CN107918600A - report development system and method, storage medium and electronic equipment - Google Patents
report development system and method, storage medium and electronic equipment Download PDFInfo
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- CN107918600A CN107918600A CN201711127508.8A CN201711127508A CN107918600A CN 107918600 A CN107918600 A CN 107918600A CN 201711127508 A CN201711127508 A CN 201711127508A CN 107918600 A CN107918600 A CN 107918600A
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- G—PHYSICS
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- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
- G06F40/18—Editing, e.g. inserting or deleting of tables; using ruled lines of spreadsheets
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- 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
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
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Abstract
The invention discloses a kind of report development system and method, storage medium and electronic equipment, it is related to technical field of data processing.The report development system includes：Basic data warehouse, for the data for the data of each source system integrate and after storage integration；Topic module, for carrying out classification storage to the common denominator data of not homologous system by business-subject based on basic data warehouse；Analysis module, for the data definition data target stored for topic module and is maintained into target dimension table, and carries out data query and calculating based on Spark frameworks；Report development module, for the report demand provided according to user and combines topic module and analysis module progress report exploitation.The present invention improves the speed of report exploitation.
Description
Technical field
The present invention relates to technical field of data processing, in particular to a kind of report development system, report exploitation side
Method, storage medium and electronic equipment.
Background technology
In the big data epoch, development of the OA operation analysis to an enterprise plays a crucial role.Especially in medical row
In industry, huge supporting function is played in the analysis and processing result of the daily operation data of medical institutions, the decision-making to manager, and
The utilization rate of rare medical resource can be effectively improved.
With increasingly paying attention to medical and health care system, the situation of fast development has been presented in medical industry, and hospital internal is special
It is not the medical system up to tens in tertiary hospitals, in addition it is up to a hundred a, and these systems can all produce substantial amounts of business number daily
According to.The characteristics of business datum is that type complexity is various, and the generation frequency is higher, and data volume is big, and has many redundant datas.With
The development of Internet technology, these data increasingly area tends to high concentration, and large-scale data center is progressively set up, to sea
The demand for measuring the professional system of storage, processing and the displaying of data is increasingly urgent.
In addition, each business department may propose various report demands, backstage technological service inside medical institutions
Although department handles these demands as possible, however, still preferably cannot quickly tackle the demand of business department.It would therefore be highly desirable to
Need a kind of professional medical big data analysis system for rapidly and efficiently meeting business development.
In consideration of it, need a kind of report development system, report form developing method, storage medium and electronic equipment.
It should be noted that information is only used for strengthening the reason of the background to the present invention disclosed in above-mentioned background section
Solution, therefore can include not forming the information to the prior art known to persons of ordinary skill in the art.
The content of the invention
It is an object of the invention to provide a kind of report development system, report form developing method, storage medium and electronic equipment,
And then one or more problem caused by the limitation of correlation technique and defect is overcome at least to a certain extent.
According to an aspect of the present invention, there is provided a kind of report development system, including：
Basic data warehouse, for the data for the data of each source system integrate and after storage integration；
Topic module, for being classified based on basic data warehouse by business-subject to the common denominator data of not homologous system
Storage；
Analysis module, for the data definition data target stored for topic module and is maintained into target dimension table,
And data query and calculating are carried out based on Spark frameworks；
Report development module, report demand and combination topic module and analysis module for being provided according to user are reported
Table is developed.
Alternatively, report development module includes：
Demand acquiring unit, for obtaining the report demand of user；
Data type judging unit, for determining report data type according to report demand；
General character report development block, for judging that report data type is common denominator data in data type judging unit
When, the corresponding data target of report data is incorporated into user self-help development platform for user's self-developing report；
Individual character report development block, for judging that report data type is personality data in data type judging unit
When, report demand is synchronously deployed to exploitation terminal and user terminal so that developer and user combine topic module and analysis
Module cooperative develops report.
Alternatively report development module further includes：
Data type conversion unit, for when the frequency of occurrences of personality data is more than a threshold value, personality data to be changed
For common denominator data.
Alternatively, analysis module includes：
Spark computing units, for receiving query statement and query statement being analyzed to generate one group of RDD, judge
It whether there is sequential instructions in query statement, if there is no sequential instructions, then perform the corresponding tasks of each RDD parallel and export
Implementing result；If there is sequential instructions, then the indexed sequential based on the corresponding tasks of each RDD performs the corresponding tasks of each RDD,
And by indexed sequential output implementing result.
According to an aspect of the present invention, there is provided a kind of report form developing method, including：
By basic data warehouse the data of each source system integrate with the data after simultaneously storage integration；
Classification storage is carried out to the common denominator data of not homologous system by business-subject based on basic data warehouse；
Definition is carried out the data target of the data of classification storage by business-subject and is maintained into target dimension table, is based on
Spark frameworks carry out data query and calculating；
The report demand and combination provided according to user is reported by the data and Spark frameworks of business-subject classification storage
Table is developed.
Alternatively, the report demand and combination that are provided according to user press the data and Spark framves of business-subject classification storage
Structure, which carries out report exploitation, to be included：
Obtain the report demand of user；
Report data type is determined according to report demand；
When report data type is common denominator data, the corresponding data target of report data is incorporated into user self-help exploitation
For user's self-developing report on platform；
When report data type is personality data, report demand is synchronously deployed to exploitation terminal and user terminal, with
The data and Spark framework co-development reports by business-subject classification storage are utilized for developer and user.
Alternatively, report form developing method further includes：
When the frequency of occurrences of personality data is more than a threshold value, personality data is converted into common denominator data.
Alternatively, carrying out data query and calculating based on Spark frameworks includes：
Receive query statement and query statement is analyzed to generate one group of RDD；
Judge to whether there is sequential instructions in query statement；
If there is no sequential instructions, then the corresponding tasks of each RDD are performed parallel and export implementing result；
If there is sequential instructions, then the indexed sequential based on the corresponding tasks of each RDD performs the corresponding tasks of each RDD,
And by indexed sequential output implementing result.
