CN110287195A - Distributed data analyzing system and method - Google Patents
Distributed data analyzing system and method Download PDFInfo
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- CN110287195A CN110287195A CN201910577757.XA CN201910577757A CN110287195A CN 110287195 A CN110287195 A CN 110287195A CN 201910577757 A CN201910577757 A CN 201910577757A CN 110287195 A CN110287195 A CN 110287195A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
- G06F16/2393—Updating materialised views
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
Abstract
The present invention relates to the data processing method technical fields for being suitable for specific function, specially a kind of distributed data analyzing system and method, including acquisition subsystem, for obtaining the acquisition data of different data format respectively, and the acquisition data of different data format are converted to the normal data of standard data format；Analyzing subsystem, for analyzing result according to normal data generation or real-time update；Subsystem is shown, for showing analysis result to manager.The data of different-format can be acquired in time using this programme, and the result that real-time update is shown according to the collected data.
Description
Technical field
The present invention relates to the data processing method technical field for being suitable for specific function, specially a kind of distributed datas point
Analysis system and method.
Background technique
For business administration, wherein important is how to acquire data, how to analyze acquisition data and generate and divide
How analysis is as a result, to show analysis result.The data producing method of existing industrial management process usually has following several:
1. staff fills in live paper list；
2. industrial robot, equipment computer generate；
3. the various software systems used of enterprise generate；
4. other hardware devices of enterprise's setting, such as sensor.
Existing data analysing method usually has following several:
1. manually being statisticallyd analyze by Excel table；
2. the program by enterprise's customized development statisticallys analyze.
But due to the diversity of data producing method, data format is also different, exists when for statistical analysis
Difficulty.It is manually statisticallyd analyze by Excel table and has the disadvantage in that the generation of Excel table, statistics and analysis are required to greatly
The time of amount, statistical analysis efficiency are too low；And have new data in the process and generate, it is not that the timely data that carry out are divided
Analysis；Excel table needs staff to assist to fill in, and increases human cost, and field data passes through secondary operation or modification, so that
Data inaccuracy, influences the result of subsequent statistical analysis.
Have the disadvantage in that data source is more by the program statistical analysis of enterprise's customized development, development difficulty is big, leads
It causes the development cycle long, and there is the case where increase and decrease data source, safeguard, scaling difficulty, cost input is big.
Summary of the invention
The invention is intended to provide a kind of distributed data analyzing system, the data of different-format, and root can be acquired in time
The result shown according to the data real-time update of acquisition.
The present invention provides base case: distributed data analyzing system, including acquisition subsystem, analyzing subsystem and displaying
Subsystem, the acquisition subsystem include:
Data reception module, for obtaining the acquisition data of different data format respectively；
Data conversion module is converted to the criterion numeral of standard data format for the acquisition data by different data format
According to, and it is sent to analyzing subsystem in real time；
The analyzing subsystem, for analyzing result according to normal data generation or real-time update；
The displaying subsystem, for showing analysis result to manager.
Noun illustrates: standard data format is the Uniform data format that calculating is able to carry out in this system.
The working principle and beneficial effect of base case: manager needs very multidata support in the management process, this
A little data are indexs, and generate these indexs and just need corresponding data, and each not phase of the mode of different data its acquisitions
Together, some need hand filling, some needs are obtained from existing equipment, such as electricity consumption is obtained in intelligent electric meter, some are needed
Corresponding equipment acquisition related data is set, so that the data of acquisition are different.It is received by data reception module
The acquisition data of different data format are converted to normal data by data conversion module by the acquisition data of different data format
The normal data of format, by Uniform data format, convenient for being handled data and being analyzed in systems.
By analyzing subsystem according to normal data generate analysis as a result, and when receiving normal data again, according to
Normal data real-time update analysis as a result, in order to manager grasp data variation dynamic and its corresponding mutation analysis
As a result.Analysis is shown as a result, enabling manager that analysis is understood more intuitively as a result, just to manager by showing subsystem
In subsequent carry out correlation analysis.
Further, the analyzing subsystem includes:
Index generation module when for receiving normal data for the first time, generates practical index according to several normal datas；It is used in combination
When receiving normal data again, practical index is updated according to several normal datas.
The utility model has the advantages that at this time and practical index is not present, it is necessary to generate by normal data when receiving normal data for the first time
Practical index has existed practical index when receiving normal data again at this time, updates practical index according to normal data and is
It can.The variation of each normal data, can all be updated practical index.
