CN110692047A - Stationery information scheduling system based on big data - Google Patents
Stationery information scheduling system based on big data Download PDFInfo
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- CN110692047A CN110692047A CN201980000982.5A CN201980000982A CN110692047A CN 110692047 A CN110692047 A CN 110692047A CN 201980000982 A CN201980000982 A CN 201980000982A CN 110692047 A CN110692047 A CN 110692047A
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Abstract
The invention is suitable for the field of big data, and provides a stationery information scheduling system based on big data, which comprises: the system comprises a data integration module, a task planning module, a scheme pool evaluation module, an information data scheduling module and an information data display module. The data integration module comprises a big data information server, the big data information server is used for collecting stationery information data and is connected with commodity databases of all shopping malls and commodity databases of electronic commerce platforms through the Internet; the information data scheduling module comprises an information data searching unit for searching the stationery information data meeting the stationery information scheduling request; the scheme pool evaluation module comprises a scheme pool evaluation unit and a scheme pool evaluation optimization unit; the information real-time acquisition and scheduling function of the stationery scheduling system is realized; the stationery information data is processed by using the storage and calculation resources of the cloud in the most profitable way, so that the processing cost is reduced, and the efficiency of searching and scheduling the stationery information data is improved.
Description
Technical Field
The invention belongs to the technical field of big data, and particularly relates to a stationery information scheduling system based on big data.
Background
With the development of big data technology, the stationery data informatization construction in stationery production enterprises has gradually entered into the big data era, and the application data of the stationery dispatching system is rapidly increased, but the stationery data in the current stationery production enterprises are dispersed in each business system, so that the stationery data cannot be comprehensively dispatched and utilized, and the timely processing of data dispatching cannot be guaranteed.
Disclosure of Invention
In order to overcome the technical problems in the prior art, the embodiment of the invention provides a stationery information scheduling system based on big data, which realizes the information real-time obtaining and scheduling function of the stationery scheduling system; the stationery information data is processed by using the storage and calculation resources of the cloud in the most profitable way, so that the processing cost is reduced, and the efficiency of searching and scheduling the stationery information data is improved.
The embodiment of the invention is realized in such a way that a big data-based stationery information scheduling system comprises:
the data integration module is used for collecting, classifying and storing various types of stationery information data through the cloud server;
the task planning module is used for dividing the integration process of the stationery information data into a data storage task, a data classification task, an index calculation task and a data processing analysis calculation task, matching a cloud service resource pool meeting the requirement of each task for each task, and forming a cloud service resource scheme pool so as to obtain storage resources or calculation resources required in the big data processing process;
the system comprises a task planning module, a scheme pool evaluation module, a cloud service resource scheme pool evaluation module and a data storage and calculation module, wherein the task planning module is used for executing evaluation of the cloud service resource scheme pool, selecting an optimal cloud service resource scheme pool and providing storage and calculation resources for processing stationery information data;
the information data scheduling module is used for scheduling the required stationery information data at the corresponding position of the cloud service resource pool according to the stationery information scheduling request input by the user; and
and the information data display module displays the scheduled stationery information data to a user in real time through a display screen.
Preferably, the data integration module comprises a big data information server, wherein the big data information server is used for collecting stationery information data and is connected with commodity databases of all shopping malls and commodity databases of electronic commerce platforms through the internet.
Preferably, the information data scheduling module comprises an information data searching unit for searching the stationery information data meeting the stationery information scheduling request.
Preferably, the solution pool evaluation module includes a solution pool evaluation unit and a solution pool evaluation optimization unit.
Preferably, the cloud service resource pool further comprises a redundancy judgment module for performing redundancy judgment on the stationery information data stored in the cloud service resource pool and deleting the same stationery information data.
Preferably, the system further comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for dividing the stationery information data stored in the cloud service resource pool to obtain a divided stationery information data set; calculating the hash value of the current stationery information data set by a check value hash algorithm, and searching whether a target stationery information data set with the same hash value exists in the backed-up stationery information data set; if a target stationery information data set with the same hash value is found in the backed-up stationery information data set, performing byte-by-byte comparison on the target stationery information data set and the current stationery information data set; and the disaster recovery backup module is used for backing up the current stationery information data set according to the comparison result.
The stationery information scheduling system based on big data provided by the embodiment of the invention realizes the information real-time obtaining and scheduling function of the stationery scheduling system; the stationery information data is processed by using the storage and calculation resources of the cloud in the most profitable way, so that the processing cost is reduced, and the efficiency of searching and scheduling the stationery information data is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
The drawings are only for purposes of illustrating and explaining the present invention and are not to be construed as limiting the scope of the present invention.
