removes in the repetition row
Each row except the first row；Wherein, it is to repeat elements field to belong to illegal a kind of field that the first kind, which selectes field,；
Second determining module identifies that second class is selected for determining that the second class selectes field in the tables of data
Null field in field rejects correspondence row of the null field in tables of data；
First identification module, the completely ineffective row of the tables of data for identification, according to the line number of the completely ineffective row
And total line number of tables of data has been calculated completely without effect ratio, determines data according to the completely ineffective ratio and the tables of data
Data preparation content before analysis；Wherein, the elements field of the selected field of third class is equal in the completely ineffective behavioral data table
Illegal row.
Above-mentioned big data system file data preparation system, can from the data file of importing reading unit field, will
Elements field is directed respectively into the field contents region of each field name, with the corresponding all kinds of words of each field name of determination
Section and the tables of data including all kinds of fields determine that the first kind selectes field in the tables of data, to identify in tables of data
It repeats to go, deletes the above-mentioned each row repeated in row in addition to the first row, and determine that the second class selectes field in above-mentioned tables of data,
To identify that second class selectes the null field in field, correspondence row of the null field in tables of data is rejected, can also be known
Completely ineffective row in other tables of data, calculates completely ineffective ratio, determines the data preparation content before data analysis with this, can be with
Data Preparation before simplifying data analysis, reduces data preparation cost.
A kind of computer equipment, including memory, processor and be stored on the memory and can be in the processing
The computer program run on device, the processor realize that any of the above-described embodiment provides big when executing the computer program
Data system file data preparation method.
A kind of computer storage medium, is stored thereon with computer program, which is characterized in that the program is executed by processor
The big data system file data preparation method that any of the above-described embodiment of Shi Shixian provides.
Big data system file data preparation method according to the present invention, the present invention also provides a kind of computer equipment and meters
Calculation machine storage medium, for realizing above-mentioned big data system file data preparation method by program.Above-mentioned computer equipment and
Computer storage medium can reduce the cost that data preparation is consumed.
Detailed description of the invention
Fig. 1 is the big data system file data preparation method flow chart of one embodiment；
Fig. 2 is the big data system file data preparation system structural schematic diagram of one embodiment；
Fig. 3 is the computer system module map of one embodiment.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention more comprehensible, with reference to the accompanying drawings and embodiments, to this
Invention is described in further detail.It should be appreciated that the specific embodiments described herein are only used to explain the present invention,
And the scope of protection of the present invention is not limited.
It should be noted that term involved in the embodiment of the present invention " first second third " be only distinguish it is similar
Object does not represent the particular sorted for object, it is possible to understand that ground, " first second third " can be mutual in the case where permission
Change specific sequence or precedence.It should be understood that the object that " first second third " is distinguished in the appropriate case can be mutual
It changes, so that the embodiment of the present invention described herein can be real with the sequence other than those of illustrating or describing herein
It applies.
The term " includes " of the embodiment of the present invention and " having " and their any deformations, it is intended that cover non-exclusive
Include.Such as contain series of steps or module process, method, system, product or equipment be not limited to it is listed
Step or module, but optionally further comprising the step of not listing or module, or optionally further comprising for these processes, side
Method, product or equipment intrinsic other steps or module.
Referenced herein " embodiment " is it is meant that a particular feature, structure, or characteristic described can wrap in conjunction with the embodiments
It is contained at least one embodiment of the application.Each position in the description occur the phrase might not each mean it is identical
Embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art explicitly and
Implicitly understand, embodiment described herein can be combined with other embodiments.
Referenced herein " multiple " refer to two or more."and/or", the association for describing affiliated partner are closed
System indicates may exist three kinds of relationships, for example, A and/or B, can indicate: individualism A exists simultaneously A and B, individualism
These three situations of B.Character "/" typicallys represent the relationship that forward-backward correlation object is a kind of "or".
Refering to what is shown in Fig. 1, Fig. 1 is the big data system file data preparation method flow chart of one embodiment, comprising:
Elements field, is directed respectively into the word of each field name by S10, the reading unit field from the data file of importing
Section content area, determines the corresponding all kinds of fields of each field name and the tables of data including all kinds of fields；
Above-mentioned data file can be imported by the importing dialog box of pop-up, including all kinds of marketing data form documents, such as
The data form file of following 5 seed type:
Member data table: for storing member/client and its Attribute class data；
Commodity register table: for storing merchandise classification and item property data；
Sales figure table: for storing sales figure, this table can splice with other tables to be used；
Channel tables of data: for storing Sales Channel and its attribute data；
Action result table: for storing marketing activity related data, field relates generally to the member participated in and above-mentioned meeting
The situation of member's participation activity.
