CN113051234A - Mobile on-site big data analysis platform - Google Patents
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- CN113051234A CN113051234A CN202110420446.XA CN202110420446A CN113051234A CN 113051234 A CN113051234 A CN 113051234A CN 202110420446 A CN202110420446 A CN 202110420446A CN 113051234 A CN113051234 A CN 113051234A
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Abstract
The invention discloses a mobile on-site big data analysis platform, which belongs to the technical field of big data analysis and comprises a data search module, a data source data capture module, a data collection and storage module, a data analysis module, a data storage cloud, a data conversion module, a data display module and a data selection module, wherein the data search module is in communication connection with the data source data capture module, and the data collection and storage module is in communication connection with the data source data capture module and the data analysis module; according to the invention, by deleting the junk information in the data, a user can conveniently check the data, the network environment is protected, the data is sorted from new to old according to the searching time, the latest data can be conveniently inquired by the staff, the inquiring time of the staff is saved, and the working efficiency is improved.
Description
Technical Field
The invention relates to the technical field of big data analysis, in particular to a mobile field big data analysis platform.
Background
Big data analysis refers to analysis of huge-scale data, wherein the big data can be summarized into 5V, the data size is large (Volume), the speed is high (Velocity), the types are multiple (Variety), the Value (Value) and the authenticity (Veracity), the big data is used as the vocabulary of the IT industry which is the most hot at present, the utilization of commercial values of data warehouse, data security, data analysis, data mining and the like around the big data gradually becomes the profit focus for industry people to pursue, the big data analysis is generated along with the coming of the big data era, the high-efficiency data and analysis capability ensures the best fraud prevention level, the safety of the whole enterprise organization is improved, so that the enterprise can rapidly detect and predict fraud activities, and simultaneously identify and track the hitter; therefore, it becomes especially important to invent a mobile field big data analysis platform;
through retrieval, Chinese patent No. CN109086396A discloses an old-age-care big data analysis platform, which can display data change conditions in real time in various visual modes, but can not filter redundant information, influence a user to check data and damage network environment, secondly, the existing mobile field big data analysis platform can not order data according to time, and a worker often inquires the data which is too old, thereby wasting the inquiry time of the worker and reducing the working efficiency.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a mobile field big data analysis platform.
In order to achieve the purpose, the invention adopts the following technical scheme:
the mobile field big data analysis platform comprises a data search module, a data source data capture module, a data collection and storage module, a data analysis module, a data storage cloud, a data conversion module, a data display module and a data selection module;
the data acquisition and storage module is in communication connection with the data source data acquisition module, the data acquisition and storage module is in communication connection with the data source data acquisition module and the data analysis module, the data analysis module is in communication connection with the data storage cloud and the data conversion module, and the data display module is in communication connection with the data conversion module and the data selection module;
the data search module comprises a data input module and a query information processing module;
the data collection and storage module comprises a data collection unit, a data classification unit and a data storage unit;
the data analysis module comprises a data analysis unit and a file conversion unit.
Further, the data input unit is used for a user to input keywords corresponding to data to be queried and generate search data through data conversion, the query information processing unit is used for receiving search information and performing judgment analysis processing on the search information to generate search data, and the specific judgment analysis steps are as follows:
the method comprises the following steps: if the search data conforms to the data search specification, processing the search data to generate the search data;
step two: and if the search data does not accord with the data search specification, feeding back a user data query format error.
Further, the data source data fetching module is used for receiving the search data and starting to fetch the data from different data sources, and processing the data to generate initial data, wherein the different data sources include ODBC, C3P0 and DBCP.
Further, the data collecting unit is used for receiving the initial data and converting the initial data into screening data according to the definition of the data dictionary, the data classifying unit is used for receiving the screening data and performing classification cleaning processing to generate template data, and the specific classification cleaning steps are as follows:
step (1): classifying the screening data according to different types, wherein the different types comprise articles, videos and junk advertisements, and simultaneously marking the classified screening data as A, B, C;
step (2): a, B, C, the data are screened, and the screening process comprises the following steps:
the first step is as follows: deleting A, B, C garbage advertisements to obtain A and B;
the second step is that: deleting the bad information in A, B to generate a and b;
and the data storage unit is used for receiving the data a and the data b and converting the data a and the data b into temporary storage data in a file form according to the definition of the data dictionary.
