CN110069508A - Data analysing method, device and terminal device based on big data - Google Patents
Data analysing method, device and terminal device based on big data Download PDFInfo
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- CN110069508A CN110069508A CN201710942846.0A CN201710942846A CN110069508A CN 110069508 A CN110069508 A CN 110069508A CN 201710942846 A CN201710942846 A CN 201710942846A CN 110069508 A CN110069508 A CN 110069508A
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- 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
- G06F16/2428—Query predicate definition using graphical user interfaces, including menus and forms
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- 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
- G06F16/245—Query processing
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- 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
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24553—Query execution of query operations
- G06F16/24554—Unary operations; Data partitioning operations
- G06F16/24556—Aggregation; Duplicate elimination
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- 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
- G06F16/248—Presentation of query results
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- 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
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/283—Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
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- 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
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
Abstract
The embodiment of the invention provides a kind of data analysing method based on big data, device and terminal devices, wherein the data analysing method based on big data includes: the data analysis request for receiving user and being sent by visualization interface；The matching analysis processing is carried out to data analysis request by the multiple cubes obtained, and returns to corresponding analysis result；Wherein, cube obtains after carrying out polymerization processing to big data sample in advance.The embodiment of the present invention, comprehensively the matching analysis processing quickly, neatly is carried out to the data analysis request of user by cube, to in response to the data analysis request of user, realize that user can intuitively observe by visualization interface, browse, studying the analysis result returned accurately and in time.
Description
Technical field
The present invention relates to data analysis technique fields, specifically, the present invention relates to a kind of data based on big data point
Analyse method, apparatus and terminal device.
Background technique
With the arriving in information data epoch, the mechanisms such as government, enterprise have accumulated a large amount of business processing and turn of the market
Data, in particular with the high speed development of Internet technology, the explosive increase trend of the data volume of every profession and trade exponentially,
Some applications can reach million grades or more, mass data amounts more than even hundred tera-scale, thousand tera-scale, such as business intelligence
The application such as energy, environment weather, digital city, biological information, these data contain a large amount of information, but need reasonable place
Reason could be formed it is useful can information for reference, in order to predict and in time make a policy to future.
However, can search in face of so huge data system, the data volume inquired it is more and more, therefrom extracting can
The difficulty of information for reference is also increasing, brings great challenge for the analysis of a certain data to data analyst, adopts
It has been difficult to deal with mass data with traditional means of numerical analysis, in the analysis process, can not only wasted compared with multi-system resource,
And take long time, efficiency it is extremely low, be unable to satisfy data analyst be directed to a certain data analysis demand.
Summary of the invention
The purpose of the present invention is intended at least can solve above-mentioned one of technological deficiency, and spy proposes following technical scheme:
The embodiment of the present invention provides a kind of data analysing method based on big data according on one side, comprising:
Receive the data analysis request that user is sent by visualization interface；
The matching analysis processing is carried out to the data analysis request by the multiple cubes obtained, and returns to phase
The analysis result answered；
Wherein, the cube obtains after carrying out polymerization processing to big data sample in advance.
It is preferably, described that polymerization processing is carried out to big data sample in advance, comprising:
Based on the big data sample for the intended service type being pre-stored in data warehouse, the multiple of preset model type are constructed
Multidimensional Data Model；
Big data sample according to the multiple Multidimensional Data Model to the intended service type being pre-stored in data warehouse
Polymerization processing is carried out, multiple cubes are obtained.
Preferably, it is described according to the multiple Multidimensional Data Model to the intended service type being pre-stored in data warehouse
Big data sample carries out polymerization processing, obtains multiple cubes, comprising:
Polymerization processing is carried out to the big data sample according to the multiple Multidimensional Data Model, generates and corresponds to multiple dimensions
Multiple tables of data of degree；
Multiple cubes are constructed based on the multiple tables of data.
Preferably, multiple cubes by having obtained carry out at the matching analysis the data analysis request
Reason, and return to corresponding analysis result, comprising:
Data to be analyzed are extracted from the data analysis request；
Any the multidimensional data whether data to be analyzed are concentrated with the multiple multidimensional data is analyzed to match；
If analyzing result is matching, returning response is in the analysis report of the data analysis request.