Above-mentioned data file is big data system file, includes multiclass field, such as member data in Various types of data file
Table includes all kinds of words such as cell-phone number, registration market, registration site, city, identification card number, record date, name, gender, age
Section.All kinds of fields all have corresponding field name, and field name is usually gauge outfit of the respective field where it in tables of data,
Above-mentioned each field name can be dragged to the gauge outfit position in data preview region by user by way of pulling or inputting, really
Field name is determined, so that user can more directly know all kinds of fields.Certain class field may include field name and field contents
(content of field contents regional record), field name can usually characterize field classification, and field contents may include several
Elements field, if cell-phone number can be field name (gauge outfit), each number below cell-phone number can be field contents, one
Number is an elements field, and an elements field generally takes up a line in such field, i.e., in certain class field, field name
It can be the first row, each row in such field after field name can record an elements field respectively.Such as cell-phone number,
It, can be by the corresponding unit of field name after the completion of the field names such as registration market, registration site, city, identification card number determine
Field imports corresponding field contents region, after the completion of elements field imports, if there is also be not imported into for above-mentioned data file
Elements field (i.e. non-selected field), these not imported elements fields may be invalid field, can reject
State invalid field.
During elements field to be directed respectively into the field contents region of each field name, unit word can be carried out
Section judgement judges to set whether class field includes unique field (such as: " identification card number ", " membership number " or " cell-phone number "), if packet
Containing at least one unique field, then it can be determined that all kinds of fields import successfully；Above-mentioned unique field is that can characterize referents
A kind of field of (such as member, commodity or activity).After all kinds of fields import successfully, imported field classification can also be counted
Sum uploads successful field classification number, does not upload field classification number and total amount of data, and passing through the prompt of the forms such as dialog box
Above-mentioned statistical result；If not including any one unique field in the data file imported, it can show importing dialog box, make
User uploads data file again.
S20 determines that the first kind selectes field in the tables of data, identifies that the first kind selectes the repetition list in field
First field determines the repetition row in tables of data according to repetitive unit field, deletes each in addition to the first row in the repetition row
Row；Wherein, it is to repeat elements field to belong to illegal a kind of field that the first kind, which selectes field,；
The above-mentioned first kind is selected in field, and elements field does not repeat to be legal, if the elements field duplicated mutually
It is illegal, such as ID card No., membership number field；If duplicating field in these fields, show Repeating Field in number
Repeat to go according to behavior where in table, thus the first kind is selected in field, repetitive unit field be it is illegal, can be by this kind of words
The analysis of Duan Jinhang repetition values, identifies repetitive unit field therein, determines the corresponding repetition in tables of data of repetitive unit field
Row deletes each row repeated in row in addition to the first row, to guarantee the validity of tables of data recorded contents,
Specifically, the first kind that can read user's selection selectes field, carries out repetition values analysis to all kinds of fields, i.e., will
All field names in tables of data gauge outfit, which are set out, to be come, and all kinds of fields is divided into 2 classes: not reproducible field (the first selected word
Section) and repeatable field:
For above-mentioned not reproducible field, it is necessary to execute repetition values analysis, it is ensured that such field does not have the field of repetition values
(duplicate elements field is not present), such as identification card number and membership number.
For repeatable field, it is not required that have to carry out repetition values analysis, also do not require to ensure not repeat.
Related shortcut key can be set, so that user is clicked " starting replicate analysis " button starting replicate analysis, analyze result
It can show below tables of data.Optionally, analysis shows that result may include " repeating line number completely ", " non-fully repeat to go
Number ", " repeating row ratio " three indexs:
Line number is repeated completely: being differentiated using elements fields whole in certain row in data, when owning for certain row data
When elements field is all consistent with other a line, show that the behavior repeats to go completely, such as share 5 row data, wherein the first row and
Two rows are consistent, and the third line is consistent with fourth line, fifth line and other are all inconsistent, then repeating line number completely is 4；
Non-fully repeat line number: removing repeats to go completely, as non-fully repeats to go, 5 row data as above non-fully repeat
Line number is 1；
Repeat row ratio: to repeat line number/total line number (repeat line number completely and non-fully repeat the sum of line number), weight completely
The result of multiple row ratio can be expressed as percentage, retain two-decimal.
