CN110515989A - A kind of data real-time statistical method based on financial data management platform - Google Patents
A kind of data real-time statistical method based on financial data management platform Download PDFInfo
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Abstract
The invention discloses a kind of data real-time statistical methods based on financial data management platform, comprising: A. initializes system, and B. user enters system, modifies newly-increased module data；C. in queue data setup module name as classification foundation；D. data summarization and enter server program, server obtain data return state；E. new thread is opened when the rate that data enter server program is greater than threshold value；F. it stores data into database and data is carried out to sentence weight；G. the monetary unit of the confirmed data that can summarize and currency symbol are taken out, modifies the value of initial data to the numerical value that can summarize；H. whether the material code for obtaining data, inquiring in summary sheet has this field；I. it will summarize data and obtain the new data needed to be added in table multiplied by weight, the data after this time being summarized.Method of the invention solves three difficulties for realizing System, to realize whole requirements that real-time financial data summarizes.
Description
Technical field
The present invention relates to technical field, in particular to a kind of data real-time statistics side based on financial data management platform
Method.
Background technique
Modern financial process is all to make cluster with structure as cloud center, still, the industry accessed with cloud center
Business system and business datum gradually increase, and all kinds of analysis indexes and performance assessment criteria also accordingly increase, it is necessary to be built by platform
It sets up one's own business and is engaged in a large amount of manual works of Modeling analysis operation system data means replacement to reach efficient management value, to need
Establish a set of data management platform.In platform, other than the demand that data are shown with report, it is frequently run onto needs efficiently, in fact
When the financial data for summarizing each module and show the cake chart for summarizing data or this demand of histogram.This demand tool
For body be exactly that user changes operation to carrying out respective additions and deletions in the system of disparate modules in modules, and summarize the page or
In person's summary sheet, when the data of some module change, summarizing here can show in real time its variation according to weight
Come.
There are three the technological difficulties of this demand.Difficult point first is that take into account when triggering summarize, that is, trigger summarize when
Between, the prior art be usually have modification just remove immediately to modify summary sheet and timing go full dose inquiry directly covering aggregate value both
Method, immediately change the present defect of this method of table be more people operate a table be easy to cause database there is affairs problem and by
Table is locked, follow-up data is caused to cannot be introduced into summarizing module.The defect of timing covering is just will appear if timed interval is big
Non real-time situation is not carried out real-time function, and a large amount of memory is needed if time interval is small to guarantee fixed cycle operator energy
It goes on smoothly, it is very big to the pressure of server, once other operations occur is easy to cause system failure.
Difficult point second is that summarize the repeated problem of data, for example certain row financial data that we increase newly several due to sentencing
It is judged as the case where having calculated that one time when summarizing before under the conditions of disconnected, or even can be judged in different summary views
To calculate multiple situation, just need to solve the problems, such as Data duplication when this；
Difficult point third is that as caused by the particularity of financial data, be exactly that data have weight when summarizing to judge data
Importance, different data weightings is different, and some is newly come in summarizes data and the shown data that summarize all can root
Change according to the modification of weight.
In the prior art in the method for going to solve difficult point two and difficult point three, all abandons and realize described in difficult point one immediately
The method for modifying summary sheet can not find aggregated data because immediately modification summary sheet does not have realization invertibity
Those are duplicate and which needs to be needed to modify because of weight modification.
The prior art all mainly uses timed task to go to summarize a kind of this method when facing the two difficult points, this
Kind method benefit is avoiding the problem of judgement repeats and judge modification weight, directly goes full dose to summarize, being equivalent to is every time
Most complete summarizes, and defect is identical with difficult point a period of time is solved, and the data volume summarized needs a large amount of memory just greatly to guarantee that timing is grasped
Work can be gone on smoothly, can be bigger to the pressure of server, it is easier to lead to system failure.Thus, Yao Shixian financial data is real
When summarize whole require and difficult point, emphasis are exactly to solve more people's operations to summarize appearance lag, data redundancy and data weighting
These three problems.
