CN109558462A - Data statistical approach and device - Google Patents
Data statistical approach and device Download PDFInfo
- Publication number
- CN109558462A CN109558462A CN201811300937.5A CN201811300937A CN109558462A CN 109558462 A CN109558462 A CN 109558462A CN 201811300937 A CN201811300937 A CN 201811300937A CN 109558462 A CN109558462 A CN 109558462A
- Authority
- CN
- China
- Prior art keywords
- data
- statistical
- dimension
- statistical dimension
- statistics
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention is suitable for field of computer technology, provides a kind of data statistical approach and device, comprising: obtain the first data to be processed, determine the data type of first data；The corresponding statistical dimension of first data is determined according to the data type；Extract corresponding second data of each statistical dimension respectively from first data；Data statistics strategy based on each statistical dimension, corresponding second data of each statistical dimension are counted, and statistical result is obtained.By classifying to the first data to be processed, determine the dimension that the first data to be processed need to count, the dimension counted as needed is extracted from the first data each needs corresponding second data of statistical dimension, in this way during statistics, it is searched without first ergodic data library, data to be processed can directly be counted, improve the efficiency of statistics.
Description
Technical field
The invention belongs to field of computer technology more particularly to a kind of data statistical approach and device.
Background technique
Traditional data statistical approach is usually to pass through query statement to take out basic data from searching database, and to base
Plinth data are counted.
However, when business relations are complicated, data volume is big, need to carry out various dimensions statistics to data when, need to write a large amount of
Complicated query statement and statistics sentence, recall precision and statistical efficiency are low, and the stability of system is poor.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of data statistical approach and device, to solve industry in the prior art
Business relationship is complicated, data volume is big, when needing to carry out various dimensions statistics to data, needs to write the query statement and system of large amount of complex
Sentence is counted, recall precision and statistical efficiency are low, the problem of the stability difference of system.
The first aspect of the embodiment of the present invention provides a kind of data statistical approach, comprising:
The first data to be processed are obtained, determine the data type of first data；
The corresponding statistical dimension of first data is determined according to the data type；
Extract corresponding second data of each statistical dimension respectively from first data；
Data statistics strategy based on each statistical dimension, corresponding second data of each statistical dimension carry out
Statistics, obtains statistical result.
The second aspect of the embodiment of the present invention provides a kind of data statistics device, comprising:
Acquiring unit determines the data type of first data for obtaining the first data to be processed；
Determination unit, for determining the corresponding statistical dimension of first data according to the data type；
Extraction unit, for extracting corresponding second data of each statistical dimension respectively from first data；
Processing unit, it is corresponding for the data statistics strategy based on each statistical dimension, each statistical dimension
The second data counted, obtain statistical result.
The third aspect of the embodiment of the present invention provides a kind of data statistics terminal, comprising: memory, processor and deposits
Store up the computer program that can be run in the memory and on the processor, which is characterized in that the processor executes
The step of above-mentioned first aspect the method is realized when the computer program.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, comprising: computer program,
It is characterized in that, the computer program realizes above-mentioned first aspect the method when being executed by processor the step of.
The embodiment of the present invention determines the data type of the first data, according to data by obtaining the first data to be processed
Type determines the corresponding statistical dimension of the first data, and it is corresponding to extract each statistical dimension respectively from first data
Second data, data statistics strategy based on each statistical dimension, corresponding second data of each statistical dimension into
Row statistics, obtains statistical result.By classifying to the first data to be processed, determine that the first data to be processed need to unite
The dimension of meter, the dimension counted as needed extracted from the first data it is each need corresponding second data of statistical dimension, this
Sample is searched during statistics without first ergodic data library, can directly be counted, be mentioned to data to be processed
The high efficiency of statistics.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is a kind of schematic flow diagram of data statistical approach provided in an embodiment of the present invention；
Fig. 2 is the implementation flow chart of S101 in a kind of data statistical approach provided in an embodiment of the present invention；
Fig. 3 is the implementation flow chart of S104 in a kind of data statistical approach provided in an embodiment of the present invention；
Fig. 4 is the implementation flow chart of S1042 in a kind of data statistical approach provided in an embodiment of the present invention；
Fig. 5 is the implementation flow chart of data statistical approach S105~S107 provided in an embodiment of the present invention a kind of；
Fig. 6 is a kind of schematic diagram of data statistics device provided in an embodiment of the present invention；
Fig. 7 is the schematic diagram of data statistics terminal provided in an embodiment of the present invention.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.In order to illustrate this
The invention technical solution, the following is a description of specific embodiments.Referring to Figure 1, Fig. 1 is that the embodiment of the present invention mentions
A kind of schematic flow diagram of the data statistical approach supplied.The executing subject of the method for data statistics is terminal in the present embodiment, eventually
End includes but is not limited to the terminals such as desktop computer, smart phone, tablet computer, personal digital assistant PAD.Number as shown in the figure
Method according to statistics can include:
In S101, the first data to be processed are obtained, determine the data type of first data.
