CN114185875A - Big data unified analysis and processing system based on cloud computing - Google Patents
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Abstract
The invention discloses a cloud computing-based big data unified analysis and processing system, and particularly relates to the technical field of cloud computing. The data acquisition module screens and acquires useful complete data information, the data analysis module selects reliable source data and judges the data accuracy by using an accuracy judgment formula to obtain accurate information, the data storage module classifies the information data, sorts and combs the data, the accuracy of unified analysis processing is improved, a data model is built in the data modeling unit, keywords are input through the search engine unit and linked with the keywords in the data model, and the method is favorable for quickly acquiring accurate data information.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a big data unified analysis and processing system based on cloud computing.
Background
The present society is a high-speed society, technology is developed, information is circulated, people are communicated more and more closely, life is more and more convenient, big data is a product of the high-technology era, the big data is generally used for describing a large amount of unstructured and semi-structured data created by a company, and the data can spend excessive time and money when being downloaded to a relational database for analysis. Big data analysis is often tied to cloud computing because real-time large dataset analysis requires a MapReduce-like framework to distribute work to tens, hundreds, or even thousands of computers.
Big data brings our three subversive notions to transition: is full data, not random sampling; is a general direction, not an accurate guide; are related, not causal. The big data era has the characteristics of large data volume, various types, low value density, high speed and high timeliness. The initial measurement unit of the big data is at least P (1000T), including weblog, audio, video, picture, geographical location information and the like, and the multi-type data puts higher requirements on the data processing capability, and most of the data has limited value, relatively low value density, fast data updating speed and high timeliness requirement.
Because the data is complex and the updating speed is high, the value purification of the data needs to be completed more quickly through a powerful machine algorithm, and the method is an urgent problem to be solved in the big data era; the existing technical architecture and route can not process the massive data efficiently, and for related organizations, if the information acquired with huge investment can not feed back effective information by processing in time, the effective data can not be retrieved quickly.
Disclosure of Invention
In order to overcome the above defects in the prior art, embodiments of the present invention provide a cloud computing-based big data unified analysis processing system, useful complete data information is screened and collected by a data collection module, a data analysis module selects reliable source data and judges data accuracy by using an accuracy judgment formula to obtain accurate information, a data storage module performs classification processing on information data, classifies and combs data, and improves the accuracy of unified analysis processing, a data model is built in a data modeling unit, and a search engine unit inputs a keyword to link with the keyword in the data model, which is beneficial to quickly obtaining accurate data information.
In order to achieve the purpose, the invention provides the following technical scheme: a big data unified analysis processing system based on cloud computing comprises a data source server, a central server and a retrieval server, wherein the central server is arranged at the connecting end of the data source server, the retrieval server is arranged at the connecting end of the central server, and a plurality of clients are arranged at the connecting end of the retrieval server;
the data source server is internally provided with a data acquisition module, and the data acquisition module is used for screening useful information data and sending the useful information data to the central server through the Internet of things;
the data analysis module is used for analyzing the acquired information data, analyzing and detecting the reliability of information sources and the accuracy of the data, transferring reasonable information data to the data processing module for classification processing, the data processing module encodes and classifies the information data, the information data are uniformly stored in the data storage module, and the data modeling unit models the same type of data sets and associates content keywords;
and a search engine unit is arranged in the retrieval server and used for inputting keywords and acquiring related data from the central server.
In a preferred embodiment, five storage sub-units, namely a data sub-storage module a, b data sub-storage module, c data sub-storage module, d data sub-storage module and e data sub-storage module, are arranged in the data storage module, and a plurality of different data partitions are arranged in each of the five storage sub-units.
In a preferred embodiment, the data source of the data source server includes manual input, an internet of things and a cloud database, and the client is configured as a mobile phone end or a PC end.