Preferably, described that polymerization processing is carried out to big data sample in advance, it specifically includes:
Polymerization processing is carried out to big data sample in preset time section with predetermined period；
And polymerization processing result is stored into the database of predefined type.
Preferably, the database of the predefined type includes relational database.
The embodiment of the present invention additionally provides a kind of data analysis set-up based on big data according on the other hand, wraps
It includes:
Receiving module, the data analysis request sent for receiving user by visualization interface；
Respond module is handled, the data analysis request is matched for multiple cubes by having obtained
Analysis processing, and return to corresponding analysis result；
Wherein, the cube is obtained after polymerization processing module carries out polymerization processing to big data sample in advance
's.
Preferably, the polymerization processing module specifically includes: Multidimensional Data Model building submodule is obtained with cube
Take submodule；
The Multidimensional Data Model constructs submodule, for based on the big of the intended service type being pre-stored in data warehouse
Data sample constructs multiple Multidimensional Data Models of preset model type；
The cube acquisition submodule, for according to the multiple Multidimensional Data Model to being prestored in data warehouse
The big data sample of the intended service type of storage carries out polymerization processing, obtains multiple cubes.
Preferably, the cube acquisition submodule specifically includes: tables of data generates subelement and cube
Construct subelement；
The tables of data generates subelement, for being carried out according to the multiple Multidimensional Data Model to the big data sample
Polymerization processing, generates the multiple tables of data for corresponding to multiple dimensions；
The cube constructs subelement, for constructing multiple cubes based on the multiple tables of data.
Preferably, the processing respond module includes: extracting sub-module, analysis submodule and response submodule；
The extracting sub-module, for extracting data to be analyzed from the data analysis request；
The analysis submodule, any whether concentrated with the multiple multidimensional data for analyzing the data to be analyzed
Multidimensional data matching；
The response submodule, for when analyzing result is matching, returning response to be in point of the data analysis request
Analysis report.
Preferably, the polymerization processing module be specifically used for predetermined period preset time section to big data sample into
Row polymerization processing, and polymerization processing result is stored into the database of predefined type.
Preferably, the database of the predefined type includes relational database.
The embodiment of the present invention additionally provides a kind of terminal device according on the other hand, including memory, processor and
The computer program that can be run on a memory and on a processor is stored, processor is realized above-mentioned based on big number when executing program
According to data analysing method.
The embodiment of the present invention receives the data analysis request that sends by visualization interface of user, so that user is can
Simple operations are carried out depending on changing interface, corresponding analysis can be carried out for a certain data, meanwhile, pass through visualization circle for subsequent user
Face intuitively checks that the data analysis result of return provides premise guarantee；Data are divided by the multiple cubes obtained
Analysis request carries out the matching analysis processing, wherein and cube obtains after carrying out polymerization processing to big data sample in advance,
So as to quickly, neatly be asked to the data analysis of user by cube on the basis of existing big data sample
Asking progress, comprehensively the matching analysis is handled, and data analysis is effectively performed；Return to corresponding analysis as a result, to timely respond in
The data analysis request of user realizes that user can intuitively observe by visualization interface, browse, studying the analysis knot returned
Fruit.
The additional aspect of the present invention and advantage will be set forth in part in the description, these will become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect and advantage of the invention will become from the following description of the accompanying drawings of embodiments
Obviously and it is readily appreciated that, in which:
Fig. 1 is the flow chart of the data analysing method based on big data of first embodiment of the invention；
Fig. 2 is the structural schematic diagram of the Star Model of first embodiment of the invention；
Fig. 3 is the basic structure schematic diagram of the data analysis set-up based on big data of second embodiment of the invention；
Fig. 4 is the detailed construction schematic diagram of the data analysis set-up based on big data of second embodiment of the invention.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, and for explaining only the invention, and is not construed as limiting the claims.
