A query system based on data analysis

Abstract

The present invention relates to a query system based on data analysis, and in particular to the technical field of database management. The query system comprises a user information management module for implementing dynamic authority management for users, a data source management module for managing user requests, caches, data sources and data security, and a database management module for managing a number of databases. The present invention analyzes the query request of the user to determine whether the user request exists in the cache, so as to determine the selection of the query mode for the query request, thereby making flexible selections in the query process, and setting different supervision strengths in the corresponding query mode to supervise the query process, thereby improving the accuracy of control over the data query process.

Description

Technical Field

[0001] The present invention relates to the technical field of database management, and in particular to a query system based on data analysis. Background Art

[0002] In today's big data context, query analysis is a very important module. By writing SQL query statements and visualization methods, analysts can quickly perform data exploration queries on the data warehouse, data mart, and business database within the platform, view relevant library table information and query logs, etc., to verify the accuracy of data task execution and complete tasks such as query data sharing.

[0003] However, in actual business, there may be heterogeneous data in multiple data sources that need to be jointly queried, and data query and permission control need to be implemented in scenarios such as multi-tenant, multi-environment, and cross-project. Due to technical differences between different data sources and large data scale, query efficiency is low and it is difficult to meet business needs.

[0004] Chinese Patent Publication No.: CN108984582B discloses a query request processing method, the method comprising: S1: receiving a user query request to obtain a keyword ordered group; S2: processing the keyword ordered group to obtain an intermediate keyword ordered group; S3: performing a search engine-based query based on the intermediate keyword ordered group. The invention can process the query request input by the user from multiple levels, incorporate personalized corrections based on big data analysis, and deeply characterize the user query request by completing the user query request, so as to better meet the actual needs of the user; it can be seen that the existing technology has the problem of not being able to accurately control the data in multiple databases during the query process, resulting in the problem that data query efficiency and data security cannot be guaranteed. Summary of the invention

[0005] To this end, the present invention provides a query system based on data analysis to overcome the problem in the prior art that it is not possible to accurately control the data existing in multiple databases during the query process, thereby resulting in the inability to guarantee data query efficiency and data security.

[0006] To achieve the above object, the present invention provides a query system based on data analysis, comprising:

[0007] User information management module, which is used to implement dynamic rights management for users;

[0008] A data source management module, which is connected to the user information management module, and includes:

[0009] A request acquisition unit, which is used to acquire a query request from a user;

[0010] a data analysis unit, configured to determine the selection of a query mode for the query request based on whether the query request and similar data exist in the cache, and determine supervision of the query request under the corresponding query mode;

[0011] A cache management unit, configured to determine creation of a cache for the query request based on an interface of a data source required by the query request;

[0012] A data management unit, which is used to manage the data source during the query process;

[0013] A security management unit, which is used to perform security management on the data queried by the query request;

[0014] An optimization unit, which is used to determine optimization for the current query process based on historical query requests under the corresponding query mode, and to determine adjustment of the supervision of the query request by the data analysis unit based on the usage frequency of similar information data of the data source pooled by the cache management unit through the connection pool and the data source of the query request;

[0015] The database management module is connected to the data source management module and is used to manage a number of databases.

[0016] Furthermore, the data analysis unit determines whether there is data similar to the query request in the cache under the condition that the request acquisition unit obtains the query request of the user, so as to determine the selection of a query mode for the query request, and the selection includes determining supervision of the query request when there is no similar data to the query request; or performing a secondary selection of the query mode when there is similar data to the query request.

[0017] Further, the data analysis unit determines that supervision of the query request includes parsing the query request, determining a target database corresponding to the query request, determining an evaluation value of a degree of association between the query request and the data source, and determining to execute a supervisory query based on a comparison result that the evaluation value of the degree of association is greater than a preset evaluation value of the degree of association.

[0018] Furthermore, when executing a supervisory query, the data analysis unit determines the supervisory intensity of the supervisory query based on a comparison result in which the difference between the association degree evaluation value and a preset association degree evaluation value is less than or equal to a preset difference, and performs supervision on operations on a preset proportion of sensitive data during the query request process.

[0019] Furthermore, when executing a supervisory query, the data analysis unit determines the supervisory intensity of the supervisