CN110442629A - Big data multicenter isomery daynamic transformation method - Google Patents
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Abstract
The present invention provides a kind of big data multicenter isomery daynamic transformation method, this method includes the first data inquiry request information for obtaining subsystem and sending, and obtains the data model of subsystem from multidimensional data dictionary database according to the information of subsystem and parses to the data model of acquisition；The second data inquiry request information is issued to virtual data source according to the result of parsing, and judge whether the data of inquiry are the data for executing default operation, if not being, third data inquiry request information is issued from virtual data source to real data source, according to the data model and mapping ruler of subsystem, received data is converted into the corresponding data shape of subsystem, and the data after conversion are sent to subsystem.The present invention can low cost the polycentric data transformation operations of realization.
Description
Technical field
The present invention relates to technical field of data processing, specifically big data multicenter isomery daynamic transformation method.
Background technique
With the development of big data technology, big data technology has been widely used in user information collection, user behavior point
The multiple fields such as analysis, Personalized service, wherein data conversion is a key link of big data process flow.At present
General big data process flow is ETL (Extract-Transform-Load) process.Wherein data conversion
It (DataTransform) is an important link in big data process flow.
Traditional data converts a kind of method using centralization, as shown in Figure 1, existing big data processing method can
The data of multiple data sources can be handled, for example, need to the data of data source 11, data source 12 and data source 13 into
Row processing.Traditional data transfer device is usually arranged a data center 20, the data of multiple and different data sources need by
Data shift to an earlier date, data adapter unit forms normal data, and normal data will be stored in data center 20, such as the data of data source 11
After data extract the conversion operation of 14 and data adapter unit 17, it is stored in data center 20, and the data of data source 12
After data extract the conversion operation of 15 and data adapter unit 18, it is stored in data center 20, the data warp of data source 13
After crossing the conversion operation of data extraction 16 and data adapter unit 19, it is stored in data center 20, is stored in data center 20
Data are by data cleansing, and are static, centralization normal datas.
With the continuous development of computer technology, this static, centralization data conversion technique is not able to satisfy gradually
The needs of many practical application scenes, dynamic, the data conversion demand of multicenter are increasing.If still taking static number
The data conversion demand of multicenter is solved according to the method for adapter, possible framework is as shown in Figure 2.Assuming that needing integrated three
A subsystem 21,22,23, subsystems have the data shape of oneself, such as the data shape of subsystem is 24, subsystem
22 data shape is 25, and the data shape of subsystem 23 is 26.If requiring to realize that data are handed between subsystems
Mutually, then need to be arranged conversion of the data adapter unit to carry out data, for example, setting data adapter unit 27 is for realizing data shape
Data adapter unit 28 is arranged for realizing between data shape 25 and data shape 26 in conversion between 24 and data shape 25
Data adapter unit 29 is arranged for realizing the conversion between data shape 24 and data shape 26 in conversion.
Obviously, if using this technology, when will lead to progress multicenter data conversion, need to construct a large amount of special mesh
Data adapter unit, increase the complexity of exploitation, O&M, the cost of data system is also very high.Also, due to each adaptation
Device is all special mesh and designs that the software reusability of each adapter is very poor.In addition, once data and its attribute occur
When change, need to change one by one all adapters relevant to the data, upgrade-system could use again, greatly increase liter
Grade, update and testing cost.In some data variations than more frequently application scenarios, this method bring negative effect can be big
The big availability and reliability for influencing system.It is converted finally, the adapter of this method can only be used as static data, as data spy
Property be possible to dynamic when changing, this method cannot meet actual demand.
Summary of the invention
The main object of the present invention is to provide a kind of big data multicenter isomery dynamic data that adaptability is good and at low cost
Conversion method.
Main purpose to realize the present invention, big data multicenter isomery daynamic transformation method packet provided by the invention
It includes and obtains the first data inquiry request information that subsystem is sent, according to the information of subsystem from multidimensional data dictionary database
It obtains the data model of subsystem and the data model of acquisition is parsed；It is issued according to the result of parsing to virtual data source
Second data inquiry request information, and judge whether the data of inquiry are the data for executing default operation, if not being, by virtually counting
Third data inquiry request information is issued to real data source according to source, after obtaining the data that real data source returns, according to subsystem
Received data is converted into the corresponding data shape of subsystem by the data model and mapping ruler of system, and will be after conversion
Data be sent to subsystem.