Further, the analyzing subsystem includes:
Indicator analysis module, after generating practical index or updating practical index, according to standard index and practical index
Generate analysis result.
Noun explanation: standard index is the preset target value of enterprise, is preset with multiple standard indexs, such as single-piece in system
Product cost needs to control at 100 yuan hereinafter, it is 98% or more that then 100 yuan, which are standard index, such as same day product qualification rate, then
98% is standard index.
The utility model has the advantages that either generating practical index still updates practical index, require to regenerate analysis as a result, just
Variation dynamic is grasped in real time in manager, to find the problem in time, and is managed in time for problem.
Further, the analyzing subsystem includes:
Statistical module is analyzed, if for obtaining dry analysis according to time range as a result, and carrying out statistics life to analysis result
At statistical result；
Analyze sorting module, for according to standard index obtain sort criteria, and according to sort criteria to statistical result into
Row sequence generates analysis chart and checks for manager.
Noun explanation: analysis result can be preset problematic item, i.e., exceeded reason.
The utility model has the advantages that then analyzing for example, to find the problem be that A link is unqualified according to practical index and standard index comparison
It as a result include that A link is unqualified, and statistical management person wants the analysis in the time range checked as a result, i.e. A link is unqualified more
Few time, the unqualified how many times of B link, the unqualified how many times of C link.Since analysis result is related to standard index, according to standard
Index selection sort criteria, such as A link unqualified 10 times, B link unqualified 6 times, C link unqualified 14 times, then press number
It sorts from high to low, statistical result are as follows: C link unqualified 14 times, A link unqualified 10 times, B link unqualified 6 times.According to row
Statistical result after sequence generates analysis chart and checks for manager, and manager can be made to see the ring of problem most serious at a glance
Section, promotes manager to handle in time, increases the dynamics of management.
Further, the sort criteria is number, time and difference.
The utility model has the advantages that the corresponding sort criteria of different standard indexs is different, for example, analysis the result is that some part not
Qualified number, side are arranged successively from more to less according to number, such as analysis is the result is that the time that some part is spent, then sort item
Part is successively to sort from long to short according to the time, such as analysis is the result is that the distance between some position difference, then sort item
Part is arranged successively according to difference is descending.
Further, the displaying subsystem includes:
As a result display module, for showing analysis result to manager；
Diagrammatic representation module, for showing analysis chart to manager.
The utility model has the advantages that can be shown to manager when each generation analysis result by result display module, lead to
Cross the problem of diagrammatic representation module shows analysis chart to manager when manager needs, is convenient for analysis management.
The invention is intended to also provide a kind of distributed data analyzing method, comprising the following steps:
Data acquisition step obtains the acquisition data of different data format according to different acquisition modes, and by different data
The acquisition data of format are converted to the normal data of standard data format；
Data analysis step generates analysis result according to normal data；
Data show step, show analysis result to manager.
The utility model has the advantages that obtaining the acquisition data of different data specification by data acquisition step, and to the number of acquisition data
It is converted according to format, for being calculated and being analyzed in follow-up system.Analysis is generated as a result, passing through analysis by normal data
Where results management person can get information about problem, data are analyzed without devoting a tremendous amount of time.
Further, the acquisition modes in the data acquisition step include: to fill in manually, smart machine acquisition, biography be arranged
Sensor acquisition.
The utility model has the advantages that different acquisition data natural data obtaining steps is different, such as the final product quality of artificial detection is asked
Topic needs staff to fill in corresponding sampling observation quantity, unqualified quantity and qualified quantity.Since the processing industry of modernization uses
The equipment such as industrial robot work, and industrial robot just can acquire relevant data and be uploaded in system.Enterprise can also be with
By the way that sensor is arranged, the acquisition of related data is carried out, such as the usage amount of raw material can pass through gravity sensor.
Further, the data analysis step specifically includes the following steps:
Index generation step generates practical index according to the normal data obtained for the first time, and according to the standard obtained again
Data update practical index；
Indicator-specific statistics step, it is raw according to practical index and standard index after generating practical index or updating practical index
If at analysis as a result, and carrying out statistics generation statistical result according to time range pair dry analysis result；
Index sequence step obtains sort criteria according to standard index, and is arranged according to sort criteria statistical result
Sequence generates analysis chart.
The utility model has the advantages that generating practical index, as index needed for manager by index generation step, united by index
Step counting generates analysis result and statistical result suddenly, analyzes without manager data, is directly viewable as a result, when saving a large amount of
Between, the problem of being ranked up by index sequence step to statistical result, manager is enabled to see most serious at a glance, promote
Solve the problems, such as manager.