After the repetition values analysis for carrying out all kinds of fields, situation can also be repeated to single class field and be counted and shown, made
User can check that single class field repeats situation, and " delete and repeat to go " can be arranged after all kinds of fields and " delete weight completely
The shortcut key of multiple row " allows user according to data preparation demand, is pressed by clicking each field subsequent " delete and repeat to go "
Button repeats to go to delete based on the repetition situation of single class field, can also be deleted by click " deletion repeats to go completely " button
The all duplicate row of all fields.
Above-mentioned steps select in field the first kind, after deleting each row repeated in row in addition to the first row, this kind of field
There is no any repetition values (duplicate elements fields), i.e., repeatedly ratio is 0%.
S30 determines that the second class selectes field in the tables of data, identifies that second class selectes the empty word in field
Section, rejects correspondence row of the null field in tables of data；Wherein, the selected field of second class belongs to illegal for null field
A kind of field；
Above-mentioned null field refers in certain class field that elements field is empty elements field；It is sky that above-mentioned second class, which selectes field,
Field belongs to illegal a kind of field, i.e., in the second selected field, the elements field that does not allow blank occur.
Specifically, the tables of data deleted after repeating each row in row in addition to the first row can be shown, is read
Second class of user's selection selectes field, determines the mandatory field (the second class selectes field) and Optional Field of the analysis of vacancy value,
Fields all kinds of in tables of data are carried out to analyze available " complete vacancy line number ", " non-fully vacancy line number " and " vacancy row ratio
Three indexs of example ":
Complete vacancy line number: differentiated using whole fields in tables of data, when all fields of certain row data are
Null field shows the behavior complete vacancy row；
Non-fully vacancy line number: complete vacancy row is removed, as non-fully repeats to go；
Vacancy row ratio: complete vacancy line number/total line number (complete vacancy line number and non-fully the sum of vacancy line number), as a result
It can be expressed as percentage, retain two-decimal.
Vacancy analysis can also be carried out to single class field in tables of data, in the vacancy analysis of single class field, empty word
The character string of symbol string and multiple spaces composition can be regarded as vacancy (null field).
The second class can be deleted to select in field there are the row of vacancy value (null field), make not having in the selected field of the second class
It is 0% that any vacancy value, i.e. the second class, which select the vacancy ratio in field,.
S40 identifies the completely ineffective row of the tables of data, according to the total of the line number of the completely ineffective row and tables of data
Line number calculates completely ineffective ratio, determines that the data before data analysis are quasi- according to the completely ineffective ratio and the tables of data
Standby content；Wherein, the illegal row of the elements field of the selected field of third class in the completely ineffective behavioral data table.
It is that can carry out a kind of field of validation checking that above-mentioned third class, which selectes field, it can according to included by field
The corresponding elements field of identifications such as number of words, the corresponding format of field and field logic effectively or be not necessarily to.It specifically, can be with
Building progress validation checking mode, which detects, illustrates table, illustrates that table determines that the third class in tables of data selectes word according to above-mentioned detection
Section.It is illegal that third class, which selectes the unit character of field, in above-mentioned completely ineffective row, for example can be had in certain tables of data
A kind of field (third class selectes field) of effect property detection includes cell-phone number, identification card number and membership number, if the cell-phone number of certain row
Field includes letter, and the number of words that identification card number field includes is 2 more than corresponding setting number of words, and the number of words that membership number includes is than corresponding
Setting number of words few 2 is the then behavior completely ineffective behavior.After the completely ineffective row for identifying the tables of data, it can count complete
The line number of inactive line the processing such as can also be hidden or delete to above-mentioned completely ineffective row according to data preparation demand, with
User is set to obtain more efficiently data preparation content.
Each row, the corresponding sky of rejecting in row in addition to the first row are repeated according to completely ineffective ratio and successively by deletion
Field be expert at these processing after identified data preparation content can make in subsequent data analysis process, user can be more
Directly to obtain required data, helps that user is made to have an X-rayed business panorama, promote relevant market marketing and operation management ability.