Those skilled in the art of the present technique are appreciated that unless expressly stated, singular " one " used herein, " one
It is a ", " described " and "the" may also comprise plural form.It is to be further understood that being arranged used in specification of the invention
Diction " comprising " refer to that there are the feature, integer, step, operation, element and/or component, but it is not excluded that in the presence of or addition
Other one or more features, integer, step, operation, element, component and/or their group.It should be understood that when we claim member
Part is " connected " or when " coupled " to another element, it can be directly connected or coupled to other elements, or there may also be
Intermediary element.In addition, " connection " used herein or " coupling " may include being wirelessly connected or wirelessly coupling.It is used herein to arrange
Diction "and/or" includes one or more associated wholes for listing item or any cell and all combinations.
Those skilled in the art of the present technique are appreciated that unless otherwise defined, all terms used herein (including technology art
Language and scientific term), there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Should also
Understand, those terms such as defined in the general dictionary, it should be understood that have in the context of the prior art
The consistent meaning of meaning, and unless idealization or meaning too formal otherwise will not be used by specific definitions as here
To explain.
Those skilled in the art of the present technique are appreciated that " terminal " used herein above, " terminal device " both include wireless communication
The equipment of number receiver, only has the equipment of the wireless signal receiver of non-emissive ability, and including receiving and emitting hardware
Equipment, have on bidirectional communication link, can carry out two-way communication reception and emit hardware equipment.This equipment
It may include: honeycomb or other communication equipments, shown with single line display or multi-line display or without multi-line
The honeycomb of device or other communication equipments；PCS (Personal Communications Service, PCS Personal Communications System), can
With combine voice, data processing, fax and/or communication ability；PDA (Personal Digital Assistant, it is personal
Digital assistants), it may include radio frequency receiver, pager, the Internet/intranet access, web browser, notepad, day
It goes through and/or GPS (Global Positioning System, global positioning system) receiver；Conventional laptop and/or palm
Type computer or other equipment, have and/or the conventional laptop including radio frequency receiver and/or palmtop computer or its
His equipment." terminal " used herein above, " terminal device " can be it is portable, can transport, be mounted on the vehicles (aviation,
Sea-freight and/or land) in, or be suitable for and/or be configured in local runtime, and/or with distribution form, operate in the earth
And/or any other position operation in space." terminal " used herein above, " terminal device " can also be communication terminal, on
Network termination, music/video playback terminal, such as can be PDA, MID (Mobile Internet Device, mobile Internet
Equipment) and/or mobile phone with music/video playing function, it is also possible to the equipment such as smart television, set-top box.
First embodiment of the invention provides a kind of data analysing method based on big data, and detailed process is as shown in Figure 1.
Step 110: receiving the data analysis request that user is sent by visualization interface.
Specifically, user or passes through touching sending data analysis request in such a way that visualization interface pulls data
It touches the modes such as predeterminated position, display box, graphics item, the virtual key of visualization interface and sends data analysis request, wherein touching
The mode touched include but is not limited to click, double-click, the common operations such as left cunning, right cunning, or by it is in the prior art other
Visualization interface mode of operation sends data analysis request.
Step 120: the matching analysis processing being carried out to data analysis request by the multiple cubes obtained, and is returned
Return corresponding analysis result；Wherein, cube obtains after carrying out polymerization processing to big data sample in advance.
Specifically, more by what is obtained after receiving the data analysis request that user is sent by visualization interface
A cube carries out the matching analysis processing to data analysis request, and returns to corresponding analysis result.
Users'Data Analysis method provided in an embodiment of the present invention based on big data receives user and passes through visualization interface
The data analysis request of transmission can carry out corresponding so that user carries out simple operations in visualization interface for a certain data
Analysis, meanwhile, intuitively check that the data analysis result of return provides premise guarantee by visualization interface for subsequent user；It is logical
The matching analysis processing is carried out to data analysis request after the multiple cubes obtained, wherein cube is preparatory
Big data sample obtain after polymerization processing, so as to pass through multidimensional number on the basis of existing big data sample
Comprehensively the matching analysis processing quickly, neatly is carried out to the data analysis request of user according to collection, data analysis is effectively performed
And corresponding analysis is returned as a result, realizing that user can pass through visualization to timely respond to the data analysis request in user
It observes to objective interface, browse, studying the analysis result returned.