Terminal obtains the first data to be processed, and the process of trigger data statistics handles the first data, determines the
The data type of one data.First data to be processed are data object to be processed, can be the number of any required statistics
According to, such as ad data, online shopping mall's order data, evaluation of employee achievement data etc..Data type is actually to treat place
The data object of reason does a classification.For example, if online shopping mall's order data as data object to be processed, on the net
Store order data can be divided into ordinary user's purchase order, purchase by group order, send order with charge free etc..Terminal is obtaining quotient on the net
After the order of city, the data type of online shopping mall's order data is determined, be ordinary user's purchase order, purchase by group order, send with charge free and order
It is any in list.
Optionally, S101 may include S1011~S1012, as shown in Figure 2.It is specific as follows:
S1011: obtaining the first data to be processed, and obtains the data attribute of first data.
Terminal obtains the first data to be processed, and the process of trigger data statistics is extracted from the first data to be processed
A preset data field, the data attributes of the first data is determined based on the meaning of data field mark.Wherein, data
Attribute, for identifying the data characteristics of the first data to be processed.
S1012: according to the preset corresponding pass between the data attribute, data attribute and data type of first data
System, determines the data type of first data.
The corresponding relationship between data attribute and data type is preset and be stored in terminal, is getting data category
Property when, according to the corresponding relationship between data attribute and data type, obtain the corresponding data class of data attribute of the first data
Type, to obtain the data type of the first data.The data type of first data is for determining belonging to the first data to be processed
Classification.For example, the data attribute is corresponding when detecting the field for being used for mark data attribute in the first data is a field
Data type be online shopping mall's group purchase information；The field of mark data attribute is used in the first data as b word when detecting
Duan Shi, the corresponding data type of the data attribute are the purchase information that online shopping mall uses discount coupon.
In the present embodiment, by the corresponding relationship preset and between storing data attribute and data type, eventually
After end obtains the data attribute of the first data, the corresponding data type of the data attribute can determine, so that it is determined that be processed
The corresponding data type of first data.The data type obtained in this way is more accurate, and efficiency is also higher.
In S102, the corresponding statistical dimension of first data is determined according to the data type.
In one embodiment, terminal can parse data type, obtain the corresponding statistical dimension of the first data.Wherein,
It, can be comprising being somebody's turn to do in the information of application-specific data type because data type is a definition to the affiliated type of the first data
Categorical data needs the statistical dimension counted, and the information by parsing application-specific data type can obtain the corresponding system of the first data
Count dimension.
In another embodiment, its corresponding statistical dimension is set for every kind of data type in advance, due to each type
The data of type have a corresponding statistical dimension, therefore, terminal when the data type of the first data to be processed has been determined,
The first data pair can be determined according to the data type of incidence relation and the first data between data type and statistical dimension
The statistical dimension answered.
Further, the first data can be store order data, and the data type of the first data is purchase order.S102
It specifically includes: according to the purchase order, determining the corresponding statistical dimension of the purchase order；Wherein, the purchase order pair
The statistical dimension answered include the sales volume of trade company, the sales volume of the commodity of purchase, purchase the corresponding production plant of commodity pin
Sell volume.