In one embodiment, it can illustrate that each unit field in table detection data table is according to detection shown in table 1
It is no effective, it is legal or illegal with the corresponding elements field of determination, identify the completely ineffective row in tables of data:
Table 1
If finding the above field in tables of data, corresponding content can be shown, and corresponding inspection is executed in analysis
It looks into.Wherein gauge outfit is consistent with gauge outfit in step S20, S30, is not needed selection field, but is replaced to show in the table
The validity check content that mustn't be completed.After the effective analysis supported according to table 1, may include in effective situation in tables of data
Three indexs:
Completely ineffective every trade number: it is related to all of finiteness inspection (validity check that table 1 is supported) in tables of data
Field is differentiated, is checked when the field of the required inspection of certain row data does not pass through, is shown the behavior completely ineffective row；
Non-fully invalid line number: removing completely ineffective row, as non-fully inactive line；
Completely ineffective ratio: completely ineffective line number/total line number (completely ineffective line number and non-fully the sum of invalid line number), knot
Fruit is expressed as percentage, retains two-decimal；
It can choose and delete in data there are the row of invalid value, it, must when one data word section is there are when multiple scopes of examination
It is effective for must just being calculated by all inspections, and otherwise the field data is considered as in vain.
Big data system file data preparation method provided in this embodiment can be read single from the data file of importing
Elements field is directed respectively into the field contents region of each field name by first field, right respectively with each field name of determination
All kinds of fields answered and the tables of data including all kinds of fields determine that the first kind selectes field in the tables of data, with identification
Repetition row in tables of data deletes the above-mentioned each row repeated in row in addition to the first row, and determines second in above-mentioned tables of data
Class selectes field, to identify that second class selectes the null field in field, rejects correspondence of the null field in tables of data
Row, can also identify the completely ineffective row in tables of data, calculate completely ineffective ratio, determine that the data before data analysis are quasi- with this
Standby content, the Data Preparation before can simplify data analysis, reduces data preparation cost.
In one embodiment, the completely ineffective row of the identification tables of data, according to the row of the completely ineffective row
Several and tables of data total line number has been calculated after the process completely without effect ratio, further includes:
Field is selected according to the 4th class and determines extension title, reads institute from the elements field in the setting type field
State the corresponding extension content of extension title；Wherein, it is that can continue to expand other types field that the 4th class, which selectes field,
Field；Wherein, it is the field that can continue to expand other types field that the 4th class, which selectes field,.
It is the field that can continue to expand other class fields that above-mentioned 4th class, which selectes field, can be according to the expansion prestored
The attributive character for opening up rule list or field determines that this field can expand Birth field, native place field such as identification card number,
So the two extension titles of Birth field, native place field can be determined according to identification card number field, it can also be from identification card number
Elements field in read out corresponding birthday and native place, to determine the corresponding extension content of extension title respectively, make tables of data
The field type for being included is more fully.
As one embodiment, the completely ineffective row of the identification tables of data, according to the row of the completely ineffective row
Several and tables of data total line number has been calculated after the process completely without effect ratio, further includes:
Effective field line number in identification extension content, total line number according to the effective field line number and extension content are true
Surely success rate is extended.
The present embodiment can illustrate validation checking rule (such as identification word of table or setting by related validation checking
Number, format and/or field logic) etc. modes identify the effective field in extension content, count the line number of above-mentioned effective field, with
It determines extension success rate, further improves the content of tables of data, keep Data Preparation more abundant.
As one embodiment, after the completely ineffective ratio for calculating tables of data, it can inquire that user is by dialog box
It is no to be extended, if do not extended, data can also be extended in subsequent processes, field can be executed if extension
Dimension extension (such as selectes field according to the 4th class and determines extension title, read from the elements field in the setting type field
Take the corresponding extension content of the extension title；Wherein, it is that can continue to expand other types that the 4th class, which selectes field,
The field of field), it is come out with going out new field according to existing field extension.Extension rule provided in this embodiment can be such as table
Shown in 2:
Table 2
User can select the field for needing to extend with determination according to extension rule shown in table 2, and click is preset " to be started to expand
Exhibition " button, the result preview after obtaining extended field, and show spread scenarios, the spread scenarios shown may include following 5
A index:
Extended field name: include all extended fields chosen, the sequentially sequence consensus with rule base shown in table 2；
Total amount of data: i.e. total line number of data；
It extends successfully or extension failure: being considered as success by what the extension logic of system can normally generate field data,
It unmatches, situations such as this is as sky, is accordingly to be regarded as failure；
Extension success rate: extending and successfully count/total amount of data, is as a result expressed as percentage, retains two-decimal.