Further, the data show step, further include that analysis chart is shown to manager.
The utility model has the advantages that showing that step shows analysis chart by data, adopts and carry out display graphically convenient for management
Person checks.
Detailed description of the invention
Fig. 1 is the logic diagram of distributed data analyzing system embodiment one of the present invention；
Fig. 2 is the logic diagram of distributed data analyzing embodiment of the method two of the present invention.
Specific embodiment
It is further described below by specific embodiment:
Embodiment one
Distributed data analyzing system, as shown in Fig. 1, including acquisition subsystem, analyzing subsystem, show subsystem,
Management end, collection terminal and database, acquisition subsystem include data reception module and data conversion module, and analyzing subsystem includes
Index generation module and indicator analysis module show that subsystem includes result display module, database be preset with parameter acquisition table,
Standard index, parameter acquisition table are the preset table for inserting all data, and standard index is the preset target value of enterprise, are
Be preset with multiple standard indexs in system, for example, single products cost need to control at 100 yuan hereinafter, then 100 yuan be standard index,
Such as same day product qualification rate is 98% or more, then 98% is standard index.
Collection terminal is sent to acquisition subsystem for filling in acquisition data manually for staff.Data reception module
Acquire data for receiving, and the acquisition tables that get parms from database, and according to parameter acquisition table from other equipment or other
Terminal acquisition acquisition data (such as acquisition data are obtained from the sensor of setting in the production line, such as obtain from intelligent electric meter
Electricity is taken, equipment can be set as needed in manager, and the data that equipment acquires are uploaded to data reception module), and will
The acquisition data of all acquisitions are sent to data conversion module (the acquisition data obtained at this time are different data format).
Data conversion module is for after receiving several acquisition data, to get parms acquisition tables from database, and by parameter
The data format of acquisition tables is converted into standard data format as standard data format, by the data format of several acquisition data
It as normal data, and inserts in parameter acquisition table, and the parameter acquisition table after will fill in is sent to analyzing subsystem.
It is raw according to several normal datas in parameter acquisition table when index generation module for receiving parameter acquisition table for the first time
At practical index；And when for receiving parameter acquisition table again, updated according to several normal datas in parameter acquisition table practical
Index (when receiving parameter acquisition table, it whether there is practical index in garbled data library, if it does not exist, then for for the first time, and if it exists,
Then for again), and practical index is sent to indicator analysis module.
Indicator analysis module is for obtaining standard corresponding with practical index from database and referring to after receiving practical index
Mark, and according to standard index and practical quota student at analysis as a result, and being sent to displaying subsystem for result is analyzed.
As a result display module is for receiving analysis as a result, and analysis result is sent to management end.Management end is for showing
Analysis result is checked for manager.
Distributed data analyzing method based on above system, comprising the following steps:
Data acquisition step obtains the acquisition data of different data format according to different acquisition modes, and by different data
The acquisition data of format are converted to the normal data of standard data format, acquisition modes including filling in manually, smart machine acquires,
Sensor is arranged to acquire.
Data analysis step generates practical index according to normal data, standard index is obtained, according to standard index and reality
Quota student is at analysis result.
Data show step, show analysis result to manager.
Specifically, data analysis step the following steps are included:
Index generation step generates practical index according to the normal data obtained for the first time, and according to the standard obtained again
The practical index of data update (normal data is obtained, and practical index is screened from database according to normal data, if it does not exist,
Then generate practical index, and if it exists, then update practical index).
Indicator-specific statistics step, it is raw according to practical index and standard index after generating practical index or updating practical index
At analysis result (analysis result can be generated by generating or being updated every time).
Embodiment two
The present embodiment and embodiment one the difference is that: as shown in Fig. 2, analyzing subsystem further includes analysis statistics mould
Block and analysis sorting module, show that subsystem further includes diagrammatic representation module, sort criteria are preset in database (in this implementation
In example, sort criteria is that number, time and difference sort from long to short according to the time, press that is, according to number by up to sorting less
Sort from large to small according to difference), sort criteria is the ordering rule of statistical result.
Management end is sent to analyzing subsystem for obtaining analysis signal and time range.Analysis statistical module is used for
Analysis signal and time range are received, and according to analysis signal from the analysis in database within the scope of acquisition time as a result, and right
Analysis result carries out statistics and generates statistical result, and statistical result is sent to analysis sorting module.