The second embodiment of the present invention is related to a kind of Users'Data Analysis method based on big data, and second embodiment is
On the basis of one embodiment, the preparatory realization process that polymerization processing is carried out to big data sample in step 120 is shown in particular,
It describes in detail below to the process for carrying out polymerization processing to big data sample in advance.
Preferably, preparatory the step of polymerization processing is carried out to big data sample in step 120, comprising: be based on data bins
The big data sample for the intended service type being pre-stored in library constructs multiple Multidimensional Data Models of preset model type；According to
Multiple Multidimensional Data Models carry out polymerization processing to the big data sample for the intended service type being pre-stored in data warehouse, obtain
Multiple cubes.
Specifically, the basic function of data warehouse is data storage, in the process for storing data in data warehouse in advance
In, the big data sample of intended service type can be imported in data warehouse by ETL tool or other means, to guarantee number
According to the big data sample for being pre-stored intended service type in warehouse, wherein ETL tool can be Storm, Kafka, Flume,
One or more of Kettle, Sqoop, the big data sample of intended service type include but is not limited to ad data, express delivery
Or logistics data, College Recruitment Students data and social security data etc., big data sample can be million grades or more, even 100,000,000,000,000
Mass data more than grade, thousand tera-scale.
Further, since the polymerization processing of big data is carried out on the basis of Multidimensional Data Model, so needing
First construct Multidimensional Data Model.Multidimensional model popular at present has Star Model, snowflake type model and fact constellation pattern
Type needs the data characteristics according to big data sample itself, structure when constructing multiple Multidimensional Data Models of preset model type
The Multidimensional Data Model of suitable type is built, such as all big data sample standard deviations are configured to multiple multidimensional datas of Star Model
Model, perhaps by all big data sample standard deviations be configured to snowflake type model multiple Multidimensional Data Models or will be all
Big data sample standard deviation is configured to multiple Multidimensional Data Models of fact constellation pattern type.
Preferably, the big data sample according to multiple Multidimensional Data Models to the intended service type being pre-stored in data warehouse
This carries out polymerization processing, obtains multiple cubes, comprising: is gathered according to multiple Multidimensional Data Models to big data sample
Conjunction processing, generates the multiple tables of data for corresponding to multiple dimensions；Multiple cubes are constructed based on multiple tables of data.
Specifically, can be incited somebody to action during carrying out polymerization processing to big data sample according to multiple Multidimensional Data Models
It flocks together with similar or correlation properties data, and tables of data is for storing data, and for the ease of data
Data with similar or related subject or dimension, are traditionally stored in same tables of data, then, at polymerization by management
Multiple tables of data corresponding to multiple dimensions, such as multiple tables of data of region dimension, product dimension can be generated during reason
Multiple tables of data, multiple tables of data of multiple dimensions such as multiple tables of data of time dimension, based between multiple tables of data
Relevance or keyword etc. construct multiple cubes, so that hundred billion grades of big data is degraded to the industry after million grades of polymerizations
Business data.
Preferably, preparatory the step of polymerization processing is carried out to big data sample in step 120, comprising: with predetermined period
Polymerization processing is carried out to big data sample in preset time section；And polymerization processing result is stored to the database of predefined type
In.
Preferably, the database of predefined type includes relational database.
Specifically, normal data analysis is carried out in order to avoid influencing user, usually in the period of relative free
The polymerization processing of big data sample is carried out, such as is carried out in the period of morning 00:00-8:00, in another example carried out in festivals or holidays,
Being continuously increased or update with big data sample simultaneously, carries out polymerization processing to big data sample with needing predetermined period, with
Update cube, so as to provide more acurrate, appropriate analysis as a result, for reference, wherein predetermined period according to
User sets, and can be daily, is also possible to weekly, is also possible to monthly etc..