In extended field, it is understood that there may be with the duplicate extended field of original field, i.e., existing field in tables of data, such as
Tables of data used life field, expands age field from identification card number, then can remember that the former age in tables of data is A, expand
Opening up the obtained age is B, and two fields can be merged into " age " field and be shown, the included data of merging process
Processing mode is as follows:
If A no data, B there are data, B data is used；If A has data, B no data uses A data；If A no data, B without
Data, for sky；If A has data, B has data: using B data.After user confirms above-mentioned spreading result, extension knot can be saved
Fruit, the data preparation content before determining data analysis.
Big data system file data preparation method provided in this embodiment is suitable for the data based on intelligent marketing platform
Preparation method can make relative clients oneself operation data, voluntarily carry out expansible data scrubbing；In big data system file
In Data Preparation Process, cleaning rule can also be used to store according to preparation requirement setting rule base and algorithms library, above-mentioned rule base
Then, algorithms library is used to store cleaning algorithm, and algorithms library may include many algorithms, and can extend to it.By in rule base
It defines cleaning rule and selects suitable cleaning algorithm from algorithms library, the big data system file data can be made to prepare scheme
Suitable for different data sources, to make it have stronger versatility and adaptability, by the cleaning of many algorithms, improve
The resultant effect of data scrubbing.Above-mentioned big data system file data preparation method can become complete marketing data and analyze
The data access of process, and the data of different company are managed by the way of point library.For the light weight for ensureing platform in operation
Change and subsequent expansibility, data source access use file lead-in mode, file can be provided on importing interface and import dialog box
Realize this function, can be using data be first imported for the standardization issue of data field, rear is the side that data arrange specified title
Formula is handled.
In one embodiment, reading unit field in the data file from importing, elements field is directed respectively into
The field contents region of each field name determines the corresponding all kinds of fields of each field name and including all kinds of fields
Tables of data process before, further includes:
The data file that user uploads is imported, identifies the format of the data file；
If the format of the data file is the first setting format, the reading unit field from the data file of importing.
The present embodiment can identify the format of data file by the file name suffix of data file.Above-mentioned first setting lattice
Formula may include xls (Microsoft Excel worksheet) format or xlsx format.From the data of above-mentioned first setting format
In file, each unit field directly can be directed respectively into the corresponding field contents region of respective field title, guarantee unit
The importing efficiency of field.
As one embodiment, the data file for importing user and uploading identifies the mistake of the format of the data file
After journey, further includes:
If the format of the data file is the second setting format, use separator by the file in the data file
Content is divided into multiple elements fields.
Above-mentioned second setting format may include txt format and csv format.
Specifically, the preceding partial file content in data file can be shown, so as to the above-mentioned file content of user's preview, i.e.,
It can be seen that the preceding partial content (such as preceding 5 style of writing is originally) of text file, provides the selection of field seperator, meeting after selection for user
Show a preview after this article this document (data file) imports.Separator can set symbol for comma etc., if user
Separator used in upper transmitting file is not setting symbol, and each field of the file content of preview is necessarily incorrect, all fields
It may squeeze in the same field, this problem can be solved by the way that field seperator is revised as setting symbol at this time.It determines
After separator, preview page can refresh automatically
File content in the data file is divided into multiple elements fields, Ke Yibao using separator by the present embodiment
Demonstrate,prove the subsequent accuracy for carrying out elements field importing.
It, will using separator if the format of the data file is the second setting format as one embodiment
File content in the data file is divided into after the process of multiple elements fields, further includes:
Identify whether the format of the data file and the elements field that the data file includes are legal respectively, if
It is, then the reading unit field from the data file of importing.
Legal format includes the first setting format and the second setting format in the present embodiment, and legal elements field is can
With the elements field being matched in the corresponding field of respective field title.
The present embodiment can guarantee the fairness in elements field reading process.
As one embodiment, the data file for importing user and uploading identifies the mistake of the format of the data file
Before journey, further includes:
Whether the data file that identification user uploads is the first setting format or the second setting format, if it is not, then showing
Warning prompt frame；Wherein, the warning prompt frame is the dialog box for prompting subscriber data file format illegal.