For example, the first data can be store order data, the data type of the first data is purchase order, according to purchase
Order can determine the corresponding statistical dimension of store order data include: the sales volume of trade company, purchase commodity sales volume,
The sales volume, etc. of the corresponding production plant of the commodity of purchase.Wherein, the sales volume of trade company is to sell the trade company of the commodity
Sales volume；The sales volume of the commodity of purchase is the total sales volume in this store commodity；The corresponding production work of the commodity of purchase
The sales volume of the commodity is sold by the factory that the sales volume of factory as produces the commodity.During subsequent statistical, to store
The statistics of order information will from the sales volume of trade company, the sales volume of the commodity of purchase, purchase commodity corresponding production plants
These dimensions of sales volume go to handle.
Optionally, S102 may include: the corresponding relationship according to data type and statistical dimension, determine first data
The corresponding statistical dimension of data type, obtain the corresponding statistical dimension of first data.
Terminal presets and is stored with the corresponding relationship of data type and statistical dimension, and same data type has corresponded to this
All statistical dimensions that one categorical data should be counted in statistics, this corresponding relationship can voluntarily be set previously according to demand
It sets.By presetting the corresponding relationship of data type and statistical dimension, the corresponding system of data type can be rapidly obtained
Count dimension.Also, due to the corresponding relationship of data type and statistical dimension be can be pre-set, it is possible to it is flexible to adjust
The corresponding statistical dimension of whole every kind of data type, for example, when data type is to purchase by group order, it according to the demand of user can be pre-
It includes: to purchase by group quantity that first setting, which purchases by group the corresponding statistical dimension of order, purchases by group commodity sales number, purchases by group commodity profit；When with
When family needs to increase new statistical dimension group purchase user information, it can be adjusted to the corresponding statistical dimension of order is purchased by group,
Group purchase user information is added on the basis of original.In this way, user is allowed to adjust different types of data according to their own needs
The dimension for needing to count improves the flexibility of system, also improves the efficiency of statistics.
In S103, corresponding second data of each statistical dimension are extracted respectively from first data.
After terminal has determined that the first data need the dimension that counts, the first data are handled and split, extracts the
Each in one data needs data information corresponding to statistical dimension, i.e., corresponding second data of each statistical dimension.
Such as first data be store order data, the data type got according to store order data is purchase order, according to purchase
The order bought can determine that order data corresponding statistical dimension in store includes: the personal letter of the sales volume of trade company, purchase user
The unit price of breath, purchase commodity.Wherein, the first data store order information is Zhang San with 68 yuan of unit price, has purchased 2 cups, from
Corresponding second data of sales volume for counting trade company are extracted in first data store order information to be 136, buy user
Corresponding second data of personal information be Zhang San, purchase commodity corresponding second data of unit price be 68.
In S104, data statistics strategy, each statistical dimension based on each statistical dimension corresponding
Two data are counted, and statistical result is obtained.
Terminal pre-sets the data statistics strategy of each statistical dimension, the data statistics strategy of different statistical dimensions
It can be different.For example the statistics strategy of sales volume of goods can be the operation of addition, and the commodity amount that user buys is added to original
In some sales volume data；The data statistics strategy of statistical dimension can also be set as a mapping relations, such as known order
Single amount of money counts the sales volume of this affiliated trade company of order commodity, in addition the price of value order accordingly, mapping relations can
Think orderPrice- > commercialSales.After obtaining corresponding second data of each statistical dimension, according to every
The data statistics strategy of a statistical dimension, the second data corresponding to each statistical dimension count, and obtain each dimension pair
The statistical result answered.
Optionally, S104 may include S1041~S1042, as shown in Figure 3.It is specific as follows:
S1041: data statistics strategy, each statistical dimension corresponding second based on each statistical dimension count
According to determining the corresponding more new information of each statistical dimension.