By above scheme as it can be seen that after the request of virtual data source receiving subsystem, parsed according to the data model of subsystem
Result to real data source send inquiry request, and obtain real data source return data after, using after mapping turn
It changes the data model that subsystem can identify into and the data after conversion is returned into subsystem, in this way, virtual data source can connect
Receive the data inquiry request of multiple subsystems, also available multiple and different sub-systems data, in this way, be not provided with it is multiple
In the case where adapter, the conversion to a variety of different types of data is realized, that is, realize the conversion of data shape.
Therefore, it using the solution of the present invention, does not need that a large amount of data adapter unit is arranged, it is only necessary to according to data model
Attribute carries out adaptable conversion to a variety of different types of data shapes, and method of the invention can be adapted for a variety of differences
The data conversion of data shape, compatible a variety of different subsystems, adaptability are good.Also, it is multiple independent due to not needing to be arranged
The adapter for realizing the conversion of certain two kinds of data shape, can substantially reduce the cost of data conversion.
One Preferable scheme is that, such as confirmation inquiry data be to need to be implemented the data of default operation, then from data grasp
Make the operation rule information for obtaining the item data in rule database, obtains the data that real data source returns in virtual data source
Afterwards, after the data returned according to operation rule information to real data source carry out operation, according to the data model of subsystem and
Data after conversion by the data conversion after institute's operation at the corresponding data shape of subsystem, and are sent to son by mapping ruler
System.
It can be seen that the data if necessary to inquiry are the data needed by certain operations, then the present invention can be with
Operation is carried out according to data of the operation rule of operation setting to required operation, and the data after operation are subjected to data shape
The conversion of state, to realize the purpose of data query and data operation.
Further embodiment is, after the operation rule information for obtaining the item data in data manipulation rule database, also
Judge whether the operation to the data of inquiry needs to obtain supplementary data, if so, supplementary data inquiry request information is generated, to void
Quasi- data source sends the 4th data inquiry request information, obtains supplementary data from virtual data source.
As it can be seen that if carrying out also needing to obtain supplementary data during default operation, it can be from virtual data source
Supplementary data required for obtaining may insure the smooth execution of default operation in this way, can quick obtaining supplementary data go forward side by side
The effective operation of row timely returns to the result after operation to subsystem.
Further scheme is that the first data inquiry request information includes data name and querying condition, it is preferred that
Querying condition includes conditional name and condition value list.
It, can be with as it can be seen that by the way that the information such as data name, conditional name and condition value list are sent to virtual data source
Facilitate virtual data quickly to obtain the relevant information for needing the data inquired, improves efficiency data query.
Further scheme is that each subsystem all has unique identification code；According to the information of subsystem from multidimensional
The data model that subsystem is obtained in data dictionary database includes: according to the identification code of subsystem from multidimensional data dictionary data
The data model of subsystem is obtained in library.
It can be seen that obtaining the data module of the subsystem according to the identification code of subsystem, can quickly identify
Which subsystem need to inquire is, and quickly finds out the data model of the subsystem.
Further scheme is that carrying out parsing to the data model of acquisition includes: that following ginseng is parsed from data model
At least one several: mark of the data field of subsystem in virtual data source, subsystem data field in real data
Title of the data field of mark, subsystem in source in real data source, subsystem data field in real data source
In type, subsystem data field mapping ruler.
As it can be seen that obtaining a large amount of attribute informations of data model, and according to these categories by parsing to data model
Property information can determine data shape conversion regime, in order to accurately convert to data shape.
Further scheme is that multidimensional data dictionary database is stored with the corresponding data model of multiple subsystems, often
The information of one data model is including at least one below: the mapping of data name, data source and the data in source systems
Title, data format, static mappings rule code, data address of the operation rule in operation rule database.
It can be seen that can quickly determine data source according to the information to data model, be conducive to quickly obtain
Required data.
Detailed description of the invention
Fig. 1 is the structural block diagram of the data conversion system of existing big data processing.