Fig. 1 is a schematic structural diagram of a big data-based stationery information scheduling system according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of another big-data-based stationery information scheduling system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another big-data-based stationery information scheduling system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The big data-based stationery information scheduling system provided by the embodiment of the invention comprises a data integration module, a task planning module, a scheme pool evaluation module, an information data scheduling module and an information data display module. The data integration module comprises a big data information server, the big data information server is used for collecting stationery information data and is connected with commodity databases of all shopping malls and commodity databases of electronic commerce platforms through the Internet; the information data scheduling module comprises an information data searching unit for searching the stationery information data meeting the stationery information scheduling request; the scheme pool evaluation module comprises a scheme pool evaluation unit and a scheme pool evaluation optimization unit; the information real-time acquisition and scheduling function of the stationery scheduling system is realized; the stationery information data is processed by using the storage and calculation resources of the cloud in the most profitable way, so that the processing cost is reduced, and the efficiency of searching and scheduling the stationery information data is improved.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
As shown in fig. 1, in an embodiment of the present invention, a big data-based stationery information scheduling system 10 includes: a data integration module 11 for collecting, classifying and storing various types of stationery information data through a cloud server; the task planning module 12 is used for dividing the integration process of the stationery information data into a data storage task, a data classification task, an index calculation task and a data processing analysis calculation task, matching a cloud service resource pool meeting the requirement of each task to form a cloud service resource scheme pool, and obtaining storage resources or calculation resources required in the big data processing process; a plan pool evaluation module 13 for executing evaluation of the cloud service resource plan pool according to the task plan of the big data service generated by the task plan module, selecting the optimal cloud service resource plan pool, and providing storage and calculation resources for processing the stationery information data; an information data scheduling module 14 for scheduling the required stationery information data at the corresponding position of the cloud service resource pool according to the stationery information scheduling request input by the user; the information data display module 15 displays the scheduled stationery information data to the user in real time through a display screen, so that the information real-time obtaining and scheduling function of the stationery scheduling system is realized; the stationery information data is processed by using the storage and calculation resources of the cloud in the most profitable way, so that the processing cost is reduced, and the efficiency of searching and scheduling the stationery information data is improved.
In this embodiment, the data integration module 11 includes a big data information server 111, and the big data information server 111 is used for collecting stationery information data, and is connected to the commodity database of each store and the commodity database of the e-commerce platform through the internet.
In this embodiment, the information data scheduling module 14 includes an information data searching unit 141 for searching for stationery information data satisfying the stationery information scheduling request.
In this embodiment, the solution pool evaluation module 13 includes a solution pool evaluation unit 131 and a solution pool evaluation optimization unit 132.
As a preferred embodiment of the present invention, as shown in fig. 2, the system further includes a redundancy determining module 16, configured to perform redundancy determination on stationery information data stored in the cloud service resource pool, and delete the same stationery information data, so as to reduce data storage burden.
As a preferred embodiment of the present invention, as shown in fig. 3, the system further includes a disaster recovery backup module 17, configured to segment the stationery information data stored in the cloud service resource pool to obtain a segmented stationery information data set; calculating the hash value of the current stationery information data set by a check value hash algorithm, and searching whether a target stationery information data set with the same hash value exists in the backed-up stationery information data set; if a target stationery information data set with the same hash value is found in the backed-up stationery information data set, performing byte-by-byte comparison on the target stationery information data set and the current stationery information data set; the backup of the current stationery information data set is carried out according to the comparison result, and the user can be helped to cope with soft disasters such as manual misoperation, software error and virus invasion and hard disasters such as hardware faults and natural disasters.
The big data-based stationery information scheduling system provided by the embodiment of the invention comprises a data integration module, a task planning module, a scheme pool evaluation module, an information data scheduling module and an information data display module. The data integration module comprises a big data information server, the big data information server is used for collecting stationery information data and is connected with commodity databases of all shopping malls and commodity databases of electronic commerce platforms through the Internet; the information data scheduling module comprises an information data searching unit for searching the stationery information data meeting the stationery information scheduling request; the scheme pool evaluation module comprises a scheme pool evaluation unit and a scheme pool evaluation optimization unit; the information real-time acquisition and scheduling function of the stationery scheduling system is realized; the stationery information data is processed by using the storage and calculation resources of the cloud in the most profitable way, so that the processing cost is reduced, and the efficiency of searching and scheduling the stationery information data is improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. A big data-based stationery information scheduling system, comprising:
the data integration module is used for collecting, classifying and storing various types of stationery information data through the cloud server;
the task planning module is used for dividing the integration process of the stationery information data into a data storage task, a data classification task, an index calculation task and a data processing analysis calculation task, matching a cloud service resource pool meeting the requirement of each task for each task, and forming a cloud service resource scheme pool so as to obtain storage resources or calculation resources required in the big data processing process;
the system comprises a task planning module, a scheme pool evaluation module, a cloud service resource scheme pool evaluation module and a data storage and calculation module, wherein the task planning module is used for executing evaluation of the cloud service resource scheme pool, selecting an optimal cloud service resource scheme pool and providing storage and calculation resources for processing stationery information data;
the information data scheduling module is used for scheduling the required stationery information data at the corresponding position of the cloud service resource pool according to the stationery information scheduling request input by the user; and
and the information data display module displays the scheduled stationery information data to a user in real time through a display screen.