Summary of the invention
It is insufficient in above-mentioned background technique the purpose of the present invention is overcoming, a kind of number based on financial data management platform is provided
According to real-time statistical method, it is put forward for the first time the joint by queue technology, multithreading and Stored Procedure Technology these three technologies
It uses, solves three difficulties for realizing System, to realize whole requirements that real-time financial data summarizes.
In order to reach above-mentioned technical effect, the present invention takes following technical scheme:
A kind of data real-time statistical method based on financial data management platform, comprising the following steps:
A. initialize system, including one processing queue of initialization, a library Elasticsearch, a set of modules table,
Table is checked in a set of summary sheet and each system corresponding material code information；
B. user enters system, modifies newly-increased module data, and by the data assembling of modification in pairs as entering queue；
C. data setup module name increases renewal time attribute and whether complete newly to data object as classification foundation in queue
At status attribute, data sort first in first out by renewal time, obtain the more new state of data, will more new state with attribute format
It is put into data object；
D. data summarization and enter server program, server obtain data return state；
E. when the rate that data enter server program is greater than threshold value, open new thread, then multithread programs are opened,
Queue will be transmitted to program by current thread number and batch with the consistent data of Thread Count and enter thread pool, while to thread pool
In data handled；
F. it stores data into database and data is carried out to sentence weight；
G. by the monetary unit of the confirmed data that can summarize (such as a, ten thousand, hundred million etc.) and currency symbol (such as CNY,
USD etc.) it takes out and known unified monetary unit and symbol compare that (such as setting summarizes data unit and is unified for position
Several CNY currency), the value of initial data is modified to the numerical value that can summarize；
H. whether the material code for obtaining data, inquiring in summary sheet has this field, has and then enters in next step；
I. it is found after unified material code summarizes field in data, inquires this weight for summarizing data in summary sheet, it will
Summarize data and obtain the new data needed to be added in table multiplied by weight, new data is added in former data, is this time summarized it
Data afterwards；
For financial data System this problem is realized, the technical scheme is that in the feelings for not having to timed task
Under condition, three kinds of mode of storing process are write plus using database by using queue technology, written in code multi-threading
Technology is used in combination, the demand of Lai Shixian System data.This method does not have to the memory for considering server, avoids memory negative
Excessive problem is carried, while without in addition supporting using timed task server, processing efficiently, solves financial data and summarizes
The problem of multioperand being easy to appear judges according to lag, Data duplication and data weighting.
Further, the more new state of data includes newly-increased and modification in the step C.
Further, in the step D, when queue read data return state value be " success " when, then to data into
Row backs up and deletes in queue this data, if the return state value for reading data is " time-out is not fed back ", by data backup
Once, and Backup Data setting state be it is untreated, Backup Data re-enter into queue rear end original data delete, return step
Rapid C.
It further, is specifically that data are standby by the format progress of " module name+table name+attribute " when being backed up to data
Part.
It further, further include the key by " module name+table name+attribute " as data when being backed up to data, it will be right
As being put into the library Elasticsearch as value, and Ruo Kuli has the object key-value pair of same key, then directly overrides.
Further, the step F is specifically included:
F1. according to financial data it is necessary sentence weight condition assemble querying condition " module name+table name+attribute " inquiry clothes
Whether business device has the identical data other than notebook data；
F2. G is entered step if not, otherwise, judges the Update attribute of the data；
F3. G is entered step if the Update attribute of the data is " modification "；If the Update attribute of the data is " newly-increased ",
Then assert that the data are repeated data, is not involved in data summarization, then directly exits and return to " having repeated data ".
Further, it is described it is necessary sentence weight condition include company name, statistics month, section time.
Further, in the step H further include: if the material code of data can not inquire in summary sheet, obtain
The System Number for evidence of fetching, and inquire in the corresponding material code information inspection table of system initialized in advance corresponding
Unified material code, and the corresponding field of the material code is the field for needing to summarize, and enters step I, if in material
Code information checks that table does not inquire yet, then directly exits and return " without this material ", and the data are not involved in and summarize.
Further, when multithread programs are opened in the step E, the value of newly-increased Thread Count is that present rate divides exactly threshold
The value of value.
Compared with prior art, the present invention have it is below the utility model has the advantages that
Data real-time statistical method based on financial data management platform of the invention, on solving more people's operational issues,
Data queue is solved the problems, such as using multithreading；On solving the problems, such as data redundancy, data are carried out using queue technology
Sequence and classification, and the data operated are regard as key by " module name+table name+attribute ", module object is put as value
Enter Elasticsearch to be backed up, goes judgement to repeat using the Rule of judgment that acquisition queue comes is write in Stored Procedure Technology
It is repeated to solve the problems, such as；On solving the problems, such as data weighting, data weighting computational problem is realized using Stored Procedure Technology,
Meanwhile it can also be plus the transaction operation to summary sheet come the problem of preventing lock table in writing storing process；Do not having to
In the case where timed task, adds by using queue technology, the specific multi-threading of written in code and write using database
The advantages of mode that specific three kinds of technologies of storing process combine, the demand of Lai Shixian System data, this method is
The memory situation for considering server can not be had to, to avoid the problem that memory load excessive, while without other using fixed
When task server support so that processing is more efficient, while also controlling cost；It and is not that will summarize pressure to be placed on server
On, but by by the combined use method of the multithreading of queue technology, code and database purchase process technology come real
Existing function is, it can be achieved that summarize speed for the first time fast, and after certain data is changed in real time, can go to show change in real time in the figure that summarizes
It is influenced caused by entirety, clear with specific aim, clear logic handles efficient remarkable result.
Detailed description of the invention
Fig. 1 is the flow diagram of the data real-time statistical method of the invention based on financial data management platform.
Specific embodiment
Below with reference to the embodiment of the present invention, the invention will be further elaborated.
Embodiment:
Embodiment one:
As shown in Figure 1, a kind of data real-time statistical method based on financial data management platform, can effectively solve existing skill
The difficult point of financial data System in art, specifically includes following below scheme:
Firstly, it is necessary to initialize system, initialization one processing queue, the library Elasticsearch, one are specifically included
Table is checked in set of modules table, a set of summary sheet and each system corresponding material code information.
After initialization system, this processing queue is obtained, wherein the effect of the processing queue is for that will need to handle
It is ranked up and classifies into the data summarized.
Specifically, specific classification method is in the present embodiment: generating and in the change data of certain module to the module
Basic operation after get the module object of update, then obtaining its Update attribute from operating method link is " newly-increased "
Or " modification ", and this attribute is put into module object, it then is used as classification standard according to " module title ", is with module title
Key is packed into queue, Value module attribute object thus, meanwhile, increase the renewal time attribute of data object, by the module into
The time of enqueue is set as " renewal time ", and is successively sorted using this time as standard, and each module attribute pair is arranged
The return state of elephant be it is untreated, since this technology of queue itself has the attribute of first in first out, can join the team advanced
The data of column are first handled.
The data being each aggregated return to state in return parameters when being successfully, then by the attribute value " module of this data
Name ", " table name " and " basis judges attribute " are combined as " module name+table name+attribute ", and using this as key, object conduct
Value is put into the library Elasticsearch, and Ruo Kuli has the object key-value pair of same key, directly overrides.
Queue just deletes this data when reading the return state value of data and being successfully in queue, if the state of return is
" time-out does not receive feedback ", then it is data backup is primary, and untreated state is set by Backup Data, re-enter into queue
Rear end, reset " renewal time ", at the same by the original location data delete；If the state of return is " having repeated data "
Or " without this material ", then the data of original position are directly deleted.
After entering single line server from queue output, single line server has the processing upper limit, and long time treatment is more than upper
Limited capacity easily leads to the overstocked data processing of server and hysteretic operation occurs not in time, even loses data or delay machine, so this
Scheme needs that multithreading is combined to use.
Specific combination is: queue is to can control input and output rate, if than server one-line operation
Maximum value is 300/second, queue output speed be more than this value after, that is, be judged as more than threshold value, then calculate number per second
Divided by 300 aliquot (such as 550 divide exactly 300 results be 1), then at queue thresholds control setting docking service be multithreading
The result divided exactly is set as needing the Thread Counts opened by operation more.