A big data unified analysis and processing system based on cloud computing specifically comprises the following analysis and processing steps:
the method comprises the steps that firstly, data are collected, a data source server is connected with the Internet of things, overall browsing is conducted on overall data in a database, useful complete data information is screened and collected through a data collection module, and the collected information data are sent to a central server through the Internet of things;
step two, data analysis processing, namely receiving data information by a data analysis module, analyzing and detecting the reliability of the information source, screening reliable information sources, rejecting information data of unreliable sources, comparing the screened reliable source information with the data, comparing the difference of the reliable source information, analyzing the accuracy of the data, rejecting the data with large data difference, and obtaining accurate and reliable information data;
step three, data classification storage, namely sending the accurate and reliable information data obtained in the step two to a data storage module, classifying the information data by the data storage module, generating keywords according to the information data source and the related content of the information data, coding the information data according to the related degree of the information data, wherein the codes are a ', b ', c ', d ' and e ', respectively representing the correlations of 0, 25%, 50%, 75% and 100%, classifying the information data with the same codes into one class, respectively storing the five classes of information data in five sub-data storage modules, and classifying the same class of coded information data in a plurality of data partitions according to different contents of the same class of coded information data;
step four, modeling data information, constructing a data similarity model, and associating the information data content classified and stored in the step three with the similarity model;
and step five, data application, namely logging in a retrieval server through a client, inputting keywords in a search engine unit, sending the keywords to a central server through the Internet of things, receiving and carrying the keywords by a data similarity model, quickly editing related contents according to the keywords by a data modeling unit, obtaining retrieval information data, and obtaining a retrieval information data mean value by the retrieval server through a formula.
In a preferred embodiment, the step one uses a data integrity filter to filter, and the data integrity filter is specifically as follows:
|Si-S|/Si<q
and considering the error as a reasonable interval, wherein Si is the data magnitude of single data of the database, S is the average of the data magnitude of each data of the database, q is a judgment fixed value, and the q value is set to be 0.1.
In a preferred embodiment, in the second step, the accuracy of the formula analysis data is judged by using the accuracy, and the expression is as follows:
|Zi-Z|＞T·σ
considering the error as a coarse error, wherein Zi is detection data, Z is a data mean value, T is a discrimination coefficient, and sigma is a standard deviation, designing a variable coefficient self-adaptive Lee-Tech criterion, taking the value of T to be close to zero at the beginning, gradually expanding the value of T, and removing new data points each time until sufficiently accurate information data is obtained.
In a preferred embodiment, the standard deviation is calculated as:
in a preferred embodiment, the data correlation calculation formula in step three is as follows:
and a correlation index W is used for representing the data correlation, j represents the data overall information relation value, and k represents the data splitting information relation value.
In a preferred embodiment, the data similarity model expression in step four is:
the invention has the technical effects and advantages that:
1. useful complete data information is screened and collected through a data collection module, a data analysis module selects reliable source data and judges the data accuracy by using an accuracy judgment formula to obtain accurate information, a data storage module classifies the information data, sorts and combs the data, the accuracy of unified analysis processing is improved, a data model is built in a data modeling unit, keywords are input through a search engine unit and are linked with the keywords in the data model, and the quick acquisition of the accurate data information is facilitated;
2. the information data are classified and processed through the data storage module to generate information data keywords which are convenient to link with search keywords, after the keywords are searched, the keywords are used for reversely searching the database, the data storage module 8 is used for calculating the correlation degree of the search information data through a correlation calculation formula and storing the correlation degree in a plurality of data partitions according to codes, the precision and the efficiency of a data retrieval search are improved, and retrieval results are convenient to check;
3. the integrity degree of the data is calculated through the data integrity filter, the data integrity filter is compared with the data mean value, incomplete information data is eliminated, the accuracy of the information data is judged by using the accuracy judgment formula again, the data with large difference is eliminated, the accuracy of the data is improved, the interference of error information is reduced, and the retrieval efficiency is improved.
Drawings
FIG. 1 is a block diagram of the system architecture of the present invention.
FIG. 2 is a schematic structural diagram of a data storage module according to the present invention.
The reference signs are: the system comprises a data source server 1, a central server 2, a retrieval server 3, a client 4, a data acquisition module 5, a data analysis module 6, a data processing module 7, a data storage module 8, a data modeling unit 9 and a search engine unit 10.
