CN110347698A - Method for processing report data and device - Google Patents
Method for processing report data and device Download PDFInfo
- Publication number
- CN110347698A CN110347698A CN201910639137.4A CN201910639137A CN110347698A CN 110347698 A CN110347698 A CN 110347698A CN 201910639137 A CN201910639137 A CN 201910639137A CN 110347698 A CN110347698 A CN 110347698A
- Authority
- CN
- China
- Prior art keywords
- inquiry
- dimension
- user
- optimal
- preset
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2433—Query languages
- G06F16/244—Grouping and aggregation
Abstract
It includes: to judge whether the inquiry dimension in user's current queries information matches the inquiry dimension preset in optimal polymeric rule that the embodiment of the present application, which provides a kind of method for processing report data and device, method,；If so, obtaining corresponding default report detailed data set according to the inquiry dimension preset in optimal polymeric rule being matched to, obtaining report data corresponding with user's current queries information；The application can be fast and accurately by the current queries information matches of user to presetting optimal polymeric rule accordingly, and then determine the default report detailed data set preset in optimal polymeric rule, to reduce the data volume of process object, alleviate mass data in Flexible Query and handle the performance pressures for caused by database server in real time, to reach good query effect and sustained serviceability.
Description
Technical field
This application involves data processing fields, and in particular to a kind of method for processing report data and device.
Background technique
Report is the basic measures and approach of business administration, is the basic service requirement of enterprise, and implements business intelligence
The basis of strategy.With the iterative method of global economic integration progress, Modern management person more pay close attention to report performance analysis,
For the facilitation of enterprise development in terms of decision support.
Existing reporting system is broadly divided into two classes: fixed reporting system and Flexible Query reporting system.Fixed report system
System dynamically loads report data by defining special structure of report, data structure be all pre-define, it is static,
It can not dynamic change.Flexible Query reporting system then enables report user according to the business rule metadata group of predefined
Structure of report is knitted, auto-associating grouping allows user voluntarily to carry out report definition and the analysis of more bores.
Inventors have found that although the more fixed reporting system of Flexible Query reporting system has embodied " data mobilism ", " lattice
The advantage of formula diversification ", but this flexibility also brings certain negative effect therewith.Since the condition of real-time query is flexible
Changeable, the level of data summarization is had nothing in common with each other, and when Flexible Query demand of the every secondary response user of system requires for magnanimity
Detailed data is handled in real time, to cause huge pressure to the performance of database.Especially initiated simultaneously in multi-user
When big data quantity is inquired, in some instances it may even be possible to lead to short time delay machine, to seriously affect the stability and continuous service energy of system
Power.
Summary of the invention
For the problems of the prior art, the application provides a kind of method for processing report data and device, can quickly, it is quasi-
The true current queries information matches by user to presetting optimal polymeric rule accordingly, and then optimal polymeric rule is preset in determination
In default report detailed data set it is real-time to alleviate mass data in Flexible Query to reduce the data volume of process object
The performance pressures for caused by database server are handled, to reach good query effect and sustained serviceability.
In order to solve the above technical problems, the application the following technical schemes are provided:
In a first aspect, the application provides a kind of method for processing report data, comprising:
Judge whether the inquiry dimension in user's current queries information matches the inquiry dimension preset in optimal polymeric rule；
If so, obtaining corresponding default report according to the inquiry dimension preset in optimal polymeric rule being matched to
Table detailed data set obtains report data corresponding with user's current queries information.
Further, optimal polymerization rule are preset whether the inquiry dimension judged in user's current queries information matches
Before inquiry dimension in then, comprising:
According to the inquiry frequency and inquiry radix for respectively inquiring dimension in user's history query information, each inquiry dimension is obtained
The recommendation of degree；
It is institute by the inquiry dimension set of preset quantity according to the numerical values recited of the recommendation of each inquiry dimension
The inquiry dimension preset in optimal polymeric rule is stated, presets optimal polymeric rule so that determination is described；
Determine default report detailed data set corresponding with the inquiry dimension preset in optimal polymeric rule.
Further, it is described according to respectively inquired in user's history query information under theme the inquiry frequency for respectively inquiring dimension and
Radix is inquired, the recommendation of each inquiry dimension is obtained, comprising:
According to the product of the inquiry frequency and the inquiry radix, the recommendation of each inquiry dimension is obtained.
Further, in the product according to the inquiry frequency and the inquiry radix, each inquiry dimension is obtained
Before the recommendation of degree, comprising:
According to the query categories of the inquiry dimension, determination includes the subquery dimension of the query categories；
According to the inquiry frequency of each subquery dimension and corresponding default professional level weight coefficient, the inquiry dimension is obtained
The inquiry frequency of degree.
Further, whether the inquiry dimension judged in user's current queries information, which matches, is preset optimal polymeric rule
In inquiry dimension, comprising:
Judging inquiry dimension and the inquiry dimension preset in optimal polymeric rule in user's current queries information is
It is no identical.
Further, whether the inquiry dimension judged in user's current queries information, which matches, is preset optimal polymeric rule
In inquiry dimension, comprising:
Judge that query categories that the inquiry dimension in user's current queries information is included optimal polymerize rule with described preset
Whether the query categories that inquiry dimension is included in then are identical；
If they are the same, then it is described pre- to judge whether the condition level of each query categories in user's current queries information is above
If the condition level of each query categories in optimal polymeric rule.
Further, whether the inquiry dimension judged in user's current queries information, which matches, is preset optimal polymeric rule
In inquiry dimension, comprising:
Judge whether the query categories that the inquiry dimension in user's current queries information is included are contained in described preset most
The query categories that dimension is included are inquired in excellent polymeric rule；
If so, it is described default to judge whether the condition level of each query categories in user's current queries information is above
The condition level of each query categories in optimal polymeric rule.
Further, the inquiry dimension preset in optimal polymeric rule that the basis is matched to obtains corresponding
Default report detailed data set, comprising:
To the condition for presetting the inquiry radix, each inquiry dimension of respectively inquiring dimension in optimal polymeric rule being matched to
Level is currently looked into the difference of the condition level of the inquiry dimension in user's current queries information and each inquiry dimension with user
The matching degree progress comprehensive analysis for asking the inquiry dimension in information, determines and described presets inquiry optimal in optimal polymeric rule
Dimension simultaneously obtains corresponding report detailed data set.
Second aspect, the application provide a kind of report data processing unit, comprising:
Polymeric rule matching module, for judge the inquiry dimension in user's current queries information whether match preset it is optimal
Inquiry dimension in polymeric rule；
Report data obtains module, presets optimal gather for working as the inquiry dimension matching judged in user's current queries information
When inquiry dimension in normally, according to the inquiry dimension preset in optimal polymeric rule being matched to, obtain corresponding
Default report detailed data set, obtains report data corresponding with user's current queries information.