In java code, the service of judging is connected to as multithreading, then the data to come can be put into simultaneously by total Thread Count
Thread pool is handled data by Thread Count using multithreading simultaneously, if that is, Thread Count is 3 at this time, then queue is every
Three groups of module datas of secondary releasing enter program, and program handles three groups of data simultaneously.Since data are that have module name and open most one
Beginning just classifies, so being the position that can be aggregated to mistake in processing to avoid data when processing multiple threads.Together
When settable reaction time such as 5 seconds, if rate is both less than present threshold value in 5 seconds, multithread programs are automatically to thread
Number subtracts one, then no longer judges until data return to single thread mode.
When summarizing data, due to needing data before multi-pass operation, to judging the repetition situation of data, judge currency
Unit completes coded format unification, judges that summarizing weight and this final data enters database and summarize, if gone with code always
It is to need repeatedly to call database if writing, efficiency is very low, live effect can not be reached, while if more people's operating databases,
Modified it is possible that will appear data, but obtain before or the case where old data, or as A goes modification data,
At this time this data by B modify in lead to Database lock table and the problem of the modification of A does not come into force.
In this programme to solve this problem, it is put into storing process and completes using by these operations, code only needs
A database is called, obtained return parameters this time, then are judged whether to summarize by the script for exactly calling storing process
Success, realization both reduce calling and improve processing capacity, prevent from occurring lagging or adjust library to lose when repeatedly calling database
The case where losing, and since storing process carries transaction functionality, it also can guarantee the consistency and isolation of data.
Data have been handled in multithread programs will just call storing process respectively, need in specific storing process
At data processing the step of it is as follows:
The data of module table are obtained according to the module name of data first and summary sheet summarizes field, according to this financial data
Company name, statistics month, section time etc. necessary sentence weight condition and go to assemble querying condition " module name+table name+attribute "
Whether the inquiry library Elasticsearch has the already existing identical data other than notebook data, does not carry out down to data then
The judgement of one step；Have, judge its Update attribute, wherein if the Update attribute of notebook data is " modification ", also directly to data into
Row judges in next step, if Update attribute is " newly-increased ", it can be assumed that this data is repeated data, then directly jumps out return
" having repeated data ".
Then it first obtains the monetary unit (such as, ten thousand, hundred million) of the confirmed data that can summarize and currency symbol is (such as
CNY, USD etc.), and compare with known unified monetary unit and symbol that (such as setting summarizes data unit and is unified for
The CNY currency of digit), the value of initial data is modified after comparison to the numerical value that can summarize, and enter in next step.
Due in each system statistics come data have the skimble-scamble problem of material code, needed in this step into
Row coded format is unified, and concrete methods of realizing is: whether having this field in inquiry summary sheet, has and then enter in next step, if looked into
Ask data material code it is all summarize can not be inquired in field, then obtain the System Number of data, and in material generation
Corresponding unified material code initialized in advance, this material code corresponding field in table are inquired in code information inspection table
Be only and need the field that summarizes, then enter in next step.If can not still be inquired in material code information inspection table, return
It knock-ons out " without this material ".
Then, after data find and summarize field, summary information table is gone to inquire the weight that this summarizes, by data multiplied by power
It recaptures to really need the new data being added in table, new data is added in former data, what is obtained is exactly after this time summarizing
Data,
In summary, for needing to solve efficiently System data and to realize zero defect, do not increase service again
The problem of device pressure, it is newly-increased to the full dose that server stress is big that the technical program does not consider that newly-increased timed task system does not use yet
Mode, but by using the combined use side of queue technology, the multithreading of code and database purchase process technology
Method realizes function treatment data, to avoid the occurrence of by surpassing repeatedly after request summarizes, timed task system repeatedly is called
The case where main system will lead to server delay machine and system caused to hang, while without going to develop a set of timed task system again
Main system is assisted, to save development cost.