Further, polymerization treated polymerization processing result can be stored in the database of predefined type, so as to
When carrying out the matching analysis processing to data, database can be quickly and easily inquired by corresponding database language, and obtain
Corresponding analysis result, wherein database can be relational database, such as oracle database, SQL Serve database,
MySQL database etc..
Further, below by taking most common Star Model as an example, the basic structure of multidimensional model is briefly introduced,
Wherein, the structure of Star Model is as shown in Fig. 2, in Star Model, and tables of data is broadly divided into two kinds, and one is include big lot number
According to and without redundancy center table (i.e. true table), center table is the most concerned primary entity of user and the matching analysis processing
Center, another kind are small attached table (dimension tables), and multiple dimension tables are radially distributed in the surrounding of center table, and logical with center table
Cross keyword connection, wherein the table 1 in Fig. 2 is center table, and table 2 in addition to expression table 1, table 3, table 4 in Fig. 2 etc. are
Attached table is associated by corresponding keyword with center table, is associated between attached table also by corresponding keyword,
Such as it is associated between attached table 3 and attached table 4 by predetermined keyword, passes through another predetermined pass between attached table 5 and attached table 6
The association of key word.
The embodiment of the present invention constructs Multidimensional Data Model during carrying out polymerization processing to big data sample in advance
Necessary premise guarantee is provided for the polymerization processing of big data, big data sample is gathered according to multiple Multidimensional Data Models
Conjunction processing, will flock together to obtain multiple cubes with similar or correlation properties data, thus timely respond in
The data analysis request of user allows user intuitively observe, browse by visualization interface, studies the analysis knot returned
Fruit allows provided analysis result with big number moreover, with predetermined period carrying out polymerization processing to big data sample
Being continuously increased or update and more accurate, appropriate according to sample.
The third embodiment of the present invention is related to a kind of Users'Data Analysis method based on big data, and 3rd embodiment is upper
On the basis of stating first embodiment or second embodiment, the detailed implementation of step 120 is shown in particular, below to this hair
Bright 3rd embodiment describes in detail, specific as follows:
The matching analysis processing is carried out to data analysis request by the multiple cubes obtained, and is returned corresponding
Analyze result, comprising: step 121, data to be analyzed are extracted from data analysis request；Step 122, analyzing data to be analyzed is
The no any multidimensional data concentrated with multiple multidimensional datas matches；Step 123, if analysis result is matching, returning response
In the analysis report of data analysis request.
Specifically, being asked when receiving the data analysis request of user's transmission by visualization interface from data analysis
It asks middle and extracts its data to be analyzed carried, to carry out corresponding the matching analysis processing to specific data to be analyzed, matching
It analyzes in treatment process, analyzes whether data to be analyzed match with any multidimensional data in multiple multidimensional datas, if it does,
Then returning response is in the analysis report of data analysis request, wherein user can be by carrying out data dragging in visual page
Mode sends data analysis request, analyzes whether data to be analyzed match with any multidimensional data in multiple multidimensional datas,
It detects data to be analyzed and whether hits the data of polymerization, if having hit the data of polymerization, return to corresponding analysis report,
If not hitting the data of polymerization, at present using the strategy for returning to sample data, and when the data analysis request of user is audited
By rear, full dose data or part most related data are returned in real time.
The embodiment of the present invention passes through the data to be analyzed in analysis data analysis request in the matching analysis treatment process
Whether with the matched mode of any multidimensional data in multiple multidimensional datas, to data analysis request carry out the matching analysis processing,
To on the basis of existing big data sample, realize real-time, quick data analysis, and return to reliable analysis result.
The fourth embodiment of the present invention is related to a kind of Users'Data Analysis device based on big data, as shown in figure 3, specifically
Include: receiving module S10, handle respond module S20 and polymerize processing module S30.
Receiving module S10, the data analysis request sent for receiving user by visualization interface.
Respond module S20 is handled, data analysis request is matched for multiple cubes by having obtained
Analysis processing, and return to corresponding analysis result；Wherein, cube be polymerization processing module in advance to big data sample into
It is obtained after row polymerization processing.