According to an aspect of the present invention, there is provided a kind of storage medium, is stored thereon with computer program, computer program
The report form developing method of above-mentioned any one is realized when being executed by processor.
According to an aspect of the present invention, there is provided a kind of electronic equipment, including：
Processor；And
Memory, for storing the executable instruction of processor；
Wherein, processor is configured to perform the report form developing method of above-mentioned any one via executable instruction is performed.
In the technical solution that some embodiments of the present invention are provided, on the one hand, by basic data warehouse to data
Integration storage is carried out, avoids data collision and redundancy, data access speed can be improved；On the other hand, topic module is passed through
Data are subjected to classification storage by business-subject, the influence to system architecture can be changed to avoid frequent demand, it is ensured that number
According to the stability of logic；Another further aspect, in analysis module, to data definition data target, specification data standard can be true
The uniformity of data is protected, in addition, carrying out data query and calculating by Spark frameworks, substantially increases data query and calculating
Response speed；Another aspect, in report development module, can carry out report exploitation, increase according to the report demand of user
The flexibility of development process and saving is exploited natural resources.
It should be appreciated that the general description and following detailed description of the above are only exemplary and explanatory, not
The disclosure can be limited.
Brief description of the drawings
Attached drawing herein is merged in specification and forms the part of this specification, shows the implementation for meeting the present invention
Example, and for explaining the principle of the present invention together with specification.It should be evident that drawings in the following description are only the present invention
Some embodiments, for those of ordinary skill in the art, without creative efforts, can also basis
These attached drawings obtain other attached drawings.In the accompanying drawings：
Fig. 1 shows the configuration diagram of the data warehouse of some current technologies；
Fig. 2 diagrammatically illustrates the block diagram of report development system according to an illustrative embodiment of the invention；
Fig. 3 diagrammatically illustrates the block diagram of analysis module according to an illustrative embodiment of the invention；
Fig. 4 diagrammatically illustrates the block diagram of report development module according to an illustrative embodiment of the invention；
Fig. 5 diagrammatically illustrates the block diagram of another report development module according to an illustrative embodiment of the invention；
Fig. 6 diagrammatically illustrates the flow chart of report form developing method according to an illustrative embodiment of the invention；
Fig. 7 diagrammatically illustrate according to an illustrative embodiment of the invention based on Spark frameworks carry out data query
With the flow chart of calculating；
Fig. 8 diagrammatically illustrates the flow chart of report development process according to an illustrative embodiment of the invention；
Fig. 9 diagrammatically illustrates the side of an embodiment of report development frame according to an illustrative embodiment of the invention
Block diagram；
Figure 10 shows the schematic diagram of storage medium according to an illustrative embodiment of the invention；And
Figure 11 diagrammatically illustrates the block diagram of electronic equipment according to an illustrative embodiment of the invention.
Embodiment
Example embodiment is described more fully with referring now to attached drawing.However, example embodiment can be with a variety of shapes
Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, these embodiments are provided so that the disclosure will more
Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.Described feature, knot
Structure or characteristic can be incorporated in one or more embodiments in any suitable manner.In the following description, there is provided permitted
More details fully understand embodiments of the present invention so as to provide.It will be appreciated, however, by one skilled in the art that can
Omitted with putting into practice technical scheme one or more in the specific detail, or others side can be used
Method, constituent element, device, step etc..In other cases, be not shown in detail or describe known solution to avoid a presumptuous guest usurps the role of the host and
So that each side of the disclosure thickens.
In addition, attached drawing is only the schematic illustrations of the disclosure, it is not necessarily drawn to scale.Identical attached drawing mark in figure
Note represents same or similar part, thus will omit repetition thereof.Some block diagrams shown in attached drawing are work(
Can entity, not necessarily must be corresponding with physically or logically independent entity.These work(can be realized using software form
Energy entity, or these functional entitys are realized in one or more hardware modules or integrated circuit, or at heterogeneous networks and/or place
These functional entitys are realized in reason device device and/or microcontroller device.
Flow chart shown in attached drawing is merely illustrative, it is not necessary to including all steps.For example, the step of having
The step of can also decomposing, and having, can merge or part merges, therefore the order actually performed is possible to according to actual conditions
Change.
Present disclosure will be described by taking the report exploitation in medical system as an example below, it being understood, however, that
, report development system disclosed by the invention and method can also be applied to report exploitation and the data query point of other field
During analysis, particular determination is not done in this illustrative embodiment to this.
In some technologies, generally use data warehouse technology carries out storage analysis to medical data.At present, data warehouse
Three layer data structures of technology generally use, specifically, three layer data structures can include service source system, data warehouse and application
Fairground.As shown in Figure 1, on the one hand, service source system can include but is not limited to business source system data 111, service source system
Data 112, business source system data 113 and business source system data 114, these source system datas usually require manually to be tieed up
Shield；On the other hand, the data in service source system can be obtained by data warehouse 120, and data warehouse 120 can be by the number of acquisition
According to progress unified integration, the data set that it can be a subject-oriented, integrated, metastable, reflecting history changes
Close.By data warehouse 120, can save needs to go to the mistake that homologous system is not acquired when data carry out Conjoint Analysis
Journey；Another further aspect, data warehouse 120 can by the data sending of itself storage to using fairground 131, using fairground 132 and/or
Using fairground 133 so as to these data of concrete application.