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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
the cloud computing-based big data unified analysis and processing system shown in fig. 1-2 comprises a data source server 1, a central server 2 and a retrieval server 3, wherein the central server 2 is arranged at the connecting end of the data source server 1, the retrieval server 3 is arranged at the connecting end of the central server 2, and a plurality of clients 4 are arranged at the connecting end of the retrieval server 3;
a data acquisition module 5 is arranged in the data source server 1, and the data acquisition module 5 is used for screening useful information data and sending the useful information data to the central server 2 through the Internet of things;
the central server 2 and the retrieval server 3 are internally provided with a data analysis module 6, a data processing module 7, a data storage module 8 and a data modeling unit 9, the data analysis module 6 is used for analyzing the acquired information data, analyzing and detecting the reliability of information sources and the accuracy of the data, and transferring reasonable information data to the data processing module 7 for classification processing, the data processing module 7 encodes and classifies the information data and uniformly stores the information data in the data storage module 8, the data modeling unit 9 models the same type data set and associates content keywords, the data acquisition module 5 screens and acquires useful complete data information, the data analysis module 6 selects reliable source data and judges the accuracy of the data by using an accuracy judgment formula to acquire accurate information, the data storage module 8 classifies and sorts the information data, the accuracy of unified analysis processing is improved, a data model is built in the data modeling unit 9, and keywords are input through the search engine unit 10 to be linked with keywords in the data model, so that the method is favorable for quickly acquiring accurate data information;
a search engine unit 10 is arranged in the retrieval server 3, and the search engine unit 10 is used for inputting keywords and obtaining related data in the central server 2;
furthermore, five storage sub-units, namely a data sub-storage module a, b data sub-storage module b, c data sub-storage module, d data sub-storage module and e data sub-storage module, are arranged in the data storage module 8, and a plurality of different data partitions are arranged in the five storage sub-units;
further, the data source of the data source server 1 comprises manual input, an internet of things and a cloud database, and the client 4 is set as a mobile phone end or a PC end;
useful complete data information is screened and collected through the data collection module 5, the data analysis module 6 selects reliable source data and judges the data accuracy by using an accuracy judgment formula to obtain accurate information, the data storage module 8 classifies the information data, sorts and combs the data, the accuracy of unified analysis and processing is improved, a data model is built in the data modeling unit 9, keywords are input through the search engine unit 10 and are linked with the keywords in the data model, and the method is favorable for quickly obtaining the accurate data information.
Example 2:
according to the cloud computing-based big data unified analysis and processing system shown in fig. 1-2, the system specifically comprises the following analysis and processing steps:
the method comprises the steps that firstly, data are collected, a data source server 1 is connected with the Internet of things, overall browsing is conducted on overall data in a database, useful complete data information is screened and collected through a data collection module 5, and the collected information data are sent to a central server 2 through the Internet of things;
step two, data analysis processing, namely, a data analysis module 6 receives data information, analyzes and detects the reliability of information sources, screens reliable information sources, eliminates information data of unreliable sources, compares the screened reliable source information with data, compares the differences, analyzes the accuracy of the data, eliminates the data with large data difference, and obtains accurate and reliable information data;
step three, data classification storage, namely sending the accurate and reliable information data obtained in the step two to a data storage module 8, classifying the information data by the data storage module 8, generating keywords according to the information data source and the related content of the information data, coding the related degree of the information data into a ', b ', c ', d ' and e ', respectively representing that the correlation is 0, 25%, 50%, 75% and 100%, classifying the information data with the same coding into one class, respectively storing the five classes of information data in five sub-data storage modules, and classifying the same class of coded information data in a plurality of data partitions according to different contents;
step four, modeling data information, constructing a data similarity model, and associating the information data content classified and stored in the step three with the similarity model;
step five, data application, namely logging in the retrieval server 3 through the client 4, inputting keywords in the search engine unit 10, sending the keywords to the central server 2 through the Internet of things, receiving and carrying the keywords by the data similarity model, quickly editing related contents according to the keywords by the data modeling unit 9, obtaining retrieval information data, and obtaining a retrieval information data mean value by the retrieval server 3 through a formula;
further, in the first step, a data integrity filter is used for screening, and the data integrity filter specifically includes:
|Si-S|/Si<q
considering the error as a reasonable interval, wherein Si is a data magnitude of single data of the database, S is an average of data magnitudes of all data of the database, q is a judgment fixed value, and the q value is set to be 0.1;
further, in the second step, the accuracy of the formula analysis data is judged by using the accuracy, and the expression is as follows:
|Zi-Z|＞T·σ
considering the error as a coarse error, wherein Zi is detection data, Z is a data mean value, T is a discrimination coefficient, and sigma is a standard deviation, designing a variable coefficient self-adaptive Lee-Tech criterion, taking the value of T to be close to zero at the beginning, gradually expanding the value of T, and removing new data points each time until sufficiently accurate information data is obtained.
The standard deviation is calculated as:
further, the data correlation calculation formula in step three is as follows:
using a correlation index W to represent data correlation, j to represent a data overall information relation value, and k to represent a data splitting information relation value;
further, the data similarity model expression in the fourth step is as follows:
the points to be finally explained are: firstly: in the drawings of the disclosed embodiments of the invention, only the structures related to the disclosed embodiments are referred to, other structures can refer to common designs, and the same embodiment and different embodiments of the invention can be combined with each other without conflict;
and finally: 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, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.