Further, further includes:
Dimension recommendation determination unit is inquired, for according to the inquiry frequency for respectively inquiring dimension in user's history query information
With inquiry radix, the recommendation of each inquiry dimension is obtained；
Optimal polymeric rule determination unit will be preset for the numerical values recited according to each recommendation for inquiring dimension
The inquiry dimension set of quantity is the inquiry dimension preset in optimal polymeric rule, presets optimal gather so that determination is described
Normally；
Report detailed data determination unit, it is corresponding with the inquiry dimension preset in optimal polymeric rule for determination
Default report detailed data set.
Further, the inquiry dimension recommendation determination unit includes:
Inquiry dimension recommendation determines subelement, for the product according to the inquiry frequency and the inquiry radix, obtains
To the recommendation of each inquiry dimension.
Further, further includes:
Subquery dimension determination unit, for the query categories according to the inquiry dimension, determination includes the inquiry
The subquery dimension of classification；
Frequency determination unit is inquired, for weighing according to the inquiry frequency of each subquery dimension with corresponding default professional level
Weight coefficient obtains the inquiry frequency of the inquiry dimension.
Further, the polymeric rule matching module includes:
Dimension judging unit, for judging that the inquiry dimension in user's current queries information optimal polymerize rule with described preset
Whether the inquiry dimension in then is identical.
Further, the polymeric rule matching module includes:
First query categories judging unit, the inquiry for being included for judging the inquiry dimension in user's current queries information
Classification presets whether the dimension query categories that are included are inquired in optimal polymeric rule identical with described；
First condition level judging unit, for being looked into when what the inquiry dimension that judge in user's current queries information was included
Ask classification with it is described preset in optimal polymeric rule query categories that inquiry dimension is included it is identical when, further judge that user works as
Whether the condition level of each query categories in preceding query information is above each inquiry class preset in optimal polymeric rule
Other condition level.
Further, the polymeric rule matching module includes:
Second query categories judging unit, the inquiry for being included for judging the inquiry dimension in user's current queries information
Whether classification is contained in described preset and inquires the query categories that dimension is included in optimal polymeric rule；
Second condition level judging unit, for being looked into when what the inquiry dimension that judge in user's current queries information was included
Ask classification be contained in it is described preset in optimal polymeric rule inquire dimension included query categories when, further judge that user works as
Whether the condition level of each query categories in preceding query information is above each inquiry class preset in optimal polymeric rule
Other condition level.
Further, the report data acquisition module includes:
Optimal inquiry dimension determination unit, for respectively inquiring dimension to described preset in optimal polymeric rule being matched to
Inquire the difference of the condition level of radix, the condition level of each inquiry dimension and the inquiry dimension in user's current queries information with
And the matching degree progress comprehensive analysis of each inquiry dimension and the inquiry dimension in user's current queries information, it determines described default
Optimal inquiry dimension and corresponding report detailed data set is obtained in optimal polymeric rule.
The third aspect, the application provides a kind of electronic equipment, including memory, processor and storage are on a memory and can
The computer program run on a processor, the processor realize the method for processing report data when executing described program
The step of.
Fourth aspect, the application provide a kind of computer readable storage medium, are stored thereon with computer program, the calculating
The step of method for processing report data is realized when machine program is executed by processor.
As shown from the above technical solution, the application provides a kind of method for processing report data and device, by user's
Historical query information is analyzed, and has been pre-designed optimal polymeric rule, not only including in the optimal polymeric rule can
The inquiry dimension of user query demand is substantially met, but also includes the corresponding report detailed data collection of the inquiry dimension
It closes, when user carries out inquiry operation, first determines whether the inquiry dimension to be inquired in user's current queries information and preset most
Whether the inquiry dimension in excellent polymeric rule matches, that is, presetting optimal polymeric rule can satisfy the current queries demand of user,
If matching, can directly acquire and preset default report detail number corresponding to the inquiry dimension of successful match in optimal polymeric rule
According to set, alleviate Flexible Query to reduce the data volume of process object without carrying out subsequent report real-time query operation again
Middle mass data handles the performance pressures for caused by database server in real time, to reach good query effect and lasting clothes
Business ability.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is the application
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.
Fig. 1 is one of the flow diagram of method for processing report data in the embodiment of the present application；
Fig. 2 is the two of the flow diagram of the method for processing report data in the embodiment of the present application；
Fig. 3 is the three of the flow diagram of the method for processing report data in the embodiment of the present application；
Fig. 4 is the four of the flow diagram of the method for processing report data in the embodiment of the present application；
Fig. 5 is the five of the flow diagram of the method for processing report data in the embodiment of the present application；
Fig. 6 is one of the structure chart of the report data processing unit in the embodiment of the present application；
Fig. 7 is the two of the structure chart of the report data processing unit in the embodiment of the present application；
Fig. 8 is the three of the structure chart of the report data processing unit in the embodiment of the present application；
Fig. 9 is the four of the structure chart of the report data processing unit in the embodiment of the present application；
Figure 10 is the five of the structure chart of the report data processing unit in the embodiment of the present application；
Figure 11 is the six of the structure chart of the report data processing unit in the embodiment of the present application；
Figure 12 is the seven of the structure chart of the report data processing unit in the embodiment of the present application；
Figure 13 is the eight of the structure chart of the report data processing unit in the embodiment of the present application；
Figure 14 is the structural schematic diagram of the electronic equipment in the embodiment of the present application.
Specific embodiment
To keep the purposes, technical schemes and advantages of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, technical solutions in the embodiments of the present application carries out clear, complete description, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
Every other embodiment obtained without creative efforts, shall fall in the protection scope of this application.
In view of the condition of real-time query in the prior art is flexible and changeable, the level of data summarization is had nothing in common with each other, and system is every
It requires to handle the detailed data of magnanimity in real time when the Flexible Query demand of secondary response user, thus to database
Performance causes huge pressure.Especially when multi-user initiates big data quantity inquiry simultaneously, in some instances it may even be possible to the short time be caused to be delayed
Machine, thus the problem of having seriously affected the stability and sustained serviceability of system, the application provides a kind of report data processing
Method and device is analyzed by the historical query information to user, has been pre-designed optimal polymeric rule, described optimal poly-
Not only include that can substantially meet the inquiry dimension of user query demand in normally, but also includes the inquiry dimension
Corresponding report detailed data set first determines whether to be looked into user's current queries information when user carries out inquiry operation
Whether the inquiry dimension of inquiry matches with the inquiry dimension preset in optimal polymeric rule, that is, presetting optimal polymeric rule can satisfy
The current queries demand of user, if matching, can directly acquire the inquiry dimension institute for presetting successful match in optimal polymeric rule
Corresponding default report detailed data set, without carrying out subsequent report real-time query operation again, to reduce process object
Data volume, alleviate Flexible Query in mass data handle the performance pressures for caused by database server in real time, to reach
Good query effect and sustained serviceability.