At present, a kind of HBase databases of generally use Hadoop (distributed system framework) platform construction pass to substitute
The affairs type data warehouse of system.HBase databases support the storage analysis of mass data and have good autgmentability, Ke Yi
Data analysis and display module are established in HBase Basis of Database, forms operating statement analysis system.However, to medical data
Integrated, analysis and displaying still suffer from problems with：On the one hand, business datum is directly exposed to operating statement by data warehouse
System carries out data analysis, causes business datum and the display data degree of coupling higher, between operating statement internal system module
Data dependency is stronger, and the data target calculated cannot be multiplexed, and reduces the interactive efficiency of system；On the other hand, in report
During displaying, user often it is expected that when point opens a report quick response can be obtained, especially in mobile terminal, because
This faces mass data, and computational efficiency is can not be ignored the problem of, but current operating statement system lacks special place
Reason computing module, or computing module are less efficient；Another further aspect, medical industry development is swift and violent, and enterprise operation situation is changeable,
Business department may be eager to obtain certain class report, and report development mode cannot meet the needs of business department at present, treat technology
After the completion of department develops report, the time point of the optimal demand of business department may be missed.
In consideration of it, the present invention provides a kind of report development system.
Fig. 2 diagrammatically illustrates the block diagram of the report development system of the illustrative embodiments of the present invention.With reference to figure 2,
The report development system 2 can include basic data warehouse 21, topic module 23, analysis module 25 and report development module
27.Each module in report development system 2 will be described in detail below.
Basic data warehouse 21, can be used for the data of each source system integrate the data after simultaneously storage integration.
What is stored in each source system is the flow data during business is carried out, and by taking medical system as an example, these flows can
Examine, prescribe, pay the fees, get it filled to include but not limited to register, see.Except HIS (Hospital Information System,
Hospital information system) outside, user may use Physical Examination System and/or financial system at the same time, between these systems there may be
The problem of data encoding is repeated, even conflicted.
In an exemplary embodiment of the present invention embodiment, basic data warehouse 21 can be according to a data model by each source system
Data pick-up come out, and according to third normal form modeling rule tissue data, then, filtering and whole is carried out according to data characteristics
Close.Wherein, data model can be by developer's sets itself and the relevant model of actual traffic data, and the number
It is corresponding with the data model according to feature.Such processing solves the problems, such as data collision, and the data stored at this time do not increase,
Only storage form is changed, and memory space is taken without extra.
The basic data warehouse 21 of the present invention can be based on Hadoop platform and build, and can pass through HBase data stocks
Data after storage experience data model integration.In addition, the present invention can also integrate MongoDB databases.Specifically, the business of being directed to
Type data characteristics, formulate corresponding data filtering criterion in advance, improve the quality of data, and source system data is changed,
Store in HBase databases；For the data of non-relational, MongoDB databases can also be stored, it is not necessary to create in advance
Data structure is built, can support abundant inquiry, while index can be created, one efficient inquiry plan of corresponding generation.
Integration storage is carried out to data by basic data warehouse, data collision and redundancy is avoided, data can be improved
Access speed.
Topic module 23, can be used for the common denominator data by business-subject to not homologous system based on basic data warehouse 21
Carry out classification storage.
For medical system, business-subject can include but is not limited to client's theme, performance theme, operation theme, serious disease
Predict theme, common subject matter etc..Topic module 23 can be taken out the common denominator data of not homologous system based on basic data warehouse 21
Take out, be further by some field combinations in the table or table that belong to same analysis theme in same data source together
Visualized operation provides basic element.Business datum is stored by business-subject, rather than passes through application or application demand
Tissue storage is carried out, it is such to have an advantage that the stability for ensureing mathematical logic, more become even if frequent or subversive demand
System architecture is not interfered with.
It should be appreciated that basic data warehouse 21 and topic module 23 on the data store difference lies in：On the one hand,
Basic data warehouse 21 is responsible for the data of each service source system carrying out effective classification storage, and topic module 23 is in basic data
On the basis of warehouse 21, the common denominator data of not homologous system is integrated, establishes standard, solves Data duplication processing, data orphan
The problem of island；On the other hand, basic data warehouse 21, which corresponds to source system data, creates database purchase, and topic module 23 needs
To be designed according to business demand document or system architecture etc., by complete system of systems, concentrate and create different themes, go forward side by side
Row synchronous processing and deployment；Another further aspect, basic data warehouse 21 and topic module 23 are relatively isolated in physical store,
What basic data warehouse 21 stored is each source system partial data, and what topic module 23 was stored is during business development
The common denominator data being derived, both separate storages, avoids data redundancy, there is provided data access speed.
Closed in addition, topic module 23 can include but is not limited to business object, service attribute, filter and business-subject table
System etc..Wherein, business object is to form the basic element of business-subject, and business object can be with nested service object, except the first order
Outside business object, remaining business object can be with new business subobject；Service attribute is the basic component of business object,
Equivalent to the field in table, the newly-built of service attribute, editor can be carried out in business-subject battery limits and is deleted；Filter is industry
Business Attribute expression, it can be arithmetic or SQL expression；For business-subject table relation, had entirely according to system option
Office's relation and local table relation, are set by table relation, form the theme fairground finally with logical relation.
Analysis module 25, can be used for the data definition data target for topic module storage and is maintained into target dimension
In table, and data query and calculating are carried out based on Spark frameworks.
Medical field data type is various, and data name is highly professional, there is a situation where that many data implications are closer to,
In order to ensure that manager, policymaker and a line service personnel are mentioned that same problem, it is necessary to establish data standard, unified number
According to specification.
Analysis module 25 can establish index definition.Specifically, can be to the data definition number that is stored in topic module 23
According to index, still by taking medical system as an example, data target can include but is not limited to index name, index grade, calculate frequency, table
Up to formula and metering units etc..Then, these data targets can be maintained into a target dimension table, which can be with
In the memory space of analysis module 25, other memory spaces can also be located at, this is not done in this illustrative embodiment
Particular determination.Furthermore it is also possible to control of authority is carried out to the target dimension table, that is to say, that the only personnel with corresponding authority
The target dimension table could be managed.
By being maintained into data definition data target, and by data target in target dimension table, specification data standard,
It may insure the uniformity of data.
In addition, the MapReduce Computational frames that Hadoop is provided can analyze mass data, but this processing mode is still
It is slower there are response speed, it is impossible to the problem of preferably meeting active user's demand.In consideration of it, with reference to figure 3, analysis of the invention
Module 25 can also include Spark computing units 301.