Claims (8)
1. The utility model provides a big data unified analysis processing system based on cloud calculates, includes data source server (1), central server (2) and search server (3), its characterized in that: a central server (2) is arranged at the connecting end of the data source server (1), a retrieval server (3) is arranged at the connecting end of the central server (2), and a plurality of clients (4) are arranged at the connecting end of the retrieval server (3);
a data acquisition module (5) is arranged in the data source server (1), and the data acquisition module (5) is used for screening useful information data and sending the useful information data to the central server (2) through the Internet of things;
the central server (2) and the retrieval server (3) are internally provided with a data analysis module (6), a data processing module (7), a data storage module (8) and a data modeling unit (9), the data analysis module (6) is used for analyzing acquired information data, analyzing and detecting the reliability of information sources and the accuracy of the data, and transferring reasonable information data to the data processing module (7) for classification processing, the data processing module (7) encodes and classifies the information data, the information data are uniformly stored in the data storage module (8), and the data modeling unit (9) models the same-kind data sets and associates content keywords;
a search engine unit (10) is arranged in the retrieval server (3), and the search engine unit (10) is used for inputting keywords and obtaining related data in the central server (2).
2. The cloud computing-based big data unified analysis and processing system according to claim 1, wherein: the data storage module (8) is internally provided with five storage sub-units, namely a data sub-storage module a, a data sub-storage module b, a data sub-storage module c, a data sub-storage module d and a data sub-storage module e, and a plurality of different data partitions are arranged in the five storage sub-units.
3. The cloud computing-based big data unified analysis and processing system according to claim 1, wherein: the data source of the data source server (1) comprises manual input, the Internet of things and a cloud database, and the client (4) is set to be a mobile phone end or a PC end.
4. The cloud computing-based big data unified analysis and processing system according to claims 1-3, wherein: the method specifically comprises the following analysis and processing steps:
the method comprises the steps that firstly, data are collected, a data source server (1) is connected with the Internet of things, overall browsing is conducted on overall data in a database, useful complete data information is screened and collected through a data collection module (5), and the collected information data are sent to a central server (2) through the Internet of things;
step two, data analysis processing, namely a data analysis module (6) receives data information, analyzes and detects the reliability of information sources, screens reliable information sources, eliminates information data of unreliable sources, compares the data of the screened reliable source information, compares the difference of the reliable source information and the reliability of the analysis data, eliminates the data with large data difference and obtains accurate and reliable information data;
step three, data classification storage, namely sending the accurate and reliable information data obtained in the step two to a data storage module (8), classifying the information data by the data storage module (8), generating keywords according to the information data source and the related content of the information data, coding the related degree of the information data into a ', b ', c ', d ' and e ', respectively representing that the correlation is 0, 25%, 50%, 75% and 100%, classifying the information data with the same coding into one class, respectively storing the five classes of information data in five sub-data storage modules, and classifying the same coding information data in a plurality of data partitions according to different contents;
step four, modeling data information, constructing a data similarity model, and associating the information data content classified and stored in the step three with the similarity model;
and step five, data application, namely logging in the retrieval server (3) through the client (4), inputting keywords in the search engine unit (10), sending the keywords to the central server (2) through the Internet of things, receiving and carrying the keywords in the data similarity model, quickly editing related contents according to the keywords by the data modeling unit (9), obtaining retrieval information data, and obtaining the retrieval information data mean value by the retrieval server (3) through a formula.
5. The cloud computing-based big data unified analysis and processing system according to claim 4, wherein: screening by using a data integrity screener in the first step, wherein the data integrity screener specifically comprises the following steps:
|Si-S|/Si<q
and considering the error as a reasonable interval, wherein Si is the data magnitude of single data of the database, S is the average of the data magnitude of each data of the database, q is a judgment fixed value, and the q value is set to be 0.1.
6. The cloud computing-based big data unified analysis and processing system according to claim 4, wherein: in the second step, the accuracy of formula analysis data is judged by using the accuracy, and the expression is as follows:
|Zi-Z|＞T·σ
considering the error as a coarse error, wherein Zi is detection data, Z is a data mean value, T is a discrimination coefficient, and sigma is a standard deviation, designing a variable coefficient self-adaptive Lee-special criterion, taking the value of T to be close to zero at the beginning, gradually enlarging the value of T, and removing new data points each time until sufficiently accurate information data is obtained;
the standard deviation is calculated as:
7. the cloud computing-based big data unified analysis and processing system according to claim 4, wherein: the data correlation calculation formula in the third step is as follows:
and a correlation index W is used for representing the data correlation, j represents the data overall information relation value, and k represents the data splitting information relation value.
8. The cloud computing-based big data unified analysis and processing system according to claim 4, wherein: the data similarity model expression in the fourth step is as follows:
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