2. The big-data-based stationery information scheduling system of claim 1 wherein said data integration module comprises a big-data information server for collecting stationery information data, which is connected to commodity databases of all shopping malls and commodity databases of e-commerce platforms through the internet.
3. The big-data-based stationery information dispatching system of claim 1 wherein said information data dispatching module includes an information data lookup unit for looking up stationery information data that satisfies the stationery information dispatching request.
4. The big-data based stationery information dispatching system of claim 1 wherein said solution pool assessment module comprises a solution pool assessment unit and a solution pool assessment optimization unit.
5. The big-data-based stationery information scheduling system according to claim 1, further comprising a redundancy judgment module for performing redundancy judgment on stationery information data stored in the cloud service resource pool and deleting the same stationery information data.
6. The big-data-based stationery information scheduling system according to claim 1, further comprising a data processing module for dividing stationery information data stored in the cloud service resource pool to obtain a divided stationery information data set; calculating the hash value of the current stationery information data set by a check value hash algorithm, and searching whether a target stationery information data set with the same hash value exists in the backed-up stationery information data set; if a target stationery information data set with the same hash value is found in the backed-up stationery information data set, performing byte-by-byte comparison on the target stationery information data set and the current stationery information data set; and the disaster recovery backup module is used for backing up the current stationery information data set according to the comparison result.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2019/087513 WO2020232592A1 (en) | 2019-05-19 | 2019-05-19 | Stationery information scheduling system based on big data |
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| CN110692047A true CN110692047A (en) | 2020-01-14 |
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| CN201980000982.5A Withdrawn CN110692047A (en) | 2019-05-19 | 2019-05-19 | Stationery information scheduling system based on big data |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW317634B (en) * | 1995-10-18 | 1997-10-11 | Nippon Electric Co | |
| CN101989929A (en) * | 2010-11-17 | 2011-03-23 | 中兴通讯股份有限公司 | Disaster recovery data backup method and system |
| US20140172809A1 (en) * | 2012-12-13 | 2014-06-19 | William Gardella | Hadoop access via hadoop interface services based on function conversion |
| CN106027344A (en) * | 2016-07-05 | 2016-10-12 | 吴本刚 | Home service system based on big data |
| CN107273463A (en) * | 2017-06-02 | 2017-10-20 | 深圳齐心集团股份有限公司 | A kind of big data stationery searching system |
| CN107395694A (en) * | 2017-07-04 | 2017-11-24 | 深圳齐心集团股份有限公司 | A kind of big data management system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8626703B2 (en) * | 2010-12-17 | 2014-01-07 | Verizon Patent And Licensing Inc. | Enterprise resource planning (ERP) system change data capture |
| CN105893375A (en) * | 2014-12-04 | 2016-08-24 | 北京航天长峰科技工业集团有限公司 | Safety production data following management based on big data |
| CN105915659A (en) * | 2016-07-05 | 2016-08-31 | 吴本刚 | Physical examination system based on cloud calculation |
-
2019
- 2019-05-19 CN CN201980000982.5A patent/CN110692047A/en not_active Withdrawn
- 2019-05-19 WO PCT/CN2019/087513 patent/WO2020232592A1/en active Application Filing
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TW317634B (en) * | 1995-10-18 | 1997-10-11 | Nippon Electric Co | |
| CN101989929A (en) * | 2010-11-17 | 2011-03-23 | 中兴通讯股份有限公司 | Disaster recovery data backup method and system |
| US20140172809A1 (en) * | 2012-12-13 | 2014-06-19 | William Gardella | Hadoop access via hadoop interface services based on function conversion |
| CN106027344A (en) * | 2016-07-05 | 2016-10-12 | 吴本刚 | Home service system based on big data |
| CN107273463A (en) * | 2017-06-02 | 2017-10-20 | 深圳齐心集团股份有限公司 | A kind of big data stationery searching system |
| CN107395694A (en) * | 2017-07-04 | 2017-11-24 | 深圳齐心集团股份有限公司 | A kind of big data management system |
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| WO2020232592A1 (en) | 2020-11-26 |
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