CN110692045A - Big data-based stationery information distributed planning system - Google Patents
Big data-based stationery information distributed planning system Download PDFInfo
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- G06F11/14—Error detection or correction of the data by redundancy in operation
- G06F11/1402—Saving, restoring, recovering or retrying
- G06F11/1446—Point-in-time backing up or restoration of persistent data
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Abstract
The invention is suitable for the technical field of big data, and provides a stationery information distributed planning system based on big data, which comprises: the system comprises a data acquisition module, a data integration module, a data redundancy judgment module, a data modeling module, a data classification module and a data search evaluation module, wherein the data acquisition module, the data integration module, the data modeling module, the data classification module and the data search evaluation module are sequentially connected through conducting wires; the data redundancy judging module is connected with the data integration module through a wire; the stationery data in the stationery production enterprises can be comprehensively utilized, a user can conveniently search data sources and data owners of the stationery data, repeated stationery data can be deleted, and data storage burden is reduced.
Description
Technical Field
The invention belongs to the technical field of big data, and particularly relates to a stationery information distributed planning system based on big data.
Background
With the continuous price reduction of computer equipment, personal computers are increasingly applied to various departments of management, and in order to exert the functions of the equipment, the functions of the equipment must be organically connected, so that the information requirement of each manager can be met, and timely information can be provided for a decision-making layer leader. The dispersed development needs to modify the original software, reorganize the data and connect into a unified large system, and the consumed manpower and the fund are more than those for newly establishing; even the maintenance and modification is not feasible at all. The system maintenance problem is just like a evil and entangles the development of data processing, which is called a 'data processing crisis'. The birth of data distribution planning, like the appearance of other theories, has own special reasons and power, which are necessary results of data processing crisis.
With the development of industrial application systems, application data of various information systems rapidly increases, for example, the stationery data informatization construction in stationery production enterprises has gradually entered the big data era. The stationery data in the current stationery production enterprises are dispersed in each business system and cannot be comprehensively utilized, the data source and the data owner of the stationery data are not clear and cannot correspond to the business system, so that the data source is disordered, the versions are numerous, the structure, the format and the relationship are complex and various, scientific guidance and support cannot be provided for data acquisition, the data carding is not clear, the management is disordered, the data redundant storage is caused, and the unnecessary data storage burden is increased.
Disclosure of Invention
In order to solve the technical problems in the prior art, embodiments of the present invention provide a distributed planning system for stationery information based on big data, which can comprehensively utilize stationery data in a stationery manufacturing enterprise, facilitate users to search data sources and data owners of the stationery data, delete duplicate stationery data, and reduce data storage burden.
The embodiment of the invention is realized in such a way that a big data-based stationery information distributed planning system comprises: the system comprises a data acquisition module, a data integration module, a data redundancy judgment module, a data modeling module, a data classification module and a data search evaluation module, wherein the data acquisition module, the data integration module, the data modeling module, the data classification module and the data search evaluation module are sequentially connected through conducting wires; the data redundancy judging module is connected with the data integration module through a wire; the data acquisition module is used for planning and acquiring stationery data and sending the acquired stationery data to the data integration module; the data integration module is used for integrating and screening the acquired stationery data, eliminating useless stationery data from the screened stationery data, reserving the stationery data with the purposes, and taking the reserved stationery data as original data of data planning; the data redundancy judgment module is used for performing redundancy judgment on the original data and deleting repeated stationery data; the data modeling module is used for establishing a data model suitable for original data aiming at the original data; the data classification module is used for planning and classifying the modeled stationery data according to the data source, the data owner and the data search frequency; and the data searching and evaluating module is used for evaluating the classified stationery data and searching the data source, the data owner and the data searching frequency of the data.
Preferably, the method further comprises the following steps: and the data disaster recovery backup module is connected with the data integration module through a wire and used for receiving the stationery data to be backed up sent by the data integration module and backing up the received stationery data.