In order to fast and accurately by the current queries information matches of user to presetting optimal polymeric rule accordingly,
And then determine the default report detailed data set preset in optimal polymeric rule, to reduce the data volume of process object, delay
Mass data handles the performance pressures for caused by database server in real time in solution Flexible Query, to reach good inquiry effect
Fruit and sustained serviceability, the application provide a kind of embodiment of method for processing report data, referring to Fig. 1, the report data
Processing method specifically includes following content:
Step S101: judge whether the inquiry dimension in user's current queries information matches and preset in optimal polymeric rule
Inquire dimension.
It is understood that the inquiry dimension be subject to enterprise practical service conditions it is preset at least one need
The query categories to be inquired composition, such as an inquiry dimension are " date terms-area condition-product condition-industry level ",
It wherein include 4 different query categories " date terms ", " regional condition ", " product condition " and " industry level ", tool
Body, every kind of query categories can also have different condition levels, for example, the condition level of date terms is defined as: 1-,
The 2- first half of the year, 3- season, the 4- month, 5- days；The condition level of regional condition is defined as: the home and abroad 1-, the western part 2- east, 3- are saved
Or municipality directly under the Central Government, the county 4-；Product condition can be with for providing a loan is defined as: 1- loan types, 2- loan transaction type, 3- loan hair
Put type；Industry level can be with by taking financial circles as an example is defined as: 1- securities broker company, 2- bank, 3- financing enterprise.
It is understood that described preset optimal polymeric rule by according to analyze to the historical query information of user
Arrive at least one recommend inquiry dimension composition, and it is each preset optimal polymeric rule with one inquire theme it is corresponding, wherein institute
It states inquiry theme and is subject to the enterprise practical scope of business and set, for example including deposit, loan, bill, bond, financing etc..
It is understood that by the known inquiry dimension preset optimal polymeric rule and included, it can be further
Ground obtains corresponding report detailed data collection according to the inquiry dimension from database in advance and is merged into row individually storage, to pass through
The current queries demand of the preset report detailed data set quick response user.
Step S102 is obtained and is corresponded to if so, according to the inquiry dimension preset in optimal polymeric rule being matched to
Default report detailed data set, obtain report data corresponding with user's current queries information.
It is understood that when receiving the current queries information of user, by judging in user's current queries information
Inquiry dimension whether match the inquiry dimension preset in optimal polymeric rule, preset in optimal polymeric rule and deposit in advance with judgement
The report detailed data set of storage can satisfy the current queries demand of user, and is only capable of in the prior art by user's current queries
Information goes in database to carry out complete inquiry operation difference, if presetting optimal polymeric rule in technical solution provided by the present application
In pre-stored report detailed data set can satisfy the current queries demand of user, then no longer go to have executed in database
Whole inquiry operation can directly acquire corresponding default report detailed data set, and then generate and currently look into the user
Ask the corresponding report data of information.
Optionally, after getting corresponding default report detailed data set, if the default report detailed data set
User's current queries demand (such as data structure is different, data integrity degree is inadequate) can not be fully met, then it can be to described pre-
If report detailed data set carries out further data processing, its data structure is adjusted, or bright from default report described in other
Fetching portion data to be in thin data acquisition system to make up the deficiency of data integrity degree, until meeting user's current queries demand and being
Only.
As can be seen from the above description, method for processing report data provided by the embodiments of the present application, it can be by being gone through to user
History query information is analyzed, and has been pre-designed optimal polymeric rule, not only including in the optimal polymeric rule being capable of base
This meets the inquiry dimension of user query demand, but also includes the corresponding report detailed data set of the inquiry dimension,
When user carries out inquiry operation, first determines whether the inquiry dimension to be inquired in user's current queries information and preset optimal poly-
Whether the inquiry dimension in normally matches, that is, presetting optimal polymeric rule can satisfy the current queries demand of user, if
Match, then can directly acquire and preset default report detailed data collection corresponding to the inquiry dimension of successful match in optimal polymeric rule
It closes, without carrying out subsequent report real-time query operation again, to reduce the data volume of process object, alleviates sea in Flexible Query
Generating date performance pressures for caused by database server are measured, to reach good query effect and continuous service energy
Power.
In order to analyze by the historical query information to user, optimal polymeric rule is predefined, in this Shen
It can also specifically include according to user's history before step S101 in one embodiment of method for processing report data please
Query information determines the step of optimal polymeric rule, and referring to fig. 2, which specifically includes following content:
Step S201: it according to the inquiry frequency and inquiry radix for respectively inquiring dimension in user's history query information, obtains each
The recommendation of the inquiry dimension.
Step S202: according to the numerical values recited of the recommendation of each inquiry dimension, the inquiry of preset quantity is tieed up
Degree is set as the inquiry dimension preset in optimal polymeric rule, presets optimal polymeric rule so that determination is described.
Step S203: default report detailed data corresponding with the inquiry dimension preset in optimal polymeric rule is determined
Set.
It, can be with it is understood that when determining described preset in optimal polymeric rule specifically comprising which inquiry dimension
It is determined by the height of the recommendation of each inquiry dimension, the calculating of the recommendation of each inquiry dimension can be for according to root
It is acquired according to the product of the inquiry frequency and inquiry radix of respectively inquiring dimension in user's history query information.
It is understood that the inquiry frequency is in predetermined period, the ad hoc inquiry dimension under ad hoc inquiry theme goes out
Existing number；The inquiry radix is the number of data that the ad hoc inquiry dimension under ad hoc inquiry theme is confined in predetermined period,
That is the item number of query result that can be obtained from database of the inquiry dimension.
Optionally, after the recommendation for obtaining each inquiry dimension, the inquiry of the higher preset quantity of recommendation can be tieed up
Degree is set as the inquiry dimension under the inquiry theme included in corresponding preset polymerization rule, that is, determined it is described preset it is optimal poly-
Normally, further, it is bright can be obtained according to the inquiry dimension preset in optimal polymeric rule for corresponding default report
Thin data acquisition system simultaneously stores.
Dimension is inquired included in optimal polymeric rule in order to determine to preset, is handled in the report data of the application
It can also specifically include the step of calculating the recommendation of each inquiry dimension, which specifically includes in one embodiment of method
There is following content: according to the product of the inquiry frequency and the inquiry radix, obtaining the recommendation of each inquiry dimension.