Such as first data be store order data, the data type got according to store order data be purchase order
It is single, it can determine that order data corresponding statistical dimension in store includes: the sales volume of trade company, purchase user according to the order of purchase
Personal information, buy commodity unit price.Wherein, the first data store order information is Zhang San with 68 yuan of unit price, has purchased 2
Cup, corresponding second data of sales volume that trade company is extracted from the first data store order information are 136, buy user's
Corresponding second data of personal information be Zhang San, purchase commodity corresponding second data of unit price be 68.At this point, according to different dimensional
Spending tactful the second data corresponding to the sales volume of trade company of corresponding statistics is 136；Buy the personal information corresponding the of user
Two data are Zhang San；Corresponding second data of unit price for buying commodity are 68, are counted.The statistics strategy of the sales volume of trade company
It can be the new data that adds up on legacy data, according to the statistics of the sales volume of trade company tactful corresponding with the sales volume of trade company the
The information that the needs that two data obtain update are as follows: the sales volume of trade company cumulative 136.Wherein more new packets include data to be updated
And the strategy updated.
S1042: based on the statistical data in the update information update database.
Terminal, according to more new strategy different in more new information, more new information can be made when getting more new information
It is stored in database for new entry, local updating directly can also be carried out to database, obtain statistical result.For example, trade company
The statistics strategy of sales volume can be the new data that adds up on legacy data, according to the statistics strategy of the sales volume of trade company and trade company
The information that updates of the obtained needs of corresponding second data of sales volume are as follows: the sales volume of trade company cumulative 136, at this point, in data
The sales volume of the trade company is increased by 136 on the basis of the original in library, to obtain the current sales volume of the trade company.
In present embodiment, the more new information updated into database is needed according to the second data acquisition, it will more new information
It is stored in database, obtains statistical result, by obtaining more new information, the convenient system for storing to data, while also exporting
Meter the result is that after have passed through database update as a result, improving the efficiency of statistics and storage.
Optionally, S1042 may include S10421~S10422, as shown in Figure 4.It is specific as follows:
S10421: the label information of corresponding second data of each statistical dimension is obtained；
Terminal gets corresponding second data of each statistical dimension, extracts the label information in the second data information.Its
In, the label information of the second data is used to identify the data type of corresponding second data of each statistical dimension, for example, label is believed
Ceasing for identifying the data type is to belong to data volume greatly but the data of not high this type of value, still fall within frequent access
The data of this type.Wherein, label information can there are many kinds of, corresponding second data type can also there are many kinds of, no
Same label information corresponds to different data types, and different label informations can be arranged in user according to oneself demand, herein
With no restrictions.
S10422:, will be described according to the default corresponding relationship between the label information, label information and Database Identification
The corresponding corresponding database of label information for updating information update to second data of each statistical dimension.
Terminal pre-sets the default corresponding relationship between label information and Database Identification, and terminal obtains label letter
Breath, it is according to the default corresponding relationship between label information and Database Identification, each statistical dimension is corresponding more
New information is updated to the corresponding database of label information of second data.Wherein, label information identifies the second data
Data type, different types of data are possibly stored in different types of database, and the corresponding database of label information is exactly
Store the database of second data of the type.For example, label information a representative is the data type that can frequently read, determine
The corresponding data of buffer tag information a are needed, then label information a is default corresponding between label information and Database Identification
The characteristics of corresponding in relationship is redis database, redis database is to look for searching for very convenient quick, is often used as
Cache database.If being a according to the corresponding label information of the second data of the second data acquisition, just illustrate this
Two data are the data type frequently read, need to cache the second data, are stored into redis database.In addition, data
Library further include: mongo database, since efficiency is very high when carrying out mass data access for mongo database, write performance is good,
But and it is dangerous, it is possible to be used to not high enough, the relatively high data of enquiry frequency of the big value of storage data quantity；Hbash number
It is more convenient when due to hbash database purchase according to library, but be inconvenient to inquire, it is possible to it is not needed for storing
The data often inquired.
In present embodiment, the label information by obtaining the second data finds the database of suitable second data storage,
It realizes and is stored data according to the characteristic of data in different databases, to improve statistics, the efficiency of storing data.
It optionally, can also include S105~S107, as shown in Figure 5 after S10422.It is specific as follows:
S105: when receiving the instruction for searching data, the data attribute of target data to be found is determined.