Further, polymerization processing module S30 is specifically included: Multidimensional Data Model constructs submodule S31 and multidimensional data
Collect acquisition submodule S32, as shown in Figure 4, wherein Multidimensional Data Model constructs submodule S31, for based on pre- in data warehouse
The big data sample of the intended service type of storage constructs multiple Multidimensional Data Models of preset model type；Cube
Acquisition submodule S32, for according to the multiple Multidimensional Data Model to the intended service type being pre-stored in data warehouse
Big data sample carries out polymerization processing, obtains multiple cubes.
Further, cube acquisition submodule S32 is specifically included: tables of data generates subelement S321 and multidimensional number
Subelement S322 is constructed according to collection, as shown in Figure 4, wherein tables of data generates subelement S321, for according to multiple multidimensional data moulds
Type carries out polymerization processing to the big data sample, generates the multiple tables of data for corresponding to multiple dimensions；Cube building
Subelement S322, for constructing multiple cubes based on multiple tables of data.
Further, processing respond module includes: extracting sub-module S21, analysis submodule S22 and responds submodule S23,
As shown in Figure 4, wherein extracting sub-module S21, for extracting data to be analyzed from data analysis request；Analysis module S22,
It is matched for analyzing any multidimensional data whether data to be analyzed are concentrated with multiple multidimensional datas；Submodule S23 is responded, is used for
When analyzing result is matching, returning response is in the analysis report of data analysis request.
Further, polymerization processing module S30 is specifically used for predetermined period in preset time section to big data sample
Polymerization processing is carried out, and polymerization processing result is stored into the database of predefined type.
Further, the database of predefined type includes relational database.
Users'Data Analysis method provided in an embodiment of the present invention based on big data receives user and passes through visualization interface
The data analysis request of transmission can carry out corresponding so that user carries out simple operations in visualization interface for a certain data
Analysis, meanwhile, intuitively check that the data analysis result of return provides premise guarantee by visualization interface for subsequent user；It is logical
The matching analysis processing is carried out to data analysis request after the multiple cubes obtained, wherein cube is preparatory
Big data sample obtain after polymerization processing, so as to pass through multidimensional number on the basis of existing big data sample
Comprehensively the matching analysis processing quickly, neatly is carried out to the data analysis request of user according to collection, data analysis is effectively performed
And corresponding analysis is returned as a result, realizing that user can pass through visualization to timely respond to the data analysis request in user
It observes to objective interface, browse, studying the analysis result returned.
The fifth embodiment of the present invention provides a kind of terminal device, including memory, processor and is stored in memory
Computer program that is upper and can running on a processor, processor are realized when executing program and are based on shown in any of the above-described embodiment
The data analysing method of big data.
Those skilled in the art of the present technique are appreciated that the present invention includes being related to for executing in operation described herein
One or more equipment.These equipment can specially design and manufacture for required purpose, or also may include general
Known device in computer.These equipment have the computer program being stored in it, these computer programs are selectively
Activation or reconstruct.Such computer program can be stored in equipment (for example, computer) readable medium or be stored in
It e-command and is coupled in any kind of medium of bus respectively suitable for storage, the computer-readable medium includes but not
Be limited to any kind of disk (including floppy disk, hard disk, CD, CD-ROM and magneto-optic disk), ROM (Read-Only Memory, only
Read memory), RAM (Random Access Memory, immediately memory), EPROM (Erasable Programmable
Read-Only Memory, Erarable Programmable Read only Memory), EEPROM (Electrically Erasable
Programmable Read-Only Memory, Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or light card
Piece.It is, readable medium includes by equipment (for example, computer) with any Jie for the form storage or transmission information that can be read
Matter.
Those skilled in the art of the present technique be appreciated that can be realized with computer program instructions these structure charts and/or
The combination of each frame and these structure charts and/or the frame in block diagram and/or flow graph in block diagram and/or flow graph.This technology neck
Field technique personnel be appreciated that these computer program instructions can be supplied to general purpose computer, special purpose computer or other
The processor of programmable data processing method is realized, to pass through the processing of computer or other programmable data processing methods
The scheme specified in frame or multiple frames of the device to execute structure chart and/or block diagram and/or flow graph disclosed by the invention.