It is understood that the principle that embodiment of above is intended to be merely illustrative of the present and the exemplary implementation that uses
Mode, however the present invention is not limited thereto.For those skilled in the art, essence of the invention is not being departed from
In the case where mind and essence, various changes and modifications can be made therein, these variations and modifications are also considered as protection scope of the present invention.
Claims (9)
1. a kind of data real-time statistical method based on financial data management platform, which comprises the following steps:
A. system is initialized, including one processing queue of initialization, a library Elasticsearch, a set of modules table, a set of
Table is checked in summary sheet and each system corresponding material code information；
B. user enters system, modifies newly-increased module data, and by the data assembling of modification in pairs as entering queue；
C. data setup module name increases renewal time attribute newly to data object and whether completes shape as classification foundation in queue
State attribute, data are obtained the more new state of data, will more new state be put into attribute format by renewal time sequence first in first out
Data object；
D. data summarization and enter server program, server obtain data return state；
E. when the rate that data enter server program is greater than threshold value, new thread is opened, then multithread programs are opened, queue
It will be transmitted to program with the consistent data of Thread Count by current thread number and batch and enter thread pool, while in thread pool
Data are handled；
F. it stores data into database and data is carried out to sentence weight；
G. by the monetary unit of the confirmed data that can summarize and currency symbol take out and known unified monetary unit and
Symbol compares, and modifies the value of initial data to the numerical value that can summarize；
H. whether the material code for obtaining data, inquiring in summary sheet has this field, has and then enters in next step；
I. it is found after unified material code summarizes field in data, inquires this weight for summarizing data in summary sheet, will summarize
Data obtain the new data needed to be added in table multiplied by weight, new data are added in former data, after this time being summarized
Data.
2. a kind of data real-time statistical method based on financial data management platform according to claim 1, feature exist
In the more new state of data includes newly-increased and modification in the step C.
3. a kind of data real-time statistical method based on financial data management platform according to claim 1, feature exist
In, in the step D, when queue read data return state value be " success " when, then to data carry out back up and in queue
In delete this data, it is if the return state value for reading data is " time-out do not feed back ", data backup is primary, and Backup Data
Setting state be it is untreated, Backup Data re-enter into queue rear end original data delete, return step C.
4. a kind of data real-time statistical method based on financial data management platform according to claim 3, feature exist
In, when being backed up to data be specifically data are backed up by the format of " module name+table name+attribute ".
5. a kind of data real-time statistical method based on financial data management platform according to claim 4, feature exist
In further including the key by " module name+table name+attribute " as data when being backed up to data, put object as value
Enter the library Elasticsearch, and Ruo Kuli has the object key-value pair of same key, then directly overrides.
6. a kind of data real-time statistical method based on financial data management platform according to claim 4, feature exist
In the step F is specifically included:
F1. according to financial data it is necessary sentence weight condition assemble querying condition " module name+table name+attribute " query service device
Whether identical data in addition to notebook data other than is had；
F2. G is entered step if not, otherwise, judges the Update attribute of the data；
F3. G is entered step if the Update attribute of the data is " modification "；If the Update attribute of the data is " newly-increased ", recognize
The fixed data are repeated data, are not involved in data summarization, then directly exit and return to " having repeated data ".
7. a kind of data real-time statistical method based on financial data management platform according to claim 6, feature exist
In, it is described it is necessary sentence weight condition include company name, statistics month, section time.
8. a kind of data real-time statistical method based on financial data management platform according to claim 6, feature exist
In in the step H further include: if the material code of data can not inquire in summary sheet, the system for obtaining data is compiled
Number, and corresponding unified material generation initialized in advance is inquired in the corresponding material code information inspection table of system
Code, and the corresponding field of the material code is the field for needing to summarize, and enters step I, if in material code information inspection
Table does not inquire yet, then directly exits and return " without this material ", and the data are not involved in and summarize.
9. according to claim 1 to a kind of data real-time statistical method based on financial data management platform any in 8,
It is characterized in that, the value of newly-increased Thread Count is that present rate divides exactly threshold value when multithread programs are opened in the step E
Value.
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