Specifically, Spark computing units 301 can be used for receiving query statement and query statement be analyzed to generate
One group of RDD (Resilient Distributed Dataset, elasticity distribution formula data set), judges whether deposited in query statement
In sequential instructions, if there is no sequential instructions, then the corresponding tasks of each RDD are performed parallel and export implementing result；If deposit
In sequential instructions, then the indexed sequential based on the corresponding tasks of each RDD performs the corresponding tasks of each RDD, and it is defeated to press indexed sequential
Go out implementing result.
Data query and calculating are carried out by Spark frameworks, substantially increase data query and the response speed calculated.
Report development module 27, can be used for report demand and combination topic module 23 and the analysis mould provided according to user
Block 25 carries out report exploitation.
With reference to figure 4, report development module 27 can include demand acquiring unit 401, data type judging unit 403, be total to
Property report development block 405 and individual character report development block 407, wherein：
Demand acquiring unit 401, can be used for the report demand for obtaining user；
Data type judging unit 403, can be used for determining report data type according to report demand；
General character report development block 405, can be used for judging that report data type is common in data type judging unit
During property data, the corresponding data target of report data is incorporated into user self-help development platform for user's self-developing report
Table；
Individual character report development block 407, can be used for judging that report data type is a in data type judging unit
Property data when, by report demand synchronously be deployed to exploitation terminal and user terminal so that developer and user combine topic module
With analysis module co-development report.
For general character report development block 405, since topic module 23 has carried out classified and stored to common denominator data, mould is analyzed
Block 25 establishes corresponding index definition and it is calculated by Spark modules, and therefore, user need to only open in developer
Pass through simple data screening on the self-service platform of hair, you can quickly develop the report of oneself needs.In addition, for user's
Specifically used process, on the basis of semantic model, can carry out the flexible self-service query of data, and can use section, bore
Take, intersect, folding, data are analyzed in early warning, sequence etc., it is not necessary to user has the professional technique that report is developed, as long as
Solve business demand, you can complete report exploitation.
Specific process can include：It is possible, firstly, to carry out data source connection and setting, mainly connected including data source,
Add table, semantic layer definition, table relational view；Then, business-subject can be created；Next, can create combinatory analysis and
Perspective analysis, it is only necessary to the business datum and analysis mode for selecting oneself to need on interface, you can establishment combinatory analysis, and
On the basis of combinatory analysis, the multidimensional analysis operation such as brill, lower brill, section in selection, forms to have an X-rayed and analyzes；It is then possible to issue clear
Look at, after the completion of report creates, can be sent out in resource issue by selecting the modes such as computer theme, tablet theme, mobile phone theme
Cloth can also carry out resource authorization to different browsing terminals, and while issue, and different power are distributed for different user
Limit, and then improve the security of data.
For individual character report development block 407, developed by developer, user coordinates progress requirement validation and test to test
Card, according to the diversified demand of user, developer can carry out cartographic analysis, instrumental analysis, electricity in module is developed jointly
Sublist case analysis etc., on the basis of basic data warehouse 21, with reference to topic module 23 and analysis module 25, iteratively faster exploitation
Complete the demand of user.
With reference to figure 5, compared to report development module 27, report development module 51, which is removed, includes demand acquiring unit 401, data
Outside type judging unit 403, general character report development block 405 and individual character report development block 407, data type can also be included
Converting unit 501, wherein：
Data type conversion unit 501, can be used for when the frequency of occurrences of personality data is more than a threshold value, by described
Property data are converted to common denominator data.Wherein, the threshold value can by developer according to practical business situation sets itself, for example,
The threshold value can be ten times a day, that is to say, that, can be by the individual character number if a personality data occurred 10 times in one day
According to being converted to common denominator data.Thus, individual character report development block 407 can switch to general character report development block 405, Yong Huke
Can voluntarily be developed.
In the report development system of the illustrative embodiments of the present invention, on the one hand, pass through basic data warehouse logarithm
According to integration storage is carried out, data collision and redundancy are avoided, data access speed can be improved；On the other hand, theme mould is passed through
Data are carried out classification storage by block by business-subject, and the influence to system architecture can be changed to avoid frequent demand, it is ensured that
The stability of mathematical logic；Another further aspect, in analysis module, to data definition data target, specification data standard can be with
Ensure the uniformity of data, in addition, carrying out data query and calculating by Spark frameworks, substantially increase data query and meter
The response speed of calculation；Another aspect, in report development module, can carry out report exploitation according to the report demand of user, can
Exploited natural resources with increasing the flexibility of development process and saving.
Further, a kind of report form developing method is additionally provided in this example embodiment.
Fig. 6 diagrammatically illustrates the flow chart of report form developing method according to an illustrative embodiment of the invention.With reference to
Fig. 6, report form developing method of the invention may comprise steps of：
S60. by basic data warehouse the data of each source system integrate with the data after simultaneously storage integration.
In an exemplary embodiment of the present invention embodiment, basic data warehouse can be according to a data model by each source system
Data pick-up comes out, and according to third normal form modeling rule tissue data.Then, it is special according to data corresponding with the data model
Sign is filtered and integrated, and the data after storage integration.In addition, basic data warehouse can be based on Hadoop platform and structure
Build, and the data after integration can be stored to HBase databases or MongoDB databases.
Integration storage is carried out to data by basic data warehouse, data collision and redundancy is avoided, data can be improved
Access speed.
S62. classification storage is carried out to the common denominator data of not homologous system by business-subject based on basic data warehouse.
The common denominator data of not homologous system can be extracted based on basic data warehouse, will belonged in same data source
Some field combinations together, basic element are provided for further visualized operation in the table or table of same analysis theme.Will
Business datum is stored by business-subject, rather than carries out tissue storage by application or application demand, and such benefit exists
In the stability for ensureing mathematical logic, even if frequent or subversive demand, which more becomes, will not influence system architecture.