Preferably, the data disaster recovery backup module includes:
the data receiving unit is used for receiving the stationery data to be backed up sent by the data integration module;
the data dividing unit is used for dividing the stationery data to be backed up to obtain divided stationery data blocks;
the calculation searching unit is used for calculating the data fingerprint value of the current stationery data block by using a weak check value hash algorithm and a strong check value hash algorithm, and searching whether a target stationery data block with the same data fingerprint value exists in a backed-up data file;
the comparison unit is used for comparing the target stationery data block with the current stationery data block byte by byte when the target stationery data block with the same data fingerprint value is found in the backed-up data file; and
and the data backup unit is used for backing up the current stationery data block according to the comparison result of the comparison unit.
Preferably, the method further comprises the following steps: and the data storage encryption module is connected with the data integration module through a wire and is used for encrypting and storing the original data in the data integration module.
Preferably, the data storage encryption module comprises a secure encryption chip and a secure decryption chip.
Preferably, the secure encryption chip and the secure decryption chip use a secure socket layer SSL and/or a secure transport layer TLS.
Preferably, the secure encryption chip and the secure decryption chip comprise one or more secure processing units of AES, RSA, SHA, OTP, RNG, GUID.
Preferably, a data acquisition port is arranged on the data acquisition module.
Preferably, the data search evaluation module comprises a data search engine.
The distributed planning system for the stationery information based on the big data, provided by the embodiment of the invention, can comprehensively utilize the stationery data in the stationery production enterprises, is convenient for a user to search the data source and the data owner of the stationery data, can delete the repeated stationery data, and can reduce the data storage burden.
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 distributed stationery information planning system according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of another big-data-based distributed planning system for stationery information according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a data disaster recovery backup module according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of another big-data-based stationery information distributed planning 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 distributed stationery information planning system comprises a data acquisition module, a data integration module, a data redundancy judgment module, a data modeling module, a data classification module and a data search evaluation module, wherein the data acquisition module, the data integration module, the data modeling module, the data classification module and the data search evaluation module are sequentially connected through a wire; the data redundancy judging module is connected with the data integration module through a wire; the stationery data in the stationery production enterprises can be comprehensively utilized, a user can conveniently search data sources and data owners of the stationery data, repeated stationery data can be deleted, and data storage burden is reduced.
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 distributed planning system 100 includes: the system comprises a data acquisition module 110, a data integration module 120, a data redundancy judgment module 130, a data modeling module 140, a data classification module 150 and a data search evaluation module 160, wherein the data acquisition module 110, the data integration module 120, the data modeling module 140, the data classification module 150 and the data search evaluation module 160 are sequentially connected through a lead; the data redundancy judging module 130 is connected with the data integrating module 120 through a wire; the data acquisition module 110 is configured to plan and acquire stationery data, and send the acquired stationery data to the data integration module; the data integration module 120 is configured to integrate and screen the acquired stationery data, remove useless stationery data from the screened stationery data, reserve the useful stationery data, and use the reserved stationery data as an original data of the data plan; the data redundancy judgment module 130 is configured to perform redundancy judgment on the original data and delete repeated stationery data; the data modeling module 140 is configured to establish a data model suitable for original data; the data classification module 150 is configured to perform planning classification on the modeled stationery data according to a data source, a data owner, and a data search frequency; the data search evaluation module 160 is configured to evaluate the classified stationery data, and search data sources, data owners, and data search frequency of the data. The stationery data in the stationery production enterprises can be comprehensively utilized, a user can conveniently search data sources and data owners of the stationery data, repeated stationery data can be deleted, and data storage burden is reduced.
As shown in fig. 2, in the embodiment of the present invention, the system further includes: the data disaster recovery backup module 170 is connected to the data integration module 120 through a wire, and is configured to receive the stationery data to be backed up sent by the data integration module, and backup the received stationery data, so as to help a user to cope with "soft" disasters such as human misoperation, software error and virus intrusion, and "hard" disasters such as hardware fault and natural disaster.