It, can be with it is understood that when determining described preset in optimal polymeric rule specifically comprising which inquiry dimension
It is determined by the height of the recommendation of each inquiry dimension, the calculating of the recommendation of each inquiry dimension can be for according to root
It is acquired according to the product of the inquiry frequency and inquiry radix of respectively inquiring dimension in user's history query information, such as an inquiry dimension
Inquiring frequency is 400, and corresponding inquiry radix is 200, then the recommendation of the inquiry dimension can be 400 × 200=
80000。
Optimal polymeric rule is more intelligent and humanized in order to making to preset, in the report data processing side of the application
It can also specifically include with reference to user's professional level before the recommendation of above-mentioned calculating inquiry dimension in one embodiment of method
The step of significance level is to be weighed, referring to Fig. 3, which specifically includes following content:
Step S301: according to the query categories of the inquiry dimension, determination includes the subquery dimension of the query categories
Degree.
Optionally, before executing step S301, data prediction can be carried out to user's history query information, specifically
Ground calculates incoherent information, such as user name with the inquiry dimension of step S301 firstly, rejecting in user's history query information
The information such as title, department and Query Dates only retain the inquiry theme in user's history query information, user academic title's rank, inquire
The inquiry times (the i.e. described inquiry frequency) of dimension, corresponding inquiry dimension.
Then, classification remittance is carried out to the inquiry times of user according to inquiry theme, user academic title's rank and inquiry dimension
It always and stores, storage organization is as shown in 1 summarized results table of table:
1 summarized results table of table
Step S302: it according to the inquiry frequency of each subquery dimension and corresponding default professional level weight coefficient, obtains
The inquiry frequency of the inquiry dimension.
Specifically, firstly, being split as the inquiry dimension under each inquiry theme to form the one-dimensional set of multielement, shaped like
[Dimday,Dimdistrict,Dimindustry].It then, is the subset of other inquiry dimensions for partial query dimension
Situation, the inquiry frequency frequency original with its own that superset need to be closed to all subsets are summed, to show that superset closes new
Inquiry frequency, for example, [Dimday, Dimdistrict, Dimindustry, Dimrepaytype] include [Dimday,
Dimdistrict, Dimindustry] and all nonvoid subset collection such as [Dimday, Dimrepaytype, Dimdistrinct]
All elements in conjunction, so the inquiry frequency of [Dimday, Dimdistrict, Dimindustry, Dimrepaytype] is answered
This for itself inquiry frequency add included [Dimday, Dimdistrict, Dimindustry] and [Dimday,
Dimrepaytype, Dimdistrinct] etc. all non-empty subsets inquiry frequency, specifically can refer to following formula:
In above-mentioned formula, Freq ([Dimday, Dimdistrict, Dimindustry, Dimrepaytype]) expression is looked into
Ask the inquiry frequency that collection is combined into each user academic title's rank of [Dimday, Dimdistrict, Dimindustry, Dimrepaytype]
Angle value, Freq_new ([Dimday, Dimdistrict, Dimindustry, Dimrepaytype]) indicate that query set is
The frequency of the nonvoid subset of [Dimday, Dimdistrict, Dimindustry, Dimrepaytype] adds according to user academic title's grade
Aggregate-value after power is total, wherein f (i) is the weight coefficient that i-th class user academic title's rank represents, andIt can be with
Understand, the setting of above-mentioned weight coefficient be in order to determine preset optimal polymeric rule when, can be according to active user's duty
The significance level of grade is weighed, and keeps the result of decision more intelligent, humanized, which can be according to enterprise practical professional level
Situation is preset.
In order to accurately and rapidly be matched to user's current queries information with optimal polymeric rule, in the application
Method for processing report data an embodiment in, can also specifically include matched to carry out according to the inquiry dimension of the two
Step, which specifically includes following content: judge inquiry dimension in user's current queries information with it is described preset it is optimal
Whether the inquiry dimension in polymeric rule is identical.
It is understood that judging that the inquiry dimension in user's current queries information is preset in optimal polymeric rule with described
Inquiry dimension it is whether identical, if they are the same, then both can determine that successful match.
In order to accurately and rapidly be matched to user's current queries information with optimal polymeric rule, in the application
Method for processing report data an embodiment in, can also specifically include according to inquiry dimension query categories and condition layer
Grade carries out matched step, and referring to fig. 4, which specifically includes following content:
Step S401: judge that the query categories that the inquiry dimension in user's current queries information is included are preset most with described
It is whether identical that the query categories that dimension is included are inquired in excellent polymeric rule.
Step S402: if they are the same, then judge whether the condition level of each query categories in user's current queries information is equal
Higher than the condition level for presetting each query categories in optimal polymeric rule.
It is understood that condition level represents the granularity that summarizes of data, for example, date dimension have per diem, the moon, season, half
Year, the granularity or level in year, per diem stored if preset in optimal polymeric rule, when inquiry can summarize out monthly
Data monthly store if preset in optimal polymeric rule, the data that cannot be per diem inquired, therefore, if
The query categories and described preset in optimal polymeric rule that inquiry dimension in user's current queries information is included inquire dimension
The query categories for being included are completely the same, and the condition level of each query categories in user's current queries information be above it is described
The condition level for presetting each query categories in optimal polymeric rule then can determine that the two successful match.
In order to accurately and rapidly be matched to user's current queries information with optimal polymeric rule, in the application
Method for processing report data another embodiment in, can also specifically include according to inquiry dimension query categories and condition
The step of level is matched, referring to Fig. 5, which specifically includes following content:
Step S501: whether the query categories for judging that the inquiry dimension in user's current queries information is included are contained in institute
It states to preset and inquires the query categories that dimension is included in optimal polymeric rule.
Step S502: if so, judging whether the condition level of each query categories in user's current queries information is high
In the condition level for presetting each query categories in optimal polymeric rule.
It is understood that if the query categories that the inquiry dimension in user's current queries information is included be contained in state it is pre-
If inquiring the query categories that dimension is included in optimal polymeric rule, and the item of each query categories in user's current queries information
Whether part level is above the condition level for presetting each query categories in optimal polymeric rule, then can determine that the two matching
Success.
In order to determine an optimal inquiry dimension from multiple inquiry dimensions being matched to, in the report of the application
In one embodiment of data processing method, can also specifically include from many aspects to each inquiry dimension carry out comprehensive analysis with
The step of determining an optimal inquiry dimension, which specifically includes following content: to be matched to it is described preset it is optimal
The inquiry radix of dimension, the condition level of each inquiry dimension and the inquiry in user's current queries information are respectively inquired in polymeric rule
The matching degree of the difference of the condition level of dimension and each inquiry dimension and the inquiry dimension in user's current queries information into
Row comprehensive analysis determines and described preset inquiry dimension optimal in optimal polymeric rule and obtain corresponding report detailed data collection
It closes.