Fig. 2 is the architecture diagram of data conversion in polycentric big data treatment process.
Fig. 3 is structure chart applied by big data multicenter isomery daynamic transformation embodiment of the method for the present invention.
Fig. 4 is the first part of the flow chart of big data multicenter isomery daynamic transformation embodiment of the method for the present invention.
Fig. 5 is the second part of the flow chart of big data multicenter isomery daynamic transformation embodiment of the method for the present invention.
The invention will be further described with reference to the accompanying drawings and embodiments.
Specific embodiment
Big data multicenter isomery daynamic transformation method of the invention is applied in big data treatment process, mainly
The data of a variety of different data forms are converted, to meet the requirement of the data conversion of multicenter.Preferably, of the invention
Method can apply on server cloud, it is preferred that server cloud have multiple servers that can mutually communicate, and these
Server can be property server, be also possible to virtual server, and the server of entity is provided with processor and storage
Device is stored with computer program on memory, and processor realizes big data multicenter isomery by executing the computer program
Daynamic transformation method.
Processor alleged by the present invention can be central processing unit (Central Processing Unit, CPU), may be used also
To be other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..
Memory can be used for storing computer program and/or module, and processor is stored in memory by operation or execution
Interior computer program and/or module, and the data being stored in memory are called, realize above-mentioned method.The present invention is simultaneously
The type of storage is not defined, memory may include high-speed random access memory, can also include non-volatile deposit
Reservoir, such as hard disk, memory, plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital
(Secure Digital, SD) card, flash card (Flash Card), disk memory, flush memory device or other volatibility are solid
State memory device.
The present embodiment is the method for data-driven, polycentric daynamic transformation, with meet data it is lack of standardization, variation compared with
There are the data conversion of relation of interdependence needs mostly between data source.The present embodiment application system architecture as shown in figure 3,
The system architecture includes five functional modules, is that multidimensional data dictionary database 30, virtual data source 40, data resource are set respectively
Set device 46, data request manager 55 and data manipulation rule database 60.
Wherein, virtual data source 40 is a virtual data warehouse, unlike real data warehouse, this implementation
In example, virtual data source 40 does not store real data, and an only agent data.Therefore, virtual data source 40
It needs to be connected to multiple systems, or even also requires connect to external data source 50, such as virtual data source 40 is connected to subsystem
51, subsystem 52 and subsystem 53, and the data shape of each subsystem can not be identical.
In this way, virtual data source 40 is seemed not to be had with the data warehouse of a centralization for the user of data
Have what difference, but when data query really occurs, virtual data source 40 by the address provided according to data management system 45 and
Inquiry instruction inquires data from real data source.In this way, as long as any one subsystem is provided with the virtual number of a set of satisfaction
According to the mechanism of 40 inquiry request of source, such as a set of instruction or executing rule are set, so that it may become virtual data at runtime
The plug-in real data source of one of source 40.Benefit using virtual data source 40 is exactly can be between complicated multiple subsystems
Data dependence relation simplify become from virtual data source 40 extract and inquire data relationship, avoid subsystems two-by-two
Between be respectively set independent data adapter unit, reduce used in adapter quantity.
Multidimensional data dictionary database 30 is stored with a data list, which includes the data of all subsystems
The information of model.Preferably, each data model includes at least one of following attribute information: data name, data source
And the data are in the mapping title, data format, static mappings rule code of source systems, if the data entry be need through
The data of operation are crossed, then data model further includes address of the corresponding operation in data manipulation rule database.For example, multidimensional number
According to the storage of dictionary database 30, there are many data models, such as data model 31,32,33.
Data manipulation rule database 60 also includes a data list, unlike common data list, number
Stored in data list according to operation rules database 60 be with can the computer language of on-the-flier compiler at runtime write
At code, write for example, by using Python.For example, data manipulation rule database 60 is stored with multiple data manipulation rules
61、62、63。
Data request manager 55 is for being managed request of data, wherein request of data can be based on abstract number
It is realized according to request protocol, generally comprises a subset of multiple subsystem data models.