Above-mentioned warning prompt frame include legal formatting hints (as at present only support TXT file, csv file, XLS file and
Four kinds of formats of XLSX file, please reselect file and be uploaded), it can also include the behaviour of " reselecting file " and " cancellation "
It prompts.When (data file that user uploads is not set format for first, and do not set for second to file format check errors
Format) when, warning prompt frame is popped up, so that user is selected " reselecting file " or " cancellation " operation, if user is in warning prompt
Clicked in frame " it reselects file and " when button, the legal (data file of file selection box uploaded format can be again turned on
One setting format or second setting format) data file, if cancel selection, corresponding parent page can be returned.If
The data file that user uploads is the first setting format or the second setting format, then may indicate that data file verifies successfully,
Data file name can be shown in file selection box.
The present embodiment can guarantee the validity for the data file that user uploads, and help to improve subsequent reading elements field
Fairness.
It show the big data system file data preparation system structural schematic diagram of one embodiment with reference to Fig. 2, Fig. 2, wraps
It includes:
Elements field is directed respectively into each by read module 10 for the reading unit field from the data file of importing
The field contents region of field name determines the corresponding all kinds of fields of each field name and the number including all kinds of fields
According to table；
First determining module 20 identifies the first kind choosing for determining that the first kind selectes field in the tables of data
Determine the repetitive unit field in field, the repetition row in tables of data is determined according to repetitive unit field, deletes described repeat in row
Each row in addition to the first row；Wherein, it is to repeat elements field to belong to illegal a kind of field that the first kind, which selectes field,；
Second determining module 30 identifies the second class choosing for determining that the second class selectes field in the tables of data
Determine the null field in field, rejects correspondence row of the null field in tables of data；
First identification module 40, the completely ineffective row of the tables of data for identification, according to the row of the completely ineffective row
Several and tables of data total line number has been calculated completely without effect ratio, determines number according to the completely ineffective ratio and the tables of data
According to the data preparation content before analysis；Wherein, in the completely ineffective behavioral data table third class select field elements field
Illegal row.
In one embodiment, the big data system file data preparation system further include:
Third determining module determines extension title for selecting field according to the 4th class, from the setting type field
Elements field in read the corresponding extension content of the extension title；Wherein, it is that can continue to that the 4th class, which selectes field,
Expand the field of other types field.
As one embodiment, the big data system file data preparation system further include:
4th determining module extends the effective field line number in content for identification, according to the effective field line number and
The total line number for extending content determines extension success rate.
In one embodiment, the big data system file data preparation system further include:
Import modul imports the data file that user uploads, identifies the format of the data file；If the data file
Format be first setting format, then enter read module execute from the data file of importing reading unit field.
As one embodiment, the big data system file data preparation system further include:
Separating modules use separator by the number if the format for the data file is the second setting format
Multiple elements fields are divided into according to the file content in file.
As one embodiment, the big data system file data preparation system further include:
Second identification module, for identifying the format and the data file unit that includes of the data file respectively
Whether field is legal, if so, executing the reading unit field from the data file of importing into read module.
As one embodiment, the big data system file data preparation system further include:
Whether third identification module, the data file that user uploads for identification are the first setting format or the second setting
Format, if it is not, then showing warning prompt frame；Wherein, the warning prompt frame is pair for prompting subscriber data file format illegal
Talk about frame.
Fig. 3 is the module map for being able to achieve a computer system 1000 of the embodiment of the present invention.The computer system 1000
An only example for being suitable for the invention computer environment is not construed as proposing appointing to use scope of the invention
What is limited.Computer system 1000 can not be construed to need to rely on or the illustrative computer system 1000 with diagram
In one or more components combination.
Computer system 1000 shown in Fig. 3 is the example for being suitable for computer system of the invention.Have
Other frameworks of different sub-systems configuration also can be used.Such as to have big well known desktop computer, notebook etc. similar
Equipment can be adapted for some embodiments of the present invention.But it is not limited to equipment enumerated above.
As shown in figure 3, computer system 1000 includes processor 1010, memory 1020 and system bus 1022.Including
Various system components including memory 1020 and processor 1010 are connected on system bus 1022.Processor 1010 is one
For executing the hardware of computer program instructions by arithmetic sum logical operation basic in computer system.Memory 1020
It is one for temporarily or permanently storing the physical equipment of calculation procedure or data (for example, program state information).System is total
Line 1020 can be any one in the bus structures of following several types, including memory bus or storage control, outer
If bus and local bus.Processor 1010 and memory 1020 can carry out data communication by system bus 1022.Wherein
Memory 1020 includes read-only memory (ROM) or flash memory (being all not shown in figure) and random access memory (RAM), RAM
Typically refer to the main memory for being loaded with operating system and application program.