S64. define the data target by the data of business-subject progress classification storage and be maintained into target dimension table, and
Data query and calculating are carried out based on Spark frameworks.
By being maintained into data definition data target, and by data target in target dimension table, specification data standard,
It may insure the uniformity of data.
In addition, with reference to figure 7, data query is carried out based on Spark frameworks to the present invention and the process calculated carries out example
Property explanation.
In step s 701, user can be according to the self-defined SQL query statement of self-demand；, can be with step S703
By the corresponding module of SQL query statement input Spark frameworks；In step S705, the data of Spark application programs can be called
The SQL query statement is sent to Spark application programs by input interface；In step S707, Spark can be to the SQL query
Sentence carries out syntactic analysis, one concordance list of generation can be corresponded to when generating one group of RDD sequence, and generating this group of RDD, for depositing
Store up each Job and its index value, each RDD corresponds to a Job, represents the once-through operation to data, after the completion of all Job,
It can complete once complete inquiry；In step S709, Job is generated, Job is submitted into an eventProcessActor (events
Handle actuator), and call the interface of Spark to submit Job, each Job to correspond to a Task.In step S711, carry out
Syntactic analysis, judges to submit whether the SOL query statements of Job have Order By (i.e. above mentioned sequential instructions), if so,
Then step jumps to step S713, if it is not, step jumps to step S723；, it is necessary to judge Task in step S713
Corresponding index value；In step S715, according to the index value determined, if index value is different, by index value from it is small to
Big order performs, if index value is identical, each Task is performed parallel；In step S717, judgement has just performed Task pairs
Answer whether index value is the next bit for exporting result index value, if it is, step jumps to step S727, if it is not, then
Step jumps to step S719；In step S719, index value can be stored in memory temporarily；In step S721, such as
During the corresponding index values of the Task that is discharged in memory of fruit output index value, step jumps to step S727；In step S727, directly
Connect the SQL output modules for being output to Spark；In addition, in step S723, each Task can be performed parallel；In step S725
In, after the completion of each Task, notify the Context of Spark；In step S729, query result can be fed back to use successively
Family；In step S731, after all Task are exported, whole poll-final.
By above-mentioned flow, the response speed of inquiry can be greatly improved.In addition, when user-defined SQL query is
During simple unordered inquiry, huge data volume is segmented into multiple Task and performs parallel, and the condition of satisfaction can export immediately, such as
Fruit is complicated orderly inquiry, can also be exported in order, it is not necessary to Deng Daosuo according to the index value table generated when decomposing Job
Just exported after the completion of having Task all, not only avoided data spilling, but also inquiry response speed can be improved.
S66. according to user provide report demand and combine by business-subject classification storage data and Spark frameworks into
Row report is developed.
Specifically, it is possible, firstly, to obtain the report demand of user；Then, report data can be determined according to report demand
Type；Next, when it is common denominator data to judge report data type, the corresponding data target of report data can be integrated
, can when it is personality data to judge report data type for user's self-developing report on to user self-help development platform
Report demand to be synchronously deployed to exploitation terminal and user terminal, so that developer and user utilize and classify by business-subject
The data and Spark framework co-development reports of storage.
In addition, when the frequency of occurrences of personality data is more than a threshold value, personality data can be converted into common denominator data.Its
In, which can be developer according to historical data or the frequency threshold of experience sets itself, this illustrative embodiment
In particular determination is not done to this.
Illustrated with reference to the process that figure 8 develops report.In step S801, report demand can be obtained；In step
In S803, it can be determined that report data type, if personality data, then step can jump to step S807, if altogether
Property data, then step can jump to step S805；In step S805, the target dimension that can be specified according to developer
Table, self-service exploitation is carried out by simple screening (in operation, screening can be realized by way of pulling)；In step S807,
User can coordinate developer's co-development, test；In step S809, the process to report resource authorization can be carried out；
In step S811, report resource can be issued at the same time by PC ends and mobile terminal.In addition, when the personality data frequency of occurrences is more than
During one threshold value, which can be converted to common denominator data.
In the report form developing method of the illustrative embodiments of the present invention, on the one hand, pass through basic data warehouse logarithm
According to integration storage is carried out, data collision and redundancy are avoided, data access speed can be improved；On the other hand, data are pressed into industry
Theme of being engaged in carries out classification storage, can change influence to system architecture to avoid frequent demand, it is ensured that mathematical logic it is steady
It is qualitative；Another further aspect, to data definition data target, specification data standard, it can be ensured that the uniformity of data, in addition, logical
Cross Spark frameworks and carry out data query and calculating, substantially increase data query and the response speed calculated；Another aspect, can
To carry out report exploitation according to the report demand of user, add the flexibility of development process and save and exploit natural resources.
It should be noted that although describing each step of method in the disclosure with particular order in the accompanying drawings, still, this is simultaneously
Undesired or hint must perform these steps according to the particular order, or have to carry out the step ability shown in whole
Realize desired result.It is additional or alternative, it is convenient to omit multiple steps are merged into a step and performed by some steps,
And/or a step is decomposed into execution of multiple steps etc..
Fig. 9 diagrammatically illustrates the side of an embodiment of report development frame according to an illustrative embodiment of the invention
Block diagram.The embodiment by taking medical system as an example, wherein, the framework can include management platform 90, source system 91, enterprise's number
According to warehouse (EDW) 92, development platform 93, application platform 94, terminal 95 and user 96 etc..Specifically, source system 91 can include
HIS, EMR (Electronic Medical Record, electronic medical record record), LIS (Laboratory in medical system
Information System, clinical laboratory's information system), PACS (Picture Archiving and Communication
Systems, Picture Archiving and Communication System) etc.；Data Warehouse for Enterprises 92 can include technical interface layer, normal data
Layer, topic module and analysis module, wherein, topic module can include Data Integration layer and public collect layer, analysis module again
It can include service logic unit and Data Computation Unit again；Development platform 93 can include self-service development module, joint development
Module, authorization module and release module；Application platform 94 can include enterprise report, cockpit, performance analysis etc.；Terminal 95 can
With including PC, mobile phone and other mobile terminals；User 96 can include decision-making level, management level and operation layer, etc..