Data management system 45 is the corn module for realizing the present embodiment, is mainly used for realizing the place of data inquiry request
Reason, conversion of data shape etc., for example, receiving the data inquiry request of some subsystem, and judge data to be checked
Whether need by preset operation, if you do not need to data management system 45 will be according to request of data by preset operation
Content retrieves the practical source of data from multidimensional data dictionary database 30, issues inquiry request letter to virtual data source 40
Breath, and the format that the corresponding data model of subsystem that query result mapping becomes request is required, the data after conversion are returned
Return corresponding subsystem.If data to be checked need to need to call corresponding generation at runtime by preset operation
Code compiler, transfers out data manipulation rule corresponding in data manipulation rule database 60 according to the requirement of data model
Come, be then compiled execution, after carrying out operation according to the rule of operation, the result of operation is returned into corresponding subsystem.Number
It is communicated according to resource setter 46 with data management system 45, and the parameter of data management system 45 can be set.
Therefore, during entire data query, conversion, data management system 45 does not need to know data and rule
Meaning, operation rule required for only calling and execute according to the identification code that data model provides, therefore work as data model
When changing, the code of data management system 45 is also had no need to change.In this way, the later maintenance cost of system is very low, and adapt to
Property is very strong, can satisfy the conversion requirements between a variety of different types of data shapes.
Since multiple subsystems 51,52,53 and external data source 50 are virtual with " centralization " in the form of real data source
Data source 40 connects, and meets the inquiry request of virtual data source 40 according to respective data model.Subsystem is according to oneself
When specific data model needs to inquire data, data query will be issued to virtual data source 40 by data management system 45 and asked
Information is sought, the query path of truthful data is parsed by virtual data source 40, and issue and inquire to the real data source of true path
Request, and by query result returned data manager 45, finally by data management system 45 by query result according to request of data side
Data model translation become required data shape.
The workflow of the present embodiment is introduced below with reference to Fig. 4 and Fig. 5.Assuming that some subsystem needs query information,
The subsystem sends a data inquiry request information to data management system, and therefore, step S1 is first carried out in data management system, connects
Receive the first data inquiry request information that subsystem is sent.Preferably, the first data inquiry request information includes inquiry in need
Data name and querying condition, wherein querying condition includes conditional name and condition value list.Therefore, from subsystem
Angle sees that data management system and virtual data source are entirely to construct using the data model of subsystem, that is, subsystem is not
It needs to carry out data the conversion of data shape, but the request of required inquiry data is directly sent to data management system i.e.
It can.
After data management system receives the first data inquiry request information of subsystem, step S2 is executed, the subsystem is obtained
The identification code of system.Preferably, in the present embodiment, each subsystem is provided with oneself unique identification code, and multidimensional data
The data model for each subsystem that dictionary database 30 is stored is stored according to the identification code of subsystem, i.e., more
Dimension data dictionary database 30 is stored with the identification code and the corresponding data model of the subsystem of each subsystem, in this way,
Multidimensional data dictionary database 30 can inquire the corresponding data model of the subsystem according to the identification code of subsystem.
Data management system according to the first data inquiry request acquisition of information information received is sent out by which subsystem
It send, and obtains the corresponding identification code of the subsystem, then execute step S3, according to the identification code of subsystem from multidimensional data word
Corresponding data model is obtained in allusion quotation database.Preferably, after obtaining data model, acquired data model is solved
Analysis, specifically, parsing at least one of following parameter from data model: the data field of the subsystem is in virtual data source
In mark, mark of the data field in real data source of the subsystem, the subsystem data field in real data
The data field mapping ruler of type of the data field of title, the subsystem in source in real data source, the subsystem.
If some subsystem is related to multiple data models, obtain multiple data models and to multiple data models into
Row parsing, obtains all conditions parameter field.
Then, step S4 is executed, the second data inquiry request information is issued to virtual data source, at this point, also needing to be implemented
Step S5, judges whether inquired data need by preset operation, that is, whether the data inquired are from reality
Data source also needs just be back to subsystem by certain operation after obtaining data, such as whether data to be checked are certain
The sum of group data or the inverse of some data etc. are executing step S11, if be not required to if necessary to pass through preset operation
S6 is thened follow the steps by default operation.