Computer system 1000 further includes display interface 1030 (for example, graphics processing unit), display 1040 (example of equipment
Such as, liquid crystal display), audio interface 1050 (for example, sound card) and audio frequency apparatus 1060 (for example, loudspeaker).Show equipment
1040 can be used for the display of data content and warning prompt frame.
Computer system 1000 generally comprises a storage equipment 1070.Storing equipment 1070 can from a variety of computers
It reads to select in medium, computer-readable medium refers to any available medium that can be accessed by computer system 1000,
Including mobile and fixed two media.For example, computer-readable medium includes but is not limited to, flash memory (miniature SD
Card), CD-ROM, digital versatile disc (DVD) or other optical disc storages, cassette, tape, disk storage or other magnetic storages are set
Any other medium that is standby, or can be used for storing information needed and can be accessed by computer system 1000.
Computer system 1000 further includes input unit 1080 and input interface 1090 (for example, I/O controller).User can
With by input unit 1080, such as the touch panel equipment in keyboard, mouse, display device 1040, input instruction and information are arrived
In computer system 1000.Input unit 1080 is usually connected on system bus 1022 by input interface 1090, but
It can also be connected by other interfaces or bus structures, such as universal serial bus (USB).
Computer system 1000 can carry out logical connection with one or more network equipment in a network environment.Network is set
It is standby to can be PC, server, router, tablet computer or other common network nodes.Computer system 1000 is logical
It crosses local area network (LAN) interface 1100 or mobile comm unit 1110 is connected with the network equipment.Local area network (LAN) refers to having
It limits in region, such as family, school, computer laboratory or the office building using the network media, interconnects the computer of composition
Network.WiFi and twisted pair wiring Ethernet are two kinds of technologies of most common building local area network.WiFi is a kind of to make to calculate
1000 swapping data of machine system or the technology that wireless network is connected to by radio wave.Mobile comm unit 1110 can be one
It answers and makes a phone call by radio communication diagram while movement in a wide geographic area.Other than call, move
Dynamic communication unit 1110 is also supported to carry out internet visit in 2G, 3G or the 4G cellular communication system for providing mobile data service
It asks.
It should be pointed out that other includes than the computer system of the more or fewer subsystems of computer system 1000
It can be suitably used for inventing.As detailed above, big data system text can be executed by being suitable for the invention computer system 1000
The specified operation of part data preparation method.Computer system 1000 is run in computer-readable medium by processor 1010
The form of software instruction executes these operations.These software instructions from storage equipment 1070 or can pass through lan interfaces
1100 are read into memory 1020 from another equipment.The software instruction being stored in memory 1020 holds processor 1010
The above-mentioned big data system file data preparation method of row.In addition, passing through hardware circuit or hardware circuit combination software instruction
Also the present invention can be equally realized.Therefore, realize that the present invention is not limited to the combinations of any specific hardware circuit and software.
Big data system file data preparation system of the invention and big data system file data preparation side of the invention
Method corresponds, in the technical characteristic and its advantages of the embodiment elaboration of above-mentioned big data system file data preparation method
Suitable for the embodiment of big data system file data preparation system.
Based on example as described above, a kind of computer equipment is also provided in one embodiment, the computer equipment packet
The computer program that includes memory, processor and storage on a memory and can run on a processor, wherein processor executes
It realizes when described program such as any one big data system file data preparation method in the various embodiments described above.
Above-mentioned computer equipment realizes Data Preparation by the computer program run on the processor
Simplified and data setting up cost control.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, it is non-volatile computer-readable that the program can be stored in one
It takes in storage medium, in the embodiment of the present invention, which be can be stored in the storage medium of computer system, and by the calculating
At least one processor in machine system executes, and includes the implementation such as above-mentioned big data system file data preparation method with realization
The process of example.Wherein, the storage medium can for magnetic disk, CD, read-only memory (Read-Only Memory,
) or random access memory (Random Access Memory, RAM) etc. ROM.
Accordingly, a kind of computer storage medium is also provided in one embodiment, is stored thereon with computer program,
In, it realizes when which is executed by processor such as any one big data system file data preparation side in the various embodiments described above
Method.
Above-mentioned computer storage medium can reduce data preparation cost by the computer program that it is stored.