Terminal receive search data instruction when, trigger data search process, wherein search data command include to
The information of the information of the target data of lookup, the corresponding statistical dimension of information of target data to be found.Terminal from search number
According to the information for the statistical dimension for extracting target data to be found in instruction, based on pre- between statistical dimension and data attribute
If corresponding relationship, the corresponding data attribute of each statistical dimension of target data to be found, target to be found are determined
Data may need to obtain the data for having multiple statistical dimensions, since the data of each statistical dimension have corresponding data category
Property, therefore, the data of multiple statistical dimensions just have multiple data attributes.
S106: according to the default corresponding relationship between data attribute and database, the data category of the target data is determined
The corresponding target database of property.
Terminal presets the corresponding relationship between the data attribute and database of target data to be found, the number of different dimensions
According to due to data characteristics difference, the database of storage is not also identical, so can be true according to the data attribute of data to be found
The database of fixed data storage.
For example, the sales volume and unit price for searching that the target information to be found that data command includes is A board cup are received, then
The corresponding dimensional information of data information to be found are as follows: the unit price of the sales volume of A board cup, A board cup, pin of the terminal from A board cup
Amount, A board cup unit price in extract A board cup sales volume data attribute be c, A board cup unit price data attribute be
D, then based on the default corresponding relationship between data attribute and database, so that it may determine represent A board cup sales volume this
The data of dimension are stored in the corresponding database of data attribute c, and the data of this monovalent dimension of A board cup are storages
In the corresponding database of data attribute d.
S107: the target data is obtained from the target database.
Terminal has determined the target database for storing target data to be found, extracts from look-up command to be found
The field of target data can search the field of target data in target database, extract the field pair from target database
The total data answered, as target data.The instruction that data can also be searched by parsing, parses target data to be found
Key message target data is directly filtered out from database according to screening conditions as screening conditions.
Present embodiment parses the data dimension required to look up by the analysis to data command is searched, and determines different
The database of the data storage of data dimension, therefrom searches and extracts target data.In this way without traversing each database, so that it may
Targetedly to find out the target data of various dimensions, the efficiency for searching data is improved.
The embodiment of the present invention determines the data type of the first data, according to data by obtaining the first data to be processed
Type determines the corresponding statistical dimension of the first data, and it is corresponding to extract each statistical dimension respectively from first data
Second data, data statistics strategy based on each statistical dimension, corresponding second data of each statistical dimension into
Row statistics, obtains statistical result.By classifying to the first data to be processed, determine that the first data to be processed need to unite
The dimension of meter, the dimension counted as needed extracted from the first data it is each need corresponding second data of statistical dimension, this
Sample is searched during statistics without first ergodic data library, can directly be counted, be mentioned to data to be processed
The high efficiency of statistics.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Referring to Fig. 6, Fig. 6 is a kind of schematic diagram for data statistics device that one embodiment of the invention provides.Including it is each
Unit is used to execute each step in the corresponding embodiment of FIG. 1 to FIG. 5.Referring specifically to the corresponding embodiment of FIG. 1 to FIG. 5
In associated description.For ease of description, only the parts related to this embodiment are shown.Referring to Fig. 6, data statistics device 6
Include:
Acquiring unit 610 determines the data type of first data for obtaining the first data to be processed；
Determination unit 620, for determining the corresponding statistical dimension of first data according to the data type；
Extraction unit 630, for extracting corresponding second number of each statistical dimension respectively from first data
According to；
Processing unit 640, for the data statistics strategy based on each statistical dimension, each statistical dimension pair
The second data answered are counted, and statistical result is obtained.
Further, acquiring unit 610 is specifically used for:
The first data to be processed are obtained, and obtain the data attribute of first data；
According to the preset corresponding relationship between the data attribute, data attribute and data type of first data, really
The data type of fixed first data.
Further, processing unit 640 includes:
First processing units, for the data statistics strategy based on each statistical dimension, each statistical dimension
Corresponding second data determine the corresponding more new information of each statistical dimension；
The second processing unit, for based on the statistical data in the update information update database.
Further, the second processing unit is specifically used for:
Obtain the label information of corresponding second data of each statistical dimension；
According to the default corresponding relationship between the label information, label information and Database Identification, by each institute
State the corresponding corresponding database of label information for updating information update to second data of statistical dimension.