It is understood that due to providing multiple specifically matching rules, user's current queries in above-mentioned steps
Inquiry dimension in information can be matched at least one and preset the inquiry dimension in optimal polymeric rule, in order to from multiple
An optimal inquiry dimension is determined in the inquiry dimension being matched to, and is taken this as the standard and obtained corresponding default report detailed data
Set, to meet the current queries demand of user conscientiously, can respectively inquire described preset in optimal polymeric rule being matched to
The condition level of the inquiry radix of dimension, the condition level of each inquiry dimension and the inquiry dimension in user's current queries information
The matching degree of difference and each inquiry dimension and the inquiry dimension in user's current queries information carries out comprehensive analysis, will match
Each inquiry dimension arrived is respectively according to the size of inquiry radix, the size of condition level difference and the matching degree for inquiring dimension
Carry out sequence sequence, and then determine the size, the size of condition level difference and the matching degree for inquiring dimension of inquiry radix
All preferably one inquiry dimension, and set it to optimal inquiry dimension.
In order to fast and accurately by the current queries information matches of user to presetting optimal polymeric rule accordingly,
And then determine the default report detailed data set preset in optimal polymeric rule, to reduce the data volume of process object, delay
Mass data handles the performance pressures for caused by database server in real time in solution Flexible Query, to reach good inquiry effect
Fruit and sustained serviceability, the application provide a kind of all or part of the content for realizing the method for processing report data
The embodiment of report data processing unit, referring to Fig. 6, the report data processing unit specifically includes following content:
Polymeric rule matching module 10 is preset most for judging whether the inquiry dimension in user's current queries information matches
Inquiry dimension in excellent polymeric rule.
Report data obtains module 20, and the inquiry dimension matching for that ought judge in user's current queries information is preset optimal
When inquiry dimension in polymeric rule, according to the inquiry dimension preset in optimal polymeric rule being matched to, obtains and correspond to
Default report detailed data set, obtain report data corresponding with user's current queries information.
As can be seen from the above description, report data processing unit provided by the embodiments of the present application, it can be by being gone through to user
History query information is analyzed, and has been pre-designed optimal polymeric rule, not only including in the optimal polymeric rule being capable of base
This meets the inquiry dimension of user query demand, but also includes the corresponding report detailed data set of the inquiry dimension,
When user carries out inquiry operation, first determines whether the inquiry dimension to be inquired in user's current queries information and preset optimal poly-
Whether the inquiry dimension in normally matches, that is, presetting optimal polymeric rule can satisfy the current queries demand of user, if
Match, then can directly acquire and preset default report detailed data collection corresponding to the inquiry dimension of successful match in optimal polymeric rule
It closes, without carrying out subsequent report real-time query operation again, to reduce the data volume of process object, alleviates sea in Flexible Query
Generating date performance pressures for caused by database server are measured, to reach good query effect and continuous service energy
Power.
In order to analyze by the historical query information to user, optimal polymeric rule is predefined, in this Shen
Also specifically include following content referring to Fig. 7 in one embodiment of report data processing unit please:
Dimension recommendation determination unit 31 is inquired, for according to the inquiry frequency for respectively inquiring dimension in user's history query information
Degree and inquiry radix obtain the recommendation of each inquiry dimension.
Optimal polymeric rule determination unit 32 will be pre- for the numerical values recited according to each recommendation for inquiring dimension
If the inquiry dimension set of quantity be the inquiry dimension preset in optimal polymeric rule, with determination it is described preset it is optimal
Polymeric rule.
Report detailed data determination unit 33, it is corresponding with the inquiry dimension preset in optimal polymeric rule for determination
Default report detailed data set.
Dimension is inquired included in optimal polymeric rule in order to determine to preset, is handled in the report data of the application
In one embodiment of device, referring to Fig. 8, the inquiry dimension recommendation determination unit 31 includes:
Inquiry dimension recommendation determines subelement 311, for inquiring frequency and the product for inquiring radix according to described,
Obtain the recommendation of each inquiry dimension.
Optimal polymeric rule is more intelligent and humanized in order to making to preset, and handles dress in the report data of the application
Also specifically include following content referring to Fig. 9 in the embodiment set:
Subquery dimension determination unit 41, for the query categories according to the inquiry dimension, determination includes described looks into
Ask the subquery dimension of classification.
Frequency determination unit 42 is inquired, for according to the inquiry frequency of each subquery dimension and corresponding default professional level
Weight coefficient obtains the inquiry frequency of the inquiry dimension.
In order to accurately and rapidly be matched to user's current queries information with optimal polymeric rule, in the application
Report data processing unit an embodiment in, referring to Figure 10, the polymeric rule matching module 10 includes:
Dimension judging unit 11, for judging that the inquiry dimension in user's current queries information presets optimal polymerize with described
Whether the inquiry dimension in rule is identical.
In order to accurately and rapidly be matched to user's current queries information with optimal polymeric rule, in the application
Report data processing unit an embodiment in, referring to Figure 11, the polymeric rule matching module 10 includes:
First query categories judging unit 12, for judging that the inquiry dimension in user's current queries information included looks into
It askes classification and whether described to preset in optimal polymeric rule the query categories that inquiry dimension is included identical.
First condition level judging unit 13 judges that the inquiry dimension in user's current queries information is included for working as
Query categories with it is described preset inquired in optimal polymeric rule the dimension query categories that are included it is identical when, further judge user
Whether the condition level of each query categories in current queries information is above each inquiry preset in optimal polymeric rule
The condition level of classification.
In order to accurately and rapidly be matched to user's current queries information with optimal polymeric rule, in the application
Report data processing unit an embodiment in, referring to Figure 12, the polymeric rule matching module 10 includes:
Second query categories judging unit 14, for judging that the inquiry dimension in user's current queries information included looks into
Whether inquiry classification is contained in described preset and inquires the query categories that dimension is included in optimal polymeric rule.
Second condition level judging unit 15 judges that the inquiry dimension in user's current queries information is included for working as
Query categories be contained in it is described preset in optimal polymeric rule inquire dimension included query categories when, further judge user
Whether the condition level of each query categories in current queries information is above each inquiry preset in optimal polymeric rule
The condition level of classification.