Analysis sorting module is obtained from database for obtaining standard index based on the analysis results according to standard index
Corresponding sort criteria, and generation analysis chart is ranked up to statistical result according to sort criteria, and analysis chart is sent
Give displaying subsystem.In the present embodiment, analysis chart is the table being arranged successively, and in other embodiments, analysis chart can
For line chart, cake chart, bar chart etc..
Diagrammatic representation module is shown for reception analysis chart and is checked for manager.
Distributed data analyzing method based on above system, comprising the following steps:
Indicator-specific statistics step further includes when manager needs the analysis result within the scope of statistical time, according to time range
The corresponding analysis within the scope of this is obtained as a result, statistics generates statistical result.
Specifically, data analysis step the following steps are included:
Index sequence step obtains sort criteria (including number, time and difference) according to standard index, and according to sequence
Condition is ranked up generation analysis chart to statistical result.
Data show step, further include that analysis chart is shown to manager.
What has been described above is only an embodiment of the present invention, and the common sense such as well known specific structure and characteristic are not made herein in scheme
Excessive description, technical field that the present invention belongs to is all before one skilled in the art know the applying date or priority date
Ordinary technical knowledge can know the prior art all in the field, and have using routine experiment hand before the date
The ability of section, one skilled in the art can improve and be implemented in conjunction with self-ability under the enlightenment that the application provides
This programme, some typical known features or known method should not become one skilled in the art and implement the application
Obstacle.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, can also make
Several modifications and improvements out, these also should be considered as protection scope of the present invention, these all will not influence the effect that the present invention is implemented
Fruit and patent practicability.The scope of protection required by this application should be based on the content of the claims, the tool in specification
The records such as body embodiment can be used for explaining the content of claim.
Claims (10)
1. distributed data analyzing system, which is characterized in that including acquisition subsystem, analyzing subsystem and show subsystem, institute
Stating acquisition subsystem includes:
Data reception module, for obtaining the acquisition data of different data format respectively；
Data conversion module is converted to the normal data of standard data format for the acquisition data by different data format, and
It is sent to analyzing subsystem in real time；
The analyzing subsystem, for analyzing result according to normal data generation or real-time update；
The displaying subsystem, for showing analysis result to manager.
2. distributed data analyzing system according to claim 1, which is characterized in that the analyzing subsystem includes:
Index generation module when for receiving normal data for the first time, generates practical index according to several normal datas；And for again
When secondary reception normal data, practical index is updated according to several normal datas.
3. distributed data analyzing system according to claim 2, which is characterized in that the analyzing subsystem includes:
Indicator analysis module generates after generating practical index or updating practical index according to standard index and practical index
Analyze result.
4. distributed data analyzing system according to claim 3, which is characterized in that the analyzing subsystem includes:
Statistical module is analyzed, if for obtaining dry analysis according to time range as a result, and carrying out statistics generation system to analysis result
Count result；
Sorting module is analyzed, for obtaining sort criteria according to standard index, and statistical result is arranged according to sort criteria
Sequence generates analysis chart and checks for manager.
5. distributed data analyzing system according to claim 4, it is characterised in that: the sort criteria be number, when
Between and difference.
6. distributed data analyzing system according to claim 5, which is characterized in that the displaying subsystem includes:
As a result display module, for showing analysis result to manager；
Diagrammatic representation module, for showing analysis chart to manager.
7. distributed data analyzing method, which comprises the following steps:
Data acquisition step obtains the acquisition data of different data format according to different acquisition modes, and by different data format
Acquisition data be converted to the normal data of standard data format；
Data analysis step generates analysis result according to normal data；
Data show step, show analysis result to manager.
8. distributed data analyzing method according to claim 7, which is characterized in that obtaining in the data acquisition step
Taking mode includes: to fill in manually, smart machine acquisition, sensor acquisition be arranged.
9. distributed data analyzing method according to claim 7, which is characterized in that the data analysis step is specifically wrapped
Include following steps:
Index generation step generates practical index according to the normal data obtained for the first time, and according to the normal data obtained again
Update practical index；
Indicator-specific statistics step generates according to practical index and standard index and divides after generating practical index or updating practical index
If analysis is as a result, and carry out statistics generation statistical result according to time range pair dry analysis result；
Index sequence step obtains sort criteria according to standard index, and is ranked up life to statistical result according to sort criteria
At analysis chart.
10. distributed data analyzing method according to claim 9, it is characterised in that: the data show step, also wrap
It includes to manager and shows analysis chart.
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