Further, the data analysis module is configured to receive a and b and perform analysis sorting processing on the received a and b to generate selection data, and the specific analysis sorting steps are as follows:
i, collecting the generation time of each data in a and b;
II, carrying out data arrangement on the data in the a and the b according to the latest data to the old data at different time ends;
and III, converting the arranged a and b into text forms, processing the text forms to generate selection data, and sending the selection data to a data storage cloud.
Further, the data storage cloud is used for processing the selection data to generate storage data and storing the storage data.
Further, the data conversion module is used for receiving the selection data, processing the selection data to generate graphic data and sending the graphic data to the data display module, and the data display module is used for displaying the graphic data.
Further, the data selection module is used for selecting the display data of the corresponding time period when the user needs to check the past data, and the specific retrieval steps are as follows:
s1: the user inputs the primary time period X to be searched in the data selection module;
s2: inputting the secondary time period X again after the user inputs the primary time period X;
s3: after the user inputs the primary time period X and the secondary time period X, the data selection module calls the content required by the user from the storage display module and displays the content through the data display module.
Compared with the prior art, the invention has the beneficial effects that:
1. the data analysis module is arranged and used for collecting the generation time of each data in a and b after receiving the data a and b, arranging the data in the data a and b according to the latest data to the old data at different time ends, converting the arranged data a and b into a text form, processing the text form to generate selection data, and sending the selection data to the data storage cloud end to sort the data from the new data to the old data according to the search time, so that a worker can conveniently inquire the latest data, the inquiry time of the worker is saved, and the working efficiency is improved;
2. the invention is provided with a data collection unit, a data source data capturing module captures data from ODBC, C3P0 and DBCP and processes the data to generate initial data, the data collection unit is used for receiving the initial data and converting the initial data into screening data according to the definition of a data dictionary, the data classification unit is used for receiving the screening data and performing classification cleaning processing, the screening data is classified according to different types, wherein the different types comprise articles, videos and junk advertisements, the classified screening data is respectively marked as A, B, C, the junk advertisements in A, B, C are deleted, A and B are remained, the bad information in A, B is deleted to generate a and B, the junk information in the data is deleted, a user can conveniently view the data, and the network environment is protected.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a system block diagram of a mobile field big data analysis platform according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Referring to fig. 1, the mobile field big data analysis platform comprises a data search module, a data source data capture module, a data collection and storage module, a data analysis module, a data storage cloud, a data conversion module, a data display module and a data selection module;
the data acquisition and storage module is in communication connection with the data source data acquisition module, the data acquisition and storage module is in communication connection with the data source data acquisition module and the data analysis module, the data analysis module is in communication connection with the data storage cloud and the data conversion module, and the data display module is in communication connection with the data conversion module and the data selection module;
the data searching module comprises a data input module and a query information processing module;
the data collection and storage module comprises a data collection unit, a data classification unit and a data storage unit;
the data analysis module comprises a data analysis unit and a file conversion unit.
The specific scheme of the embodiment is as follows: the data input unit is used for inputting keywords corresponding to the data to be inquired by a user and generating search data through data conversion, the inquiry information processing unit is used for receiving the search information and carrying out judgment analysis processing on the search information to generate search data, and the specific judgment analysis steps are as follows:
the method comprises the following steps: if the search data conforms to the data search specification, processing the search data to generate the search data;
step two: and if the search data does not accord with the data search specification, feeding back a user data query format error.
The data source data grabbing module is used for receiving the search data and starting to grab the data from different data sources and process the data to generate initial data, wherein the different data sources comprise ODBC, C3P0 and DBCP.