In order to determine an optimal inquiry dimension from multiple inquiry dimensions being matched to, in the report of the application
In one embodiment of data processing equipment, referring to Figure 13, the report data obtains module 20 and includes:
Optimal inquiry dimension determination unit 21, for respectively inquiring dimension to described preset in optimal polymeric rule being matched to
Inquiry radix, each inquiry dimension condition level and the inquiry dimension in user's current queries information condition level difference
And the matching degree progress comprehensive analysis of each inquiry dimension and the inquiry dimension in user's current queries information, it determines described pre-
If optimal inquiry dimension and obtaining corresponding report detailed data set in optimal polymeric rule.
In order to further explain this programme, the application also provides a kind of above-mentioned report data processing unit realization report of application
The specific application example of table data processing method, specifically includes following content:
Step 1: report accesses transacter and all optional base data table information is presented in interaction page confession
User selects (the report theme of inquiry, alternative inquiry dimension and corresponding level etc.).User completes input pointer category
Property information after, report access transacter transfer data to user query pretreatment unit.
Step 2: user query pretreatment unit accesses the aggregation information table judgement of report polymer layer time generating means maintenance
Whether query set hits polymerization set, i.e., is inquired if appropriate for using Aggregation Table mode.
Step 3: if 2 judging result of above-mentioned steps is hit, by Aggregation Table query processing, user query pretreatment dress
It sets and chooses most suitable Aggregation Table generation strategy, dynamic adjustment is carried out to query argument, object, obtains query result, and transmit
To report generation device；
Step 4: if 2 judging result of above-mentioned steps is to be not hit by, by detailed data query processing, obtaining inquiry knot
Fruit, and it is transmitted to report generation device.
Step 5: data are assembled into report to report generation device and back pass shows to client.
Embodiments herein also provides Overall Steps in the method for processing report data that can be realized in above-described embodiment
A kind of electronic equipment specific embodiment, referring to Figure 14, sub- equipment specifically includes following content:
Processor (processor) 601, memory (memory) 602, communication interface (Communications
Interface) 603 and bus 604；
Wherein, the processor 601, memory 602, communication interface 603 complete mutual lead to by the bus 604
Letter；The communication interface 603 is for realizing report data processing unit, online operation system, client device and other ginsengs
Information transmission between mechanism；
The processor 601 is used to call the computer program in the memory 602, and the processor executes the meter
The Overall Steps in the method for processing report data in above-described embodiment are realized when calculation machine program, for example, the processor executes
Following step is realized when the computer program:
Step S101: judge whether the inquiry dimension in user's current queries information matches and preset in optimal polymeric rule
Inquire dimension.
Step S102 is obtained and is corresponded to if so, according to the inquiry dimension preset in optimal polymeric rule being matched to
Default report detailed data set, obtain report data corresponding with user's current queries information.
As can be seen from the above description, electronic equipment provided by the embodiments of the present application, can be believed by the historical query to user
Breath is analyzed, and has been pre-designed optimal polymeric rule, has not only been included that can substantially meet use in the optimal polymeric rule
The inquiry dimension of family query demand, but also include the corresponding report detailed data set of the inquiry dimension, when user into
When row inquiry operation, first determines whether the inquiry dimension to be inquired in user's current queries information and preset in optimal polymeric rule
Inquiry dimension whether match, that is, presetting optimal polymeric rule can satisfy the current queries demand of user, if matching, can be straight
It obtains to take and presets default report detailed data set corresponding to the inquiry dimension of successful match in optimal polymeric rule, without
Subsequent report real-time query operation is carried out again, to reduce the data volume of process object, it is real to alleviate mass data in Flexible Query
When handle the performance pressures for caused by database server, to reach good query effect and sustained serviceability.
Embodiments herein also provides Overall Steps in the method for processing report data that can be realized in above-described embodiment
A kind of computer readable storage medium, be stored with computer program on the computer readable storage medium, the computer journey
The Overall Steps of the method for processing report data in above-described embodiment are realized when sequence is executed by processor, for example, the processor
Following step is realized when executing the computer program:
Step S101: judge whether the inquiry dimension in user's current queries information matches and preset in optimal polymeric rule
Inquire dimension.
Step S102 is obtained and is corresponded to if so, according to the inquiry dimension preset in optimal polymeric rule being matched to
Default report detailed data set, obtain report data corresponding with user's current queries information.
As can be seen from the above description, computer readable storage medium provided by the embodiments of the present application, it can be by user's
Historical query information is analyzed, and has been pre-designed optimal polymeric rule, not only including in the optimal polymeric rule can
The inquiry dimension of user query demand is substantially met, but also includes the corresponding report detailed data collection of the inquiry dimension
It closes, when user carries out inquiry operation, first determines whether the inquiry dimension to be inquired in user's current queries information and preset most
Whether the inquiry dimension in excellent polymeric rule matches, that is, presetting optimal polymeric rule can satisfy the current queries demand of user,
If matching, can directly acquire and preset default report detail number corresponding to the inquiry dimension of successful match in optimal polymeric rule
According to set, alleviate Flexible Query to reduce the data volume of process object without carrying out subsequent report real-time query operation again
Middle mass data handles the performance pressures for caused by database server in real time, to reach good query effect and lasting clothes
Business ability.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for hardware+
For program class embodiment, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to side
The part of method embodiment illustrates.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the movement recorded in detail in the claims or step can be come according to the sequence being different from embodiment
It executes and desired result still may be implemented.In addition, process depicted in the drawing not necessarily require show it is specific suitable
Sequence or consecutive order are just able to achieve desired result.In some embodiments, multitasking and parallel processing be also can
With or may be advantageous.
Although this application provides the method operating procedure as described in embodiment or flow chart, based on conventional or noninvasive
The labour for the property made may include more or less operating procedure.The step of enumerating in embodiment sequence is only numerous steps
One of execution sequence mode, does not represent and unique executes sequence.It, can when device or client production in practice executes
To execute or parallel execute (such as at parallel processor or multithreading according to embodiment or method shown in the drawings sequence
The environment of reason).
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.It is a kind of typically to realize that equipment is computer.Specifically, computer for example may be used
Think personal computer, laptop computer, vehicle-mounted human-computer interaction device, cellular phone, camera phone, smart phone, individual
Digital assistants, media player, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or
The combination of any equipment in these equipment of person.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It will be understood by those skilled in the art that the embodiment of this specification can provide as the production of method, system or computer program
Product.Therefore, in terms of this specification embodiment can be used complete hardware embodiment, complete software embodiment or combine software and hardware
Embodiment form.