Each technical characteristic of embodiment described above can be combined arbitrarily, for simplicity of description, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, all should be considered as described in this specification.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to protection of the invention
Range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (10)
1. a kind of big data system file data preparation method characterized by comprising
Elements field is directed respectively into the field contents area of each field name by the reading unit field from the data file of importing
Domain determines the corresponding all kinds of fields of each field name and the tables of data including all kinds of fields；
It determines that the first kind selectes field in the tables of data, identifies that the first kind selectes the repetitive unit field in field,
The repetition row in tables of data is determined according to repetitive unit field, deletes each row repeated in row in addition to the first row；
It determines that the second class selectes field in the tables of data, identifies that second class selectes the null field in field, reject institute
State correspondence row of the null field in tables of data；
The completely ineffective row for identifying the tables of data is calculated according to total line number of the line number of the completely ineffective row and tables of data
Completely ineffective ratio determines the data preparation content before data analysis according to the completely ineffective ratio and the tables of data；
Wherein, the illegal row of the elements field of the selected field of third class in the completely ineffective behavioral data table.
2. big data system file data preparation method according to claim 1, which is characterized in that the identification number
According to the completely ineffective row of table, had been calculated according to total line number of the line number of the completely ineffective row and tables of data completely without effect ratio
After process, further includes:
Field is selected according to the 4th class and determines extension title, reads the expansion from the elements field in the setting type field
Open up the corresponding extension content of title.
3. big data system file data preparation method according to claim 2, which is characterized in that the identification number
According to the completely ineffective row of table, had been calculated according to total line number of the line number of the completely ineffective row and tables of data completely without effect ratio
After process, further includes:
Effective field line number in identification extension content, determines according to total line number of the effective field line number and extension content and expands
Transform into power.
4. big data system file data preparation method according to claim 1, which is characterized in that the number from importing
According to reading unit field in file, elements field is directed respectively into the field contents region of each field name, determines each word
Before the process of the corresponding all kinds of fields of name section and the tables of data including all kinds of fields, further includes:
The data file that user uploads is imported, identifies the format of the data file；
If the format of the data file is the first setting format, the reading unit field from the data file of importing.
5. big data system file data preparation method according to claim 4, which is characterized in that on the importing user
The data file of biography, after the process for identifying the format of the data file, further includes:
If the format of the data file is the second setting format, use separator by the file content in the data file
It is divided into multiple elements fields.
6. big data system file data preparation method according to claim 5, which is characterized in that if the data
The format of file is the second setting format, then the file content in the data file is divided into multiple units using separator
After the process of field, further includes:
Identify whether the format of the data file and the elements field that the data file includes are legal respectively, if so,
The reading unit field from the data file of importing.
7. big data system file data preparation method according to claim 4, which is characterized in that on the importing user
The data file of biography, before the process for identifying the format of the data file, further includes:
Whether the data file that identification user uploads is the first setting format or the second setting format, if it is not, then showing warning
Prompting frame；Wherein, the warning prompt frame is the dialog box for prompting subscriber data file format illegal.
8. a kind of big data system file data preparation system characterized by comprising
Elements field is directed respectively into each field name for the reading unit field from the data file of importing by read module
The field contents region of title determines the corresponding all kinds of fields of each field name and the tables of data including all kinds of fields；
First determining module identifies that the first kind selectes field for determining that the first kind selectes field in the tables of data
In repetitive unit field, the repetition row in tables of data is determined according to repetitive unit field, deletes and described repeats to remove first in row
Each row except row；
Second determining module identifies that second class selectes field for determining that the second class selectes field in the tables of data
In null field, reject correspondence row of the null field in tables of data；
First identification module, the completely ineffective row of the tables of data for identification, according to the line number of the completely ineffective row and
Total line number of tables of data has been calculated completely without effect ratio, determines that data are analyzed according to the completely ineffective ratio and the tables of data
Preceding data preparation content；Wherein, the elements field of the selected field of third class is illegal in the completely ineffective behavioral data table
Row.
9. a kind of computer equipment, including memory, processor and it is stored on the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
Big data system file data preparation method described in 7 any one.
10. a kind of computer storage medium, is stored thereon with computer program, which is characterized in that the program is executed by processor
Shi Shixian big data system file data preparation method as claimed in any one of claims 1 to 7.
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| CN201811067749.2A CN109376152A (en) | 2018-09-13 | 2018-09-13 | Big data system file data preparation method and system |
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