According to one embodiment of present invention, for a secondary rehabilitation hospital, it is possible, firstly, to by inside convalescent home
The operation system data such as HIS, LIS, PACS, EMR, rehabilitation system, long-term care service system are all integrated into data warehouse,
Data volume can reach TB grades；Next, in topic module according to the scope of business and business side's demand on data warehouse
Establish outpatient service, be in hospital, physical examination, rehabilitation, the different theme submodule such as long-term care, on the basis of submodule, comb data
Index more than 500, forms target dimension table, and data processing and calculating are carried out by Spark instruments.In this embodiment, amount to
15 more than 100 position business personnels of department develop 94 reports in report development module, and technical staff develops 39 reports,
The dimension of the report display data of exploitation is more rich than before.In addition, for example, developing a report before needs cost requirements people
Member, designer, developer amount to 4 day time, and only needed using report development system of the present invention one day can be complete
Into exploitation, the work efficiency of enterprise staff is not only increased, and preferably supports the needs of business development, conveniently and efficiently
Rational decision support is provided for enterprise management level.
In an exemplary embodiment of the present invention, a kind of computer-readable recording medium is additionally provided, is stored thereon with energy
Enough realize the program product of this specification above method.In some possible embodiments, various aspects of the invention may be used also
In the form of being embodied as a kind of program product, it includes program code, when described program product is run on the terminal device, institute
State program code be used for make the terminal device perform described in above-mentioned " illustrative methods " part of this specification according to this hair
The step of bright various illustrative embodiments.
Refering to what is shown in Fig. 10, describe the program product for being used for realization the above method according to the embodiment of the present invention
1000, it can use portable compact disc read only memory (CD-ROM) and including program code, and can in terminal device,
Such as run on PC.However, the program product not limited to this of the present invention, in this document, readable storage medium storing program for executing can be with
Be it is any include or the tangible medium of storage program, the program can be commanded execution system, device either device use or
It is in connection.
Described program product can use any combination of one or more computer-readable recording mediums.Computer-readable recording medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or any combination above.The more specifically example of readable storage medium storing program for executing is (non exhaustive
List) include：It is electrical connection, portable disc, hard disk, random access memory (RAM) with one or more conducting wires, read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
Computer-readable signal media can be including the data-signal in a base band or as carrier wave part propagation, its
In carry readable program code.The data-signal of this propagation can take various forms, include but not limited to electromagnetic signal,
Optical signal or above-mentioned any appropriate combination.Readable signal medium can also be any readable Jie beyond readable storage medium storing program for executing
Matter, which can send, propagate either transmission be used to be used by instruction execution system, device or device or and its
The program of combined use.
The program code included on computer-readable recording medium can be transmitted with any appropriate medium, including but not limited to wirelessly, be had
Line, optical cable, RF etc., or above-mentioned any appropriate combination.
It can be write with any combination of one or more programming languages for performing the program that operates of the present invention
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
Perform on computing device, partly perform on a user device, the software kit independent as one performs, is partly calculated in user
Its upper side point is performed or performed completely in remote computing device or server on a remote computing.It is remote being related to
In the situation of journey computing device, remote computing device can pass through the network of any kind, including LAN (LAN) or wide area network
(WAN), user calculating equipment is connected to, or, it may be connected to external computing device (such as utilize ISP
To pass through Internet connection).
In an exemplary embodiment of the present invention, a kind of electronic equipment that can realize the above method is additionally provided.
Person of ordinary skill in the field it is understood that various aspects of the invention can be implemented as system, method or
Program product.Therefore, various aspects of the invention can be implemented as following form, i.e.,：It is complete hardware embodiment, complete
The embodiment combined in terms of full Software Implementation (including firmware, microcode etc.), or hardware and software, can unite here
Referred to as " circuit ", " module " or " system ".
The electronic equipment 1100 of this embodiment according to the present invention is described referring to Figure 11.The electricity that Figure 11 is shown
Sub- equipment 1100 is only an example, should not bring any restrictions to the function and use scope of the embodiment of the present invention.
As shown in figure 11, electronic equipment 1100 is showed in the form of universal computing device.The component of electronic equipment 1100 can
To include but not limited to：Above-mentioned at least one processing unit 1110, above-mentioned at least one storage unit 1120, connection different system
The bus 1130 of component (including storage unit 1120 and processing unit 1110), display unit 1140.
Wherein, the storage unit has program stored therein code, and said program code can be held by the processing unit 1110
OK so that the processing unit 1110 performs various according to the present invention described in above-mentioned " illustrative methods " part of this specification
The step of illustrative embodiments.For example, the processing unit 1110 can perform step S60 as shown in Figure 6：Pass through base
The data of each source system integrate plinth data warehouse and the data after storage integration；Step S62：Based on basic data warehouse
Classification storage is carried out to the common denominator data of not homologous system by business-subject；Step S64：Definition carries out classification by business-subject and deposits
The data target of the data of storage is simultaneously maintained into target dimension table, and data query and calculating are carried out based on Spark frameworks；Step
S66：The report demand and combination provided according to user carries out report by the data and Spark frameworks of business-subject classification storage and opens
Hair.
Storage unit 1120 can include the computer-readable recording medium of volatile memory cell form, such as Random Access Storage Unit
(RAM) 11201 and/or cache memory unit 11202, it can further include read-only memory unit (ROM) 11203.
Storage unit 1120 can also include program/utility with one group of (at least one) program module 11205
11204, such program module 11205 includes but not limited to：Operating system, one or more application program, other programs
Module and routine data, may include the realization of network environment in each or certain combination in these examples.