This specification embodiment can describe in the general context of computer-executable instructions executed by a computer,
Such as program module.Generally, program module includes routines performing specific tasks or implementing specific abstract data types, journey
Sequence, object, component, data structure etc..This specification embodiment can also be practiced in a distributed computing environment, in these points
Cloth calculates in environment, by executing task by the connected remote processing devices of communication network.In distributed computing ring
In border, program module can be located in the local and remote computer storage media including storage equipment.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ",
The description of " specific example " or " some examples " etc. means specific features described in conjunction with this embodiment or example, structure, material
Or feature is contained at least one embodiment or example of this specification embodiment.In the present specification, to above-mentioned term
Schematic representation be necessarily directed to identical embodiment or example.Moreover, description specific features, structure, material or
Person's feature may be combined in any suitable manner in any one or more of the embodiments or examples.In addition, in not conflicting feelings
Under condition, those skilled in the art by different embodiments or examples described in this specification and different embodiment or can show
The feature of example is combined.
The foregoing is merely the embodiments of this specification, are not limited to this specification embodiment.For ability
For field technique personnel, this specification embodiment can have various modifications and variations.It is all this specification embodiment spirit and
Any modification, equivalent replacement, improvement and so within principle should be included in the scope of the claims of this specification embodiment
Within.
Claims (18)
1. a kind of method for processing report data, which is characterized in that the described method includes:
Judge whether the inquiry dimension in user's current queries information matches the inquiry dimension preset in optimal polymeric rule；
If so, it is bright to obtain corresponding default report according to the inquiry dimension preset in optimal polymeric rule being matched to
Thin data acquisition system obtains report data corresponding with user's current queries information.
2. method for processing report data according to claim 1, which is characterized in that believe in judgement user's current queries
Whether the inquiry dimension in breath matches before the inquiry dimension preset in optimal polymeric rule, comprising:
According to the inquiry frequency and inquiry radix for respectively inquiring dimension in user's history query information, each inquiry dimension is obtained
Recommendation；
It is described pre- by the inquiry dimension set of preset quantity according to the numerical values recited of the recommendation of each inquiry dimension
If the inquiry dimension in optimal polymeric rule, optimal polymeric rule is preset so that determination is described；
Determine default report detailed data set corresponding with the inquiry dimension preset in optimal polymeric rule.
3. method for processing report data according to claim 2, which is characterized in that described according to user's history query information
In respectively inquire under theme respectively inquire dimension inquiry frequency and inquiry radix, obtain it is each it is described inquiry dimension recommendation, comprising:
According to the product of the inquiry frequency and the inquiry radix, the recommendation of each inquiry dimension is obtained.
4. method for processing report data according to claim 3, which is characterized in that it is described according to the inquiry frequency and
It is described inquiry radix product, obtain it is each it is described inquiry dimension recommendation before, comprising:
According to the query categories of the inquiry dimension, determination includes the subquery dimension of the query categories；
According to the inquiry frequency of each subquery dimension and corresponding default professional level weight coefficient, the inquiry dimension is obtained
Inquire frequency.
5. method for processing report data according to claim 1, which is characterized in that the judgement user current queries information
In inquiry dimension whether match the inquiry dimension preset in optimal polymeric rule, comprising:
Judge inquiry dimension in user's current queries information and the inquiry dimension preset in optimal polymeric rule whether phase
Together.
6. method for processing report data according to claim 1, which is characterized in that the judgement user current queries information
In inquiry dimension whether match the inquiry dimension preset in optimal polymeric rule, comprising:
Judge that the query categories that the inquiry dimension in user's current queries information is included are preset in optimal polymeric rule with described
Whether the query categories that inquiry dimension is included are identical；
If they are the same, then judge whether the condition level of each query categories in user's current queries information is above described preset most
The condition level of each query categories in excellent polymeric rule.
7. method for processing report data according to claim 1, which is characterized in that the judgement user current queries information
In inquiry dimension whether match the inquiry dimension preset in optimal polymeric rule, comprising:
Judge query categories that the inquiry dimension in user's current queries information is included whether be contained in it is described preset it is optimal poly-
The query categories that inquiry dimension is included in normally；
If so, judge the condition level of each query categories in user's current queries information whether be above it is described preset it is optimal
The condition level of each query categories in polymeric rule.
8. method for processing report data according to claim 1, which is characterized in that the basis is matched to described default
Inquiry dimension in optimal polymeric rule obtains corresponding default report detailed data set, comprising:
To the condition level for presetting the inquiry radix, each inquiry dimension of respectively inquiring dimension in optimal polymeric rule being matched to
Believe with the difference of the condition level of the inquiry dimension in user's current queries information and each inquiry dimension and user's current queries
The matching degree of inquiry dimension in breath carries out comprehensive analysis, determines and described presets inquiry dimension optimal in optimal polymeric rule
And obtain corresponding report detailed data set.
9. a kind of report data processing unit characterized by comprising
Polymeric rule matching module presets optimal polymerization for judging whether the inquiry dimension in user's current queries information matches
Inquiry dimension in rule；
Report data obtains module, presets optimal polymerization rule for working as the inquiry dimension matching judged in user's current queries information
When inquiry dimension in then, according to the inquiry dimension preset in optimal polymeric rule being matched to, obtain corresponding default
Report detailed data set obtains report data corresponding with user's current queries information.
10. report data processing unit according to claim 9, which is characterized in that further include:
Inquire dimension recommendation determination unit, for according to respectively inquired in user's history query information dimension inquiry frequency and look into
Radix is ask, the recommendation of each inquiry dimension is obtained；
Optimal polymeric rule determination unit, for the numerical values recited according to each recommendation for inquiring dimension, by preset quantity
The inquiry dimension set be the inquiry dimension preset in optimal polymeric rule, preset optimal polymerization with determination is described and advise
Then；
Report detailed data determination unit, it is corresponding with the inquiry dimension preset in optimal polymeric rule default for determining
Report detailed data set.
11. report data processing unit according to claim 9, which is characterized in that the inquiry dimension recommendation determines
Unit includes:
Inquiry dimension recommendation determines subelement, for the product according to the inquiry frequency and the inquiry radix, obtains each
The recommendation of the inquiry dimension.
12. report data processing unit according to claim 11, which is characterized in that further include:
Subquery dimension determination unit, for the query categories according to the inquiry dimension, determination includes the query categories
Subquery dimension；
Frequency determination unit is inquired, for according to the inquiry frequency of each subquery dimension and corresponding default professional level weight system
Number obtains the inquiry frequency of the inquiry dimension.
13. report data processing unit according to claim 9, which is characterized in that the polymeric rule matching module packet
It includes:
Dimension judging unit, for judging that the inquiry dimension in user's current queries information is preset in optimal polymeric rule with described
Inquiry dimension it is whether identical.