Further, it is determined that unit 620 is specifically used for:
According to the corresponding relationship of data type and statistical dimension, the corresponding statistics of data type of first data is determined
Dimension obtains the corresponding statistical dimension of first data.
Further, data statistics device further include:
First determination unit, for determining the data of target data to be found when receiving the instruction for searching data
Attribute；
Second determination unit, for determining the target according to the default corresponding relationship between data attribute and database
The corresponding target database of the data attribute of data；
Searching unit, for obtaining the target data from the target database.
Fig. 7 is the schematic diagram for the data statistics terminal that one embodiment of the invention provides.As shown in fig. 7, the number of the embodiment
Terminal 7 includes: processor 70, memory 71 and is stored in the memory 71 and can be on the processor 70 according to statistics
The computer program 72 of operation, such as data statistics program.The processor 70 is realized when executing the computer program 72
State the step in each data statistical approach embodiment, such as step 101 shown in FIG. 1 is to 104.Alternatively, the processor 70
The function of each module/unit in above-mentioned each device is realized when executing the computer program 72.
Illustratively, the computer program 72 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 71, and are executed by the processor 70, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Implementation procedure of the computer program 72 in the data statistics terminal 7 is described.For example, the computer program 72 can be with
It is divided into acquiring unit, determination unit, extraction unit, processing unit, each module concrete function is as follows:
Acquiring unit determines the data type of first data for obtaining the first data to be processed；
Determination unit, for determining the corresponding statistical dimension of first data according to the data type；
Extraction unit, for extracting corresponding second data of each statistical dimension respectively from first data；
Processing unit, it is corresponding for the data statistics strategy based on each statistical dimension, each statistical dimension
The second data counted, obtain statistical result.
The data statistics terminal 7 can be the calculating such as desktop PC, notebook, palm PC and cloud server
Equipment.The data statistics terminal may include, but be not limited only to, processor 70, memory 71.Those skilled in the art can manage
Solution, Fig. 7 is only the example of data statistics terminal 7, does not constitute the restriction to data statistics terminal 7, may include than diagram
More or fewer components perhaps combine certain components or different components, such as the data statistics terminal can also wrap
Include input-output equipment, network access equipment, bus etc..
Alleged processor 70 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 71 can be the internal storage unit of the data statistics terminal 7, such as data statistics terminal 7
Hard disk or memory.The memory 61 is also possible to the External memory equipment of the data statistics terminal 7, such as data system
The plug-in type hard disk being equipped in meter terminal 7, intelligent memory card (Smart Media Card, SMC), secure digital (Secure
Digital, SD) card, flash card (Flash Card) etc..Further, the memory 71 can also both include the data
The internal storage unit for counting terminal 7 also includes External memory equipment.The memory 71 is for storing the computer program
And other programs and data needed for the data statistics terminal.The memory 71 can be also used for temporarily storing
Output or the data that will be exported.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal device and method, it can be with
It realizes by another way.For example, device described above/terminal device embodiment is only schematical, for example, institute
The division of module or unit is stated, only a kind of logical function partition, there may be another division manner in actual implementation, such as
Multiple units or components can be combined or can be integrated into another system, or some features can be ignored or not executed.Separately
A bit, shown or discussed mutual coupling or direct-coupling or communication connection can be through some interfaces, device
Or the INDIRECT COUPLING or communication connection of unit, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..Computer-readable Jie
Matter may include: can carry the computer program code any entity or device, recording medium, USB flash disk, mobile hard disk,
Magnetic disk, CD, computer storage, read-only memory (Read-Only Memory, ROM), random access memory (Random
Access Memory, RAM), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that the meter
The content that calculation machine readable medium includes can carry out increase and decrease appropriate according to the requirement made laws in jurisdiction with patent practice,
It such as does not include electric carrier signal and telecommunications according to legislation and patent practice, computer-readable medium in certain jurisdictions
Signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of data statistical approach characterized by comprising
The first data to be processed are obtained, determine the data type of first data；
The corresponding statistical dimension of first data is determined according to the data type；
Extract corresponding second data of each statistical dimension respectively from first data；
Data statistics strategy based on each statistical dimension, corresponding second data of each statistical dimension are united
Meter, obtains statistical result.