In step S6, third data inquiry request information is sent from virtual data source to real data source.For example, such as fruit
Border data source is a subsystem, then data management system runs the vlan query protocol VLAN of the subsystem, and passes through vlan query protocol VLAN to the son
The solicited message of system transmission data query.Which since virtual data source determines the path in real data source, also determine that
Subsystem sends third data inquiry request information.
Then, step S7 is executed, data management system receives the data that real data source returns, that is, query result, should
Query result is the data sent as the subsystem in real data source, and therefore, the data shape of the data is as actual number
According to the data shape of the subsystem in source, therefore, the data shape of the data of return may not be with the subsystem for issuing inquiry request
Data shape is consistent, if the data that will acquire are sent directly to issue the subsystem of inquiry request, the subsystem of inquiry request
It will be unable to identify the data.
Therefore, data management system executes step S8, by the data conversion received at the subsystem pair for issuing inquiry request
The data shape answered, specifically, data model and field mapping rule of the data management system according to the subsystem for issuing inquiry request
Then by the data conversion of inquiry acquisition at the data shape of the subsystem.Finally, executing step S9, the data after conversion are sent
To the subsystem for issuing inquiry request, in this way, the subsystem for issuing inquiry request can identify received data.
If the judging result of step S5 be it is yes, indicate inquiry data need that hair can be returned by preset operation
Therefore the subsystem of inquiry request out executes step S11, the operation of the item data is obtained from data manipulation rule database
Rule Information, such as obtained from the second data request information and carry out the type of default operation or the title of default operation
Deng, then from data manipulation rule database obtain corresponding operation rule code.
Then, step S12 is executed, judges to execute default operation, if the data for needing to obtain supplement, for example whether also needing
Relevant data are obtained from other subsystems can complete default operation otherwise, hold if desired, thening follow the steps S17
Row step S13.If you do not need to obtaining supplementary data, then the data of real data source return are obtained, then execute step S14,
Budget is carried out to acquired data according to the data operation rule that step S11 is obtained, such as carries out cumulative operation, Huo Zhejin
Row derivative action etc..
Then, step S15 is executed, the data that operation is obtained carry out the conversion of data shape, such as obtain and issue inquiry
The information of the data shape of the subsystem of request, according to the data model and field mapping ruler of the subsystem for issuing inquiry request
By the data conversion after operation at the data shape of the subsystem.Finally, executing step S16, the data after conversion are sent to
The subsystem of inquiry request is issued, in this way, the subsystem for issuing inquiry request can identify received data.
If the judging result of step S12 is yes, the default operation of expression realization, it is also necessary to from other subsystems or outside
Supplementary data is obtained in data source.At this point, executing step S17, data management system generates supplementary data inquiry request information, then
Step S18 is executed, sends the 4th data inquiry request information to virtual data source, and obtains supplement number from real data source
According to.It is often necessary to obtain supplementary data have specific data source, can according to the data source determination can from which son
System or external data source obtain supplementary data.It, can be by step S1 to step S9's after determining supplementary data source
Method obtains supplementary data.
After obtaining supplementary data, step S19 is executed, supplementary data is obtained, at this point, data management system is as supplementary data
Recipient, receive acquired supplementary data, then, execute step S13, the supplementary data that will acquire with from real data source
The data of acquisition carry out default operation, and obtain the result after operation.
Certainly, the supplementary data if necessary to obtain has multiple, then needs to be performed a plurality of times step S1 to step S9, until obtaining
Until taking all supplementary datas.
As it can be seen that during data conversion, each subsystem need to only be used and be mentioned above using the method for the present embodiment
And data model be conducive to the relative independentability of maintenance subsystem in this way, very without knowing other systems and data shape
The more in the practical application scene of data center, the dependence between subsystem can be substantially reduced, to reduce exploitation, dimension
Protect cost.
Also, the data concatenating between subsystems is become subsystem and void using virtual data source by the present embodiment
" centralization " data between quasi- data source are in parallel, thus Maintenance free data query sequence, data mode etc., simplify each
The maintenance of data flow between subsystem.