14. report data processing unit according to claim 9, which is characterized in that the polymeric rule matching module packet
It includes:
First query categories judging unit, the query categories for being included for judging the inquiry dimension in user's current queries information
Preset whether the dimension query categories that are included are inquired in optimal polymeric rule identical with described；
First condition level judging unit, for when the inquiry class for judging that the inquiry dimension in user's current queries information is included
Not with it is described preset inquired in optimal polymeric rule the dimension query categories that are included it is identical when, further judge that user currently looks into
Whether the condition level for asking each query categories in information is above each query categories preset in optimal polymeric rule
Condition level.
15. report data processing unit according to claim 9, which is characterized in that the polymeric rule matching module packet
It includes:
Second query categories judging unit, the query categories for being included for judging the inquiry dimension in user's current queries information
Whether it is contained in described preset and inquires the query categories that dimension is included in optimal polymeric rule；
Second condition level judging unit, for when the inquiry class for judging that the inquiry dimension in user's current queries information is included
Be not contained in it is described preset in optimal polymeric rule inquire dimension included query categories when, further judge that user currently looks into
Whether the condition level for asking each query categories in information is above each query categories preset in optimal polymeric rule
Condition level.
16. report data processing unit according to claim 9, which is characterized in that the report data obtains module packet
It includes:
Optimal inquiry dimension determination unit, for respectively inquiring the inquiry of dimension in optimal polymeric rule to described preset being matched to
Radix, the condition level of each inquiry dimension are with the difference of the condition level of the inquiry dimension in user's current queries information and respectively
The matching degree progress comprehensive analysis for inquiring the inquiry dimension in dimension and user's current queries information, determine it is described preset it is optimal
Optimal inquiry dimension and corresponding report detailed data set is obtained in polymeric rule.
17. a kind of electronic equipment including memory, processor and stores the calculating that can be run on a memory and on a processor
Machine program, which is characterized in that the processor realizes the described in any item report numbers of claim 1 to 8 when executing described program
The step of according to processing method.
18. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program quilt
The step of claim 1 to 8 described in any item method for processing report data are realized when processor executes.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910639137.4A CN110347698A (en) | 2019-07-16 | 2019-07-16 | Method for processing report data and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910639137.4A CN110347698A (en) | 2019-07-16 | 2019-07-16 | Method for processing report data and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110347698A true CN110347698A (en) | 2019-10-18 |
Family
ID=68175403
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910639137.4A Pending CN110347698A (en) | 2019-07-16 | 2019-07-16 | Method for processing report data and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110347698A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111966677A (en) * | 2020-06-28 | 2020-11-20 | 北京百度网讯科技有限公司 | Data report processing method and device, electronic equipment and storage medium |
| CN112445814A (en) * | 2020-12-15 | 2021-03-05 | 北京乐学帮网络技术有限公司 | Data acquisition method and device, computer equipment and storage medium |
| CN112632411A (en) * | 2020-12-24 | 2021-04-09 | 武汉旷视金智科技有限公司 | Target object data query method, device, equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108334554A (en) * | 2017-12-29 | 2018-07-27 | 上海跬智信息技术有限公司 | A kind of novel OLAP precomputations model and construction method |
| CN109213829A (en) * | 2017-06-30 | 2019-01-15 | 北京国双科技有限公司 | Data query method and device |
| CN109471893A (en) * | 2018-10-24 | 2019-03-15 | 上海连尚网络科技有限公司 | Querying method, equipment and the computer readable storage medium of network data |
-
2019
- 2019-07-16 CN CN201910639137.4A patent/CN110347698A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109213829A (en) * | 2017-06-30 | 2019-01-15 | 北京国双科技有限公司 | Data query method and device |
| CN108334554A (en) * | 2017-12-29 | 2018-07-27 | 上海跬智信息技术有限公司 | A kind of novel OLAP precomputations model and construction method |
| CN109471893A (en) * | 2018-10-24 | 2019-03-15 | 上海连尚网络科技有限公司 | Querying method, equipment and the computer readable storage medium of network data |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111966677A (en) * | 2020-06-28 | 2020-11-20 | 北京百度网讯科技有限公司 | Data report processing method and device, electronic equipment and storage medium |
| CN111966677B (en) * | 2020-06-28 | 2024-04-19 | 北京百度网讯科技有限公司 | Data report processing method and device, electronic equipment and storage medium |
| CN112445814A (en) * | 2020-12-15 | 2021-03-05 | 北京乐学帮网络技术有限公司 | Data acquisition method and device, computer equipment and storage medium |
| CN112632411A (en) * | 2020-12-24 | 2021-04-09 | 武汉旷视金智科技有限公司 | Target object data query method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11232152B2 (en) | Efficient processing of neighborhood data | |
| Bagga et al. | QoS based web service selection and multi-criteria decision making methods | |
| Sultana et al. | An integrated approach for multiple criteria supplier selection combining Fuzzy Delphi, Fuzzy AHP & Fuzzy TOPSIS | |
| CN110347698A (en) | Method for processing report data and device | |
| CN106776660A (en) | A kind of information recommendation method and device | |
| CN106156092B (en) | Data processing method and device | |
| CN102591873B (en) | A kind of information recommendation method and equipment | |
| CN103679497A (en) | Trial commodity distributing method and device | |
| CN110096489A (en) | A kind of data query method, system, device and electronic equipment | |
| CN106202209B (en) | The storage of distributed structured data and querying method towards commodity screening application | |
| CN106202092A (en) | The method and system that data process | |
| CN109191133A (en) | The selection method and terminal device of channel of disbursement | |
| Ebrahimnejad et al. | Selection of IT outsourcing services’ activities considering services cost and risks by designing an interval-valued hesitant fuzzy-decision approach | |
| US20210334713A1 (en) | Resource Capacity Planning System | |
| CN110097302A (en) | The method and apparatus for distributing order | |
| Yang et al. | An improved cop-kmeans clustering for solving constraint violation based on mapreduce framework | |
| US20170039196A1 (en) | Computing system to evaluate sentiment of entities by processing data | |
| CN107844536A (en) | The methods, devices and systems of application program selection | |
| Yang et al. | Trust-based scheduling strategy for cloud workflow applications | |
| Hofreiter et al. | Rank aggregation for QoS-aware web service selection and composition | |
| Ludwig | Memetic algorithms applied to the optimization of workflow compositions | |
| CN103595783B (en) | Cloud computing scheduling system and cloud computing scheduling method | |
| CN108256694A (en) | Based on Fuzzy time sequence forecasting system, the method and device for repeating genetic algorithm | |
| de Moraes et al. | An Efficiency Frontier based Model for Cloud Computing Provider Selection and Ranking. | |
| CN110365799A (en) | A kind of cluster multinode dispatching method, device and computer readable storage medium |
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 |
Application publication date: 20191018 |
|
| RJ01 | Rejection of invention patent application after publication |