Those skilled in the art of the present technique have been appreciated that in the present invention the various operations crossed by discussion, method, in process
Steps, measures, and schemes can be replaced, changed, combined or be deleted.Further, each with having been crossed by discussion in the present invention
Kind of operation, method, other steps, measures, and schemes in process may also be alternated, changed, rearranged, decomposed, combined or deleted.
Further, in the prior art to have and the step in various operations, method disclosed in the present invention, process, measure, scheme
It may also be alternated, changed, rearranged, decomposed, combined or deleted.
The above is only some embodiments of the invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (10)
1. a kind of data analysing method based on big data characterized by comprising
Receive the data analysis request that user is sent by visualization interface；
The matching analysis processing is carried out to the data analysis request by the multiple cubes obtained, and is returned corresponding
Analyze result；
Wherein, the cube obtains after carrying out polymerization processing to big data sample in advance.
2. being wrapped the method according to claim 1, wherein described carry out polymerization processing to big data sample in advance
It includes:
Based on the big data sample for the intended service type being pre-stored in data warehouse, multiple multidimensional of preset model type are constructed
Data model；
It is carried out according to big data sample of the multiple Multidimensional Data Model to the intended service type being pre-stored in data warehouse
Polymerization processing, obtains multiple cubes.
3. according to the method described in claim 2, it is characterized in that, it is described according to the multiple Multidimensional Data Model to data bins
The big data sample for the intended service type being pre-stored in library carries out polymerization processing, obtains multiple cubes, comprising:
Polymerization processing is carried out to the big data sample according to the multiple Multidimensional Data Model, generates and corresponds to multiple dimensions
Multiple tables of data；
Multiple cubes are constructed based on the multiple tables of data.
4. method according to claim 1-3, which is characterized in that multiple multidimensional datas by having obtained
Collection carries out the matching analysis processing to the data analysis request, and returns to corresponding analysis result, comprising:
Data to be analyzed are extracted from the data analysis request；
Any the multidimensional data whether data to be analyzed are concentrated with the multiple multidimensional data is analyzed to match；
If analyzing result is matching, returning response is in the analysis report of the data analysis request.
5. having the method according to claim 1, wherein described carry out polymerization processing to big data sample in advance
Body includes:
Polymerization processing is carried out to big data sample in preset time section with predetermined period；
And polymerization processing result is stored into the database of predefined type.
6. according to the method described in claim 5, it is characterized in that, the database of the predefined type includes relational database.
7. a kind of data analysis set-up based on big data characterized by comprising
Receiving module, the data analysis request sent for receiving user by visualization interface；
Respond module is handled, the matching analysis is carried out to the data analysis request for multiple cubes by having obtained
Processing, and return to corresponding analysis result；
Wherein, the cube polymerization processing module obtains after carrying out polymerization processing to big data sample in advance.
8. device according to claim 7, which is characterized in that the polymerization processing module specifically includes: multidimensional data mould
Type constructs submodule and cube acquisition submodule；
The Multidimensional Data Model constructs submodule, for the big data based on the intended service type being pre-stored in data warehouse
Sample constructs multiple Multidimensional Data Models of preset model type；
The cube acquisition submodule, for according to the multiple Multidimensional Data Model in data warehouse be pre-stored
The big data sample of intended service type carries out polymerization processing, obtains multiple cubes.
9. device according to claim 8, which is characterized in that the cube acquisition submodule specifically includes: number
Subelement is generated according to table and cube constructs subelement；
The tables of data generates subelement, for being polymerize according to the multiple Multidimensional Data Model to the big data sample
Processing generates the multiple tables of data for corresponding to multiple dimensions；
The cube constructs subelement, for constructing multiple cubes based on the multiple tables of data.
10. a kind of terminal device 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 is realized described in any one of claims 1-6 based on big number when executing described program
According to data analysing method.
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