Bus 1130 can be the one or more in a few class bus structures of expression, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use any bus structures in a variety of bus structures
Local bus.
Electronic equipment 1100 can also be with one or more external equipments 1200 (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, the equipment communication interacted with the electronic equipment 1100 can be also enabled a user to one or more, and/or with making
Obtain any equipment that the electronic equipment 1100 can communicate with one or more of the other computing device (such as router, modulation
Demodulator etc.) communication.This communication can be carried out by input/output (I/O) interface 1150.Also, electronic equipment 1100
Network adapter 1160 and one or more network (such as LAN (LAN), wide area network (WAN) and/or public affairs can also be passed through
Common network network, such as internet) communication.As shown in the figure, network adapter 1160 passes through its of bus 1130 and electronic equipment 1100
Its module communicates.It should be understood that although not shown in the drawings, can combine electronic equipment 1100 uses other hardware and/or software
Module, includes but not limited to：Microcode, device driver, redundant processing unit, external disk drive array, RAID system, magnetic
Tape drive and data backup storage system etc..
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can be realized by software, can also be realized by way of software is with reference to necessary hardware.Therefore, according to the disclosure
The technical solution of embodiment can be embodied in the form of software product, the software product can be stored in one it is non-volatile
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server, terminal installation or network equipment etc.) is performed according to disclosure embodiment
Method.
In addition, above-mentioned attached drawing is only schematically saying for the processing included by method according to an exemplary embodiment of the present invention
It is bright, rather than limitation purpose.It can be readily appreciated that the time that above-mentioned processing shown in the drawings was not intended that or limited these processing is suitable
Sequence.In addition, being also easy to understand, these processing for example can be performed either synchronously or asynchronously in multiple modules.
It should be noted that although some modules or list of the equipment for action executing are referred in above-detailed
Member, but this division is not enforceable.In fact, according to embodiment of the present disclosure, it is above-described two or more
Either the feature of unit and function can embody module in a module or unit.A conversely, above-described mould
Either the feature of unit and function can be further divided into being embodied by multiple modules or unit block.
Those skilled in the art will readily occur to the disclosure its after considering specification and putting into practice invention disclosed herein
His embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Adaptive change follow the general principle of the disclosure and including the undocumented common knowledge in the art of the disclosure or
Conventional techniques.Description and embodiments are considered only as exemplary, and the true scope and spirit of the disclosure are by claim
Point out.
It should be appreciated that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by appended claim.
Claims (10)
- A kind of 1. report development system, it is characterised in that including：Basic data warehouse, for the data for the data of each source system integrate and after storage integration；Topic module, for being classified based on the basic data warehouse by business-subject to the common denominator data of not homologous system Storage；Analysis module, for the data definition data target stored for the topic module and is maintained into target dimension table, And data query and calculating are carried out based on Spark frameworks；Report development module, for the report demand that is provided according to user and with reference to the topic module and the analysis module into Row report is developed.
- 2. report development system according to claim 1, it is characterised in that the report development module includes：Demand acquiring unit, for obtaining the report demand of user；Data type judging unit, for determining report data type according to the report demand；General character report development block, for judging that report data type is common denominator data in the data type judging unit When, the corresponding data target of the report data is incorporated into user self-help development platform for user's self-developing report；Individual character report development block, for judging that report data type is personality data in the data type judging unit When, the report demand is synchronously deployed to exploitation terminal and user terminal so that developer and user are with reference to the theme mould Block and the analysis module co-development report.
- 3. report development system according to claim 2, it is characterised in that the report development module further includes：Data type conversion unit, for when the frequency of occurrences of personality data is more than a threshold value, the personality data to be changed For common denominator data.
- 4. report development system according to claim 1, it is characterised in that the analysis module includes：Spark computing units, for receiving query statement and the query statement being analyzed to generate one group of RDD, judge It whether there is sequential instructions in the query statement, if there is no sequential instructions, then perform the corresponding tasks of each RDD parallel simultaneously Export implementing result；If there is sequential instructions, then each RDD of indexed sequential execution based on the corresponding tasks of each RDD is corresponding Task, and by indexed sequential output implementing result.
- A kind of 5. report form developing method, it is characterised in that including：By basic data warehouse the data of each source system integrate with the data after simultaneously storage integration；Classification storage is carried out to the common denominator data of not homologous system by business-subject based on the basic data warehouse；Definition is carried out the data target of the data of classification storage by business-subject and is maintained into target dimension table, based on Spark Framework carries out data query and calculating；The report demand and combination provided according to user carries out report by the data and Spark frameworks of business-subject classification storage and opens Hair.
- 6. report form developing method according to claim 5, it is characterised in that according to the report demand of user's offer and combine Carrying out report exploitation by the data and Spark frameworks of business-subject classification storage includes：Obtain the report demand of user；Report data type is determined according to the report demand；When report data type is common denominator data, the corresponding data target of the report data is incorporated into user self-help exploitation For user's self-developing report on platform；When report data type is personality data, the report demand is synchronously deployed to exploitation terminal and user terminal, with The data and Spark framework co-development reports by business-subject classification storage are utilized for developer and user.
- 7. report form developing method according to claim 6, it is characterised in that the report form developing method further includes：When the frequency of occurrences of personality data is more than a threshold value, the personality data is converted into common denominator data.
- 8. report form developing method according to claim 5, it is characterised in that based on Spark frameworks carry out data query and Calculating includes：Receive query statement and the query statement is analyzed to generate one group of RDD；Judge to whether there is sequential instructions in the query statement；If there is no sequential instructions, then the corresponding tasks of each RDD are performed parallel and export implementing result；If there is sequential instructions, then the indexed sequential based on the corresponding tasks of each RDD performs the corresponding tasks of each RDD, and presses The indexed sequential exports implementing result.
- 9. a kind of storage medium, is stored thereon with computer program, it is characterised in that the computer program is executed by processor Report form developing method any one of Shi Shixian claims 5 to 8.