The data collection unit is used for receiving initial data and converting the initial data into screening data according to the definition of the data dictionary, the data classification unit is used for receiving the screening data and performing classification cleaning processing to generate template data, and the specific classification cleaning steps are as follows:
step (1): classifying the screening data according to different types, wherein the different types comprise articles, videos and junk advertisements, and simultaneously marking the classified screening data as A, B, C;
step (2): a, B, C, the data are screened, and the screening process comprises the following steps:
the first step is as follows: deleting A, B, C garbage advertisements to obtain A and B;
the second step is that: deleting the bad information in A, B to generate a and b;
in the specific embodiment of the invention, data are captured from ODBC, C3P0 and DBCP through a data source data capture module and processed to generate initial data, a data collection unit is used for receiving the initial data and converting the initial data into screening data according to the definition of a data dictionary, a data classification unit is used for receiving the screening data and performing classification cleaning processing, the screening data are classified according to different types, wherein the different types comprise articles, videos and junk advertisements, the classified screening data are respectively marked as A, B, C, the junk advertisements in A, B, C are deleted, A and B are remained, the bad information in A, B is deleted to generate a and B, the junk information in the data is deleted, a user can conveniently view the data, and the network environment is protected.
The specific scheme of the embodiment is as follows: the data storage unit is used for receiving the data a and the data b and converting the data a and the data b into temporary storage data in a file form according to the definition of the data dictionary.
The data analysis module is used for receiving a and b and carrying out analysis sorting processing on the a and b to generate selection data, and the specific analysis sorting steps are as follows:
i, collecting the generation time of each data in a and b;
II, carrying out data arrangement on the data in the a and the b according to the latest data to the old data at different time ends;
and III, converting the arranged a and b into text forms, processing the text forms to generate selection data, and sending the selection data to a data storage cloud.
In the specific embodiment of the invention, the data analysis module receives a and b and then collects the generation time of each data in a and b, data arrangement is carried out on the data in a and b according to the latest data to the old data according to different time ends, the arranged data a and b are converted into text forms and processed to generate selection data, and simultaneously the selection data are sent to the data storage cloud end, the data are sequenced from the new to the old according to the searching time, so that the latest data can be conveniently inquired by workers, the inquiring time of the workers is saved, the working efficiency is improved,
the specific scheme of the embodiment is as follows: and the data storage cloud is used for processing the selected data to generate storage data and storing the storage data.
The data conversion module is used for receiving the selection data, processing the selection data to generate graphic data and sending the graphic data to the data display module, and the data display module is used for displaying the graphic data.
The data selection module is used for selecting the display data of the corresponding time period when the user needs to check the past data, and the specific retrieval steps are as follows:
s1: the user inputs the primary time period X to be searched in the data selection module;
s2: inputting the secondary time period X again after the user inputs the primary time period X;
s3: after the user inputs the primary time period X and the secondary time period X, the data selection module calls the content required by the user from the storage display module and displays the content through the data display module.
The working principle and the using process of the invention are as follows: the user inputs keywords corresponding to the data to be inquired through the data input unit and generates search data through data conversion, the inquiry information processing unit is used for receiving the search information and judging, analyzing and processing the search information, if the search data conforms to the data search specification, the search data is processed to generate the search data, if the search data does not conform to the data search specification, the feedback user data inquiry format is wrong, the data source data capture module starts to receive the search data and starts to capture the data from different data sources and process the data to generate initial data, wherein the different data sources comprise ODBC, C3P0 and DBCP, after the initial data are sent to the data collection unit, the data collection unit converts the initial data into screening data according to the definition of a data dictionary, the data classification unit is used for receiving the screening data and performing classification and cleaning processing, and classifying the screening data according to different types, wherein different types include articles, videos and junk advertisements, the classified screening data are respectively marked as A, B, C, the junk advertisements in A, B, C are deleted, A and B are remained, bad information in A, B is deleted to generate a and B, a data storage unit is used for receiving the a and B and converting the bad information into temporary storage data in a file form according to the definition of a data dictionary, a data analysis module receives the a and B and then analyzes and sorts the data, the generation time of each data in the a and B is collected, data arrangement is performed on the data in the a and B according to different time ends from latest data to old data, the arranged a and B are converted into a text form and processed to generate selection data, and meanwhile, the selection data are sent to a data storage cloud, the data storage cloud processes the selection data to generate storage data and stores the storage data, the data conversion module receives the selection data, processes the selection data to generate graphic data and sends the graphic data to the data display module, the data display module starts to display the graphic data, when a user checks the past data through the data selection module, the user inputs a primary time period X to be searched in the data selection module, the user inputs a secondary time period X after inputting the primary time period X, and after the user inputs the primary time period X and the secondary time period X, the data selection module calls the content required by the user from the storage display module and displays the content through the data display module.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. The mobile field big data analysis platform is characterized by comprising a data search module, a data source data capture module, a data collection and storage module, a data analysis module, a data storage cloud, a data conversion module, a data display module and a data selection module;
the data acquisition and storage module is in communication connection with the data source data acquisition module, the data acquisition and storage module is in communication connection with the data source data acquisition module and the data analysis module, the data analysis module is in communication connection with the data storage cloud and the data conversion module, and the data display module is in communication connection with the data conversion module and the data selection module;
the data search module comprises a data input module and a query information processing module;
the data collection and storage module comprises a data collection unit, a data classification unit and a data storage unit;
the data analysis module comprises a data analysis unit and a file conversion unit.