As shown in fig. 3, in this embodiment, the data disaster recovery backup module 170 includes: a data receiving unit 171, a data dividing unit 172, a calculation lookup unit 173, a comparison unit 174, and a data backup unit 175; the data receiving unit 171 is configured to receive stationery data to be backed up sent by the data integrating module. The data dividing unit 172 is configured to divide the stationery data to be backed up to obtain divided stationery data blocks. The calculating and searching unit 173 is configured to calculate a data fingerprint value of the current stationery data block by using a weak check value hash algorithm and a strong check value hash algorithm, and search whether there is a target stationery data block with the same data fingerprint value in the backed-up data file. The comparing unit 174 is configured to, when a target stationery data block with the same data fingerprint value is found in the backed-up data file, perform byte-by-byte comparison between the target stationery data block and the current stationery data block. The data backup unit 175 is configured to backup the current stationery data block according to the comparison result of the comparison unit.
As shown in fig. 4, in the embodiment of the present invention, the system further includes: and the data storage encryption module 180 is connected with the data integration module 120 through a wire and is used for encrypting and storing the original data in the data integration module. The data storage encryption module comprises a security encryption chip and a security decryption chip, and can fully wrap the security of the stored data. For example, when data is stored, a user can input a locking source password, such as a character source password or a fingerprint source password, through the secure encryption chip; when a user needs to check the stored data information, the safety decoding chip pops up an unlocking password instruction input frame for the user to input an unlocking password instruction, matches the unlocking password instruction input by the user with a locking source password, and displays the stored data to the user if the unlocking password instruction input by the user is matched with a preset locking source password; if the unlocking password instruction input by the user is not matched with the preset locking source password, prompting the user that the password is incorrect and asking for re-input; meanwhile, the system is further provided with an unlocking calculation prompting module 190 which is connected with the data storage encryption module 180 through a conducting wire and used for calculating the times of unlocking password instructions input by a user within a preset time, when the times of the unlocking password instructions input by the user within the preset time exceed a preset time threshold, the user is prompted to input an upper limit of the times, and the user tries again in the next day, wherein the preset time threshold can be set according to user requirements or personal wishes, and if the preset time threshold can be set to be 3 times, 4 times, 5 times or 6 times, the limitation is not particularly made, and the unlocking calculation prompting module can further ensure the storage safety of stored data.
As a preferred embodiment, the secure encryption chip and the secure decryption chip may employ a secure socket layer SSL and/or a secure transport layer TLS. The secure encryption chip and the secure decryption chip comprise one or more secure processing units of AES, RSA, SHA, OTP, RNG and GUID.
In this embodiment, the data acquisition module is provided with a data acquisition port. The data search evaluation module includes a data search engine.
The distributed planning system for the stationery information based on the big data provided by the embodiment of the invention can comprehensively utilize the stationery data in the stationery production enterprises, is convenient for users to search the data source and the data owner of the stationery data, can delete the repeated stationery data, and can reduce the data storage burden.
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 (9)
1. A big data-based stationery data distributed planning system, comprising: the system comprises a data acquisition module, a data integration module, a data redundancy judgment module, a data modeling module, a data classification module and a data search evaluation module, wherein the data acquisition module, the data integration module, the data modeling module, the data classification module and the data search evaluation module are sequentially connected through conducting wires; the data redundancy judging module is connected with the data integration module through a wire; the data acquisition module is used for planning and acquiring stationery data and sending the acquired stationery data to the data integration module; the data integration module is used for integrating and screening the acquired stationery data, eliminating useless stationery data from the screened stationery data, reserving the stationery data with the purposes, and taking the reserved stationery data as original data of data planning; the data redundancy judgment module is used for performing redundancy judgment on the original data and deleting repeated stationery data; the data modeling module is used for establishing a data model suitable for original data aiming at the original data; the data classification module is used for planning and classifying the modeled stationery data according to the data source, the data owner and the data search frequency; and the data searching and evaluating module is used for evaluating the classified stationery data and searching the data source, the data owner and the data searching frequency of the data.
2. The big-data based stationery information distributed planning system of claim 1 further comprising: and the data disaster recovery backup module is connected with the data integration module through a wire and used for receiving the stationery data to be backed up sent by the data integration module and backing up the received stationery data.