- 10. a kind of electronic equipment, it is characterised in that including：Processor；AndMemory, for storing the executable instruction of the processor；Wherein, the processor is configured to come any one of perform claim requirement 5 to 8 via the execution executable instruction Report form developing method.
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Cited By (28)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108664638A (en) * | 2018-05-15 | 2018-10-16 | 口碑(上海)信息技术有限公司 | Report form generation method based on index system and device |
| CN109272223A (en) * | 2018-09-06 | 2019-01-25 | 广州微印信息科技有限公司 | One kind being based on section's purpose task cooperative system and method |
| CN109376147A (en) * | 2018-11-26 | 2019-02-22 | 浙江中智达科技有限公司 | A kind of data processing method and system |
| CN109617734A (en) * | 2018-12-25 | 2019-04-12 | 北京市天元网络技术股份有限公司 | Network operation capability analysis method and device |
| CN109634941A (en) * | 2018-11-14 | 2019-04-16 | 金色熊猫有限公司 | Medical data processing method, device, electronic equipment and storage medium |
| CN110458743A (en) * | 2019-08-12 | 2019-11-15 | 软通动力信息技术有限公司 | Community governance method, apparatus, equipment and storage medium based on big data analysis |
| CN110751575A (en) * | 2019-10-21 | 2020-02-04 | 中国民航信息网络股份有限公司 | Method and device for processing civil aviation passenger service data |
| CN110807016A (en) * | 2019-09-29 | 2020-02-18 | 北京淇瑀信息科技有限公司 | Data warehouse construction method and device applied to financial business and electronic equipment |
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1901477A (en) * | 2006-07-12 | 2007-01-24 | 华为技术有限公司 | Searching method and its system for equipment traffic data |
| US20080243785A1 (en) * | 2007-03-30 | 2008-10-02 | Tyron Jerrod Stading | System and methods of searching data sources |
| CN105608203A (en) * | 2015-12-24 | 2016-05-25 | Tcl集团股份有限公司 | Internet of things log processing method and device based on Hadoop platform |
| US20160162521A1 (en) * | 2014-12-08 | 2016-06-09 | Platfora, Inc. | Systems and Methods for Data Ingest in Interest-Driven Business Intelligence Systems |
| CN105912636A (en) * | 2016-04-08 | 2016-08-31 | 金蝶软件（中国）有限公司 | Map/Reduce based ETL data processing method and device |
| US20160321589A1 (en) * | 2012-06-05 | 2016-11-03 | Dimensional Insight Incorporated | Dynamic generation of guided pages |
| CN106294521A (en) * | 2015-06-12 | 2017-01-04 | 交通银行股份有限公司 | Date storage method and data warehouse |
| CN106682213A (en) * | 2016-12-30 | 2017-05-17 | Tcl集团股份有限公司 | Internet-of-things task customizing method and system based on Hadoop platform |
| US20170139674A1 (en) * | 2015-11-18 | 2017-05-18 | American Express Travel Related Services Company, Inc. | Systems and methods for tracking sensitive data in a big data environment |
| CN107168940A (en) * | 2017-03-29 | 2017-09-15 | 长春市万易科技有限公司 | A kind of report generating system and method |
| CN107193967A (en) * | 2017-05-25 | 2017-09-22 | 南开大学 | A kind of multi-source heterogeneous industry field big data handles full link solution |
-
2017
- 2017-11-15 CN CN201711127508.8A patent/CN107918600B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1901477A (en) * | 2006-07-12 | 2007-01-24 | 华为技术有限公司 | Searching method and its system for equipment traffic data |
| US20080243785A1 (en) * | 2007-03-30 | 2008-10-02 | Tyron Jerrod Stading | System and methods of searching data sources |
| US20160321589A1 (en) * | 2012-06-05 | 2016-11-03 | Dimensional Insight Incorporated | Dynamic generation of guided pages |
| US20160162521A1 (en) * | 2014-12-08 | 2016-06-09 | Platfora, Inc. | Systems and Methods for Data Ingest in Interest-Driven Business Intelligence Systems |
| CN106294521A (en) * | 2015-06-12 | 2017-01-04 | 交通银行股份有限公司 | Date storage method and data warehouse |
| US20170139674A1 (en) * | 2015-11-18 | 2017-05-18 | American Express Travel Related Services Company, Inc. | Systems and methods for tracking sensitive data in a big data environment |
| CN105608203A (en) * | 2015-12-24 | 2016-05-25 | Tcl集团股份有限公司 | Internet of things log processing method and device based on Hadoop platform |
| CN105912636A (en) * | 2016-04-08 | 2016-08-31 | 金蝶软件（中国）有限公司 | Map/Reduce based ETL data processing method and device |
| CN106682213A (en) * | 2016-12-30 | 2017-05-17 | Tcl集团股份有限公司 | Internet-of-things task customizing method and system based on Hadoop platform |
| CN107168940A (en) * | 2017-03-29 | 2017-09-15 | 长春市万易科技有限公司 | A kind of report generating system and method |
| CN107193967A (en) * | 2017-05-25 | 2017-09-22 | 南开大学 | A kind of multi-source heterogeneous industry field big data handles full link solution |
Non-Patent Citations (4)
| Title |
|---|
| BAO RONG CHANG等: "Optimized Multiple Platforms for Big Data Analysis", 《2016 IEEE SECOND INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM)》 * |
| XIUQIN LIN等: "Log analysis in cloud computing environment with Hadoop and Spark", 《2013 5TH IEEE INTERNATIONAL CONFERENCE ON BROADBAND NETWORK & MULTIMEDIA TECHNOLOGY》 * |
| 王志刚: "企业级数据中心设计与实践", 《信息技术与标准化》 * |
| 赵毅: "基于大数据平台构建数据仓库的研究与实践", 《中国金融电脑》 * |
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|---|---|---|---|---|
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