2. data statistical approach as described in claim 1, which is characterized in that it is described to obtain the first data to be processed, it determines
The data type of first data, comprising:
The first data to be processed are obtained, and obtain the data attribute of first data；
According to the preset corresponding relationship between the data attribute, data attribute and data type of first data, institute is determined
State the data type of the first data.
3. data statistical approach as described in claim 1, which is characterized in that the data based on each statistical dimension
It counts corresponding second data of tactful, each statistical dimension to be counted, obtains statistical result, comprising:
Data statistics strategy based on each statistical dimension, corresponding second data of each statistical dimension, determine every
The corresponding more new information of a statistical dimension；
Based on the statistical data in the update information update database.
4. data statistical approach as claimed in claim 3, which is characterized in that described to be based on the update information update database
In statistical data, comprising:
Obtain the label information of corresponding second data of each statistical dimension；
According to the default corresponding relationship between the label information, label information and Database Identification, by each system
Count the corresponding corresponding database of label information for updating information update to second data of dimension.
5. data statistical approach as described in claim 1, which is characterized in that described to determine described according to the data type
The corresponding statistical dimension of one data, comprising:
According to the corresponding relationship of data type and statistical dimension, the corresponding statistics dimension of the data type of first data is determined
Degree, obtains the corresponding statistical dimension of first data.
6. data statistical approach as claimed in claim 4, which is characterized in that further include:
When receiving the instruction for searching data, the data attribute of target data to be found is determined；
According to the default corresponding relationship between data attribute and database, the corresponding mesh of the data attribute of the target data is determined
Mark database；
The target data is obtained from the target database.
7. data statistical approach as described in claim 1, which is characterized in that first data are store order data, institute
The data type for stating the first data is purchase order；
It is described that the corresponding statistical dimension of first data is determined according to the data type, comprising:
According to the purchase order, the corresponding statistical dimension of the purchase order is determined；Wherein, the corresponding system of the purchase order
Meter dimension include the sales volume of trade company, the sales volume of the commodity of purchase, purchase the corresponding production plant of commodity sales volume.
8. a kind of data statistics device characterized by comprising
Acquiring unit determines the data type of first data for obtaining the first data to be processed；
Determination unit, for determining the corresponding statistical dimension of first data according to the data type；
Extraction unit, for extracting corresponding second data of each statistical dimension respectively from first data；
Processing unit, for the data statistics strategy based on each statistical dimension, each statistical dimension corresponding
Two data are counted, and statistical result is obtained.
9. a kind of data statistics terminal, including memory, processor and storage are in the memory and can be in the processing
The computer program run on device, which is characterized in that the processor realizes such as claim 1 when executing the computer program
The step of to any one of 7 the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 7 of realization the method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811300937.5A CN109558462A (en) | 2018-11-02 | 2018-11-02 | Data statistical approach and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811300937.5A CN109558462A (en) | 2018-11-02 | 2018-11-02 | Data statistical approach and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109558462A true CN109558462A (en) | 2019-04-02 |
Family
ID=65865593
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811300937.5A Pending CN109558462A (en) | 2018-11-02 | 2018-11-02 | Data statistical approach and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109558462A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111935279A (en) * | 2020-08-08 | 2020-11-13 | 詹能勇 | Internet of things network maintenance method based on block chain and big data and computing node |