2. The mobile field big data analysis platform according to claim 1, wherein the data input unit is used for a user to input keywords corresponding to data to be queried and generate search data through data conversion, the query information processing unit is used for receiving search information and performing judgment analysis processing on the search information to generate search data, and the specific judgment analysis steps are as follows:
the method comprises the following steps: if the search data conforms to the data search specification, processing the search data to generate the search data;
step two: and if the search data does not accord with the data search specification, feeding back a user data query format error.
3. The mobile onsite big data analysis platform of claim 1, wherein the data source data capture module is configured to receive search data and start capturing data from different data sources, and processing the data to generate initial data, wherein the different data sources include ODBC, C3P0, and DBCP.
4. The mobile field big data analysis platform as claimed in claim 1, wherein the data collection unit is configured to receive initial data and convert the initial data into filtered data according to the definition of the data dictionary, and the data classification unit is configured to receive the filtered data and perform classification and cleaning processing to generate template data, and the specific classification and cleaning steps are as follows:
step (1): classifying the screening data according to different types, wherein the different types comprise articles, videos and junk advertisements, and simultaneously marking the classified screening data as A, B, C;
step (2): a, B, C, the data are screened, and the screening process comprises the following steps:
the first step is as follows: deleting A, B, C garbage advertisements to obtain A and B;
the second step is that: deleting the bad information in A, B to generate a and b;
and the data storage unit is used for receiving the data a and the data b and converting the data a and the data b into temporary storage data in a file form according to the definition of the data dictionary.
5. The mobile field big data analysis platform according to claim 4, wherein the data analysis module is configured to receive a and b and perform analysis sorting processing on the received a and b to generate the selection data, and the specific analysis sorting steps are as follows:
i, collecting the generation time of each data in a and b;
II, carrying out data arrangement on the data in the a and the b according to the latest data to the old data at different time ends;
and III, converting the arranged a and b into text forms, processing the text forms to generate selection data, and sending the selection data to a data storage cloud.
6. The mobile field big data analysis platform according to claim 5, wherein the data storage cloud is used for processing and saving the selected data to generate storage data.
7. The mobile onsite big data analysis platform according to claim 5, wherein the data conversion module is configured to receive the selection data, process the selection data to generate graphic data, and send the graphic data to the data display module, and the data display module is configured to display the graphic data.
8. The mobile field big data analysis platform according to claim 1, wherein the data selection module is configured to select the display data corresponding to the time period when the user needs to check the past data, and the specific search steps are as follows:
s1: the user inputs the primary time period X to be searched in the data selection module;
s2: inputting the secondary time period X again after the user inputs the primary time period X;
s3: after the user inputs the primary time period X and the secondary time period X, the data selection module calls the content required by the user from the storage display module and displays the content through the data display module.
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| CN117729252A (en) * | 2024-02-01 | 2024-03-19 | 深圳承典电子有限公司 | Edge computing system integrating multiple algorithm models |
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Application publication date: 20210629 |