In addition, the present embodiment is not needed using data adapter unit, but utilize data model definitions and maintenance data and
Relational implementation data conversion between data, between data and system, so that data conversion process be made to become from code driving
Data-driven, the system extension greatly simplified, Data expansion and change process.For example, if integrated system need to add or
Person changes new data source, only need to add or change the data model of the data source in multidimensional data dictionary database, and
The trade mark agency in virtual data source, all subsystems can use the data, without updating data management system and owning
Subsystem.
In conclusion in big data era, initial data how to be made to become available information, data conversion be one must can not
Few step, a same data have different usages in different application scenarios, different systems, a kind of efficient, general
Suitable data conversion frame can greatly improve the service efficiency and use value of data.Likewise, integrated in large scope software
Application scenarios in, centralization data normalization method is not optimal selection no matter from the perspective of realizing and using,
Multicenter data conversion is a kind of inexorable trend.The innovation of this method is the number that both can be used between in-house door
According to conversion, trans-departmental, inter-trade platform software integrated data conversion can be used for, it is often more important that can be used for multicenter
Big data is excavated, and this conversion method based on data model can be used for Intelligent data analysis, such as use machine learning
Data model is generated, then available information is converted data to using the model.
Finally it is emphasized that the present invention is not limited to the above embodiments, such as the specific object information of data model
Variation or the data inquiry request information information that is included variation etc., these changes should also be included in power of the present invention
In the protection scope that benefit requires.
Claims (8)
1. big data multicenter isomery daynamic transformation method characterized by comprising
The first data inquiry request information that subsystem is sent is obtained, according to the information of the subsystem from multidimensional data dictionary number
It is parsed according to the data model for obtaining the subsystem in library and to the data model of acquisition；
According to the result of parsing to virtual data source issue the second data inquiry request information, and judge inquiry data whether be
The data for executing default operation issue third data inquiry request letter from the virtual data source to real data source if not being
Breath, after the virtual data source obtains the data that the real data source returns, according to the data model of the subsystem and
Received data is converted into the corresponding data shape of the subsystem, and the data after conversion is sent to by mapping ruler
The subsystem.
2. big data multicenter isomery daynamic transformation method according to claim 1, it is characterised in that:
The data for such as confirming inquiry are to need to be implemented the data of default operation, then obtain this from data manipulation rule database
The operation rule information of data, after obtaining the data that the real data source returns, according to the operation rule information to institute
After the data progress operation for stating the return of real data source, according to the data model and mapping ruler of the subsystem, it will be transported
Data conversion after calculation is sent to the subsystem at the corresponding data shape of the subsystem, and by the data after conversion.
3. big data multicenter isomery daynamic transformation method according to claim 2, it is characterised in that:
After the operation rule information for obtaining the item data in the data manipulation rule database, the data to inquiry are also judged
Operation whether need to obtain supplementary data, if so, generate supplementary data inquiry request information, Xiang Suoshu virtual data source send
4th data inquiry request information obtains supplementary data from the virtual data source.
4. big data multicenter isomery daynamic transformation method according to any one of claims 1 to 3, feature exist
In:
The first data inquiry request information includes data name and querying condition.
5. big data multicenter isomery daynamic transformation method according to claim 4, it is characterised in that:
The querying condition includes conditional name and condition value list.
6. big data multicenter isomery daynamic transformation method according to any one of claims 1 to 3, feature exist
In:
Each subsystem all has unique identification code；
The data model packet of the subsystem is obtained from the multidimensional data dictionary database according to the information of the subsystem
It includes: obtaining the data model of the subsystem from the multidimensional data dictionary database according to the identification code of the subsystem.
7. the big data multicenter isomery daynamic transformation method stated according to claim 1 to any one of 3, it is characterised in that:
Carrying out parsing to the data model of acquisition includes: at least one that following parameter is parsed from the data model: described
Mark of the data field of subsystem in the virtual data source, the subsystem data field in the real data source
In mark, title of the data field in the real data source of the subsystem, the subsystem data field exist
The mapping ruler of the data field of type, the subsystem in the real data source.
8. big data multicenter isomery daynamic transformation method according to any one of claims 1 to 3, feature exist
In:
The multidimensional data dictionary database is stored with the corresponding data model of multiple subsystems, each data model
Information include at least one below: mapping title in source systems of data name, data source and the data, data lattice
Formula, static mappings rule code, data address of the operation rule in operation rule database.
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