| CN112765673A (en) * | 2021-03-16 | 2021-05-07 | 杭州数梦工场科技有限公司 | Sensitive data statistical method and related device |
| CN113111367A (en) * | 2021-04-28 | 2021-07-13 | 北京天空卫士网络安全技术有限公司 | Security information management method, device and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106156130A (en) * | 2015-04-09 | 2016-11-23 | 阿里巴巴集团控股有限公司 | A kind of data processing method and device |
| CN106649630A (en) * | 2016-12-07 | 2017-05-10 | 乐视控股（北京）有限公司 | Data query method and device |
| WO2017161167A1 (en) * | 2016-03-18 | 2017-09-21 | President And Fellows Of Harvard College | Automatically classifying animal behavior |
| CN108108392A (en) * | 2017-11-23 | 2018-06-01 | 北京百度网讯科技有限公司 | Commodity data management method, device, computer equipment and storage medium |
| CN108132940A (en) * | 2016-12-01 | 2018-06-08 | 北京金山云网络技术有限公司 | A kind of application data extracting method and device |
-
2018
- 2018-11-02 CN CN201811300937.5A patent/CN109558462A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106156130A (en) * | 2015-04-09 | 2016-11-23 | 阿里巴巴集团控股有限公司 | A kind of data processing method and device |
| WO2017161167A1 (en) * | 2016-03-18 | 2017-09-21 | President And Fellows Of Harvard College | Automatically classifying animal behavior |
| CN108132940A (en) * | 2016-12-01 | 2018-06-08 | 北京金山云网络技术有限公司 | A kind of application data extracting method and device |
| CN106649630A (en) * | 2016-12-07 | 2017-05-10 | 乐视控股（北京）有限公司 | Data query method and device |
| CN108108392A (en) * | 2017-11-23 | 2018-06-01 | 北京百度网讯科技有限公司 | Commodity data management method, device, computer equipment and storage medium |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111935279A (en) * | 2020-08-08 | 2020-11-13 | 詹能勇 | Internet of things network maintenance method based on block chain and big data and computing node |
| CN111935279B (en) * | 2020-08-08 | 2021-07-09 | 江苏小梦科技有限公司 | Internet of things network maintenance method based on block chain and big data and computing node |
| CN113285978A (en) * | 2020-08-08 | 2021-08-20 | 詹能勇 | Fault identification method based on block chain and big data and cloud computing platform |
| CN113285978B (en) * | 2020-08-08 | 2022-08-12 | 布洛克(北京)数据科技有限公司 | Fault identification method based on block chain and big data and general computing node |
| CN112765673A (en) * | 2021-03-16 | 2021-05-07 | 杭州数梦工场科技有限公司 | Sensitive data statistical method and related device |
| CN113111367A (en) * | 2021-04-28 | 2021-07-13 | 北京天空卫士网络安全技术有限公司 | Security information management method, device and system |
| CN113111367B (en) * | 2021-04-28 | 2024-08-09 | 北京天空卫士网络安全技术有限公司 | Security information management method, device and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103970761B (en) | A kind of commodity data searching method and device | |
| CN104636429B (en) | Trademark class search method and device | |
| CN109558462A (en) | Data statistical approach and device | |
| CN108388675A (en) | Circulation method and terminal device are drawn in a kind of identity | |
| CN107967284A (en) | Method and apparatus for storing, inquiring about sequence information | |
| CN103136683A (en) | Method and device for calculating product reference price and method and system for searching products | |
| US10878476B2 (en) | Assortment optimization | |
| CN102314654A (en) | Information push method and information push server | |
| CN110245289A (en) | A kind of information search method and relevant device | |
| CN111753210B (en) | Resource pushing method and device, computer equipment and computer readable storage medium | |
| CN112528148B (en) | Resource information display and configuration method and device | |
| CN103970747A (en) | Data processing method for network side computer to order search results | |
| KR20210032691A (en) | Method and apparatus of recommending goods based on network | |
| CN109753504A (en) | Data query method and device | |
| CN116308684A (en) | Online shopping platform store information pushing method and system | |
| CN110851737A (en) | Recommendation method and device, electronic equipment and computer storage medium | |
| CN105677776A (en) | Data processing method and device | |
| AU2015201593A1 (en) | Report generation system and method | |
| CN109450963A (en) | Information push method and terminal device | |
| CN111401959B (en) | Risk group prediction method, apparatus, computer device and storage medium | |
| CN117216344A (en) | Resource type query method, device, computer equipment and storage medium | |
| CN111415168A (en) | Transaction warning method and device | |
| CN112991033A (en) | Method and device for determining value attribute of article | |
| CN108021588B (en) | Integration method and device for user first purchase data facing electronic commerce | |
| CN110427558B (en) | Resource processing event pushing method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190402 |