3. The big-data-based stationery information distributed planning system according to claim 2, wherein said data disaster recovery backup module comprises:
the data receiving unit is used for receiving the stationery data to be backed up sent by the data integration module;
the data dividing unit is used for dividing the stationery data to be backed up to obtain divided stationery data blocks;
the calculation searching unit is used for calculating the data fingerprint value of the current stationery data block by using a weak check value hash algorithm and a strong check value hash algorithm, and searching whether a target stationery data block with the same data fingerprint value exists in a backed-up data file;
the comparison unit is used for comparing the target stationery data block with the current stationery data block byte by byte when the target stationery data block with the same data fingerprint value is found in the backed-up data file; and
and the data backup unit is used for backing up the current stationery data block according to the comparison result of the comparison unit.
4. The big-data based stationery information distributed planning system of claim 1 further comprising: and the data storage encryption module is connected with the data integration module through a wire and is used for encrypting and storing the original data in the data integration module.
5. The big-data-based distributed planning system for stationery information according to claim 4, wherein said data storage encryption module comprises a secure encryption chip and a secure decryption chip.
6. The big-data based distributed planning system for stationery information according to claim 5, wherein said secure encryption chip and said secure decryption chip employ Secure Sockets Layer (SSL) and/or secure Transport Layer (TLS).
7. The big-data-based distributed planning system for stationery information according to claim 6, wherein said secure encryption chip and said secure decryption chip comprise one or more secure processing units of AES, RSA, SHA, OTP, RNG, GUID.
8. The big-data-based stationery data distributed planning system according to claim 1 wherein said data acquisition module is provided with a data acquisition port.
9. The big-data based stationery data distributed planning system of claim 1 wherein said data search evaluation module comprises a data search engine.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2019/087512 WO2020232591A1 (en) | 2019-05-19 | 2019-05-19 | Stationery information distributed planning system based on big data |
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| CN110692045A true CN110692045A (en) | 2020-01-14 |
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| CN201980000974.0A Withdrawn CN110692045A (en) | 2019-05-19 | 2019-05-19 | Big data-based stationery information distributed planning system |
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| WO (1) | WO2020232591A1 (en) |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113780767B (en) * | 2021-08-25 | 2023-12-29 | 中国人民解放军军事科学院战争研究院 | General survey data acquisition and quality evaluation coupling system |
| CN114610797A (en) * | 2022-03-25 | 2022-06-10 | 澜途集思生态科技集团有限公司 | Data distribution planning method based on fluid dynamics |
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| 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 |
| CN104966172A (en) * | 2015-07-21 | 2015-10-07 | 上海融甸信息科技有限公司 | Large data visualization analysis and processing system for enterprise operation data analysis |
| CN106202457A (en) * | 2016-07-17 | 2016-12-07 | 合肥赑歌数据科技有限公司 | A kind of distributed big data schema method |
| CN107370798A (en) * | 2017-07-04 | 2017-11-21 | 深圳齐心集团股份有限公司 | A kind of safe cloud storage system of big data |
| 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 |
| CN108090133A (en) * | 2017-11-24 | 2018-05-29 | 深圳市知小兵科技有限公司 | A kind of information orientation grasping means and system based on internet |
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2019
- 2019-05-19 CN CN201980000974.0A patent/CN110692045A/en not_active Withdrawn
- 2019-05-19 WO PCT/CN2019/087512 patent/WO2020232591A1/en active Application Filing
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN104966172A (en) * | 2015-07-21 | 2015-10-07 | 上海融甸信息科技有限公司 | Large data visualization analysis and processing system for enterprise operation data analysis |
| CN106202457A (en) * | 2016-07-17 | 2016-12-07 | 合肥赑歌数据科技有限公司 | A kind of distributed big data schema method |
| CN107370798A (en) * | 2017-07-04 | 2017-11-21 | 深圳齐心集团股份有限公司 | A kind of safe cloud storage system of big data |
| 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 |
| CN108090133A (en) * | 2017-11-24 | 2018-05-29 | 深圳市知小兵科技有限公司 | A kind of information orientation grasping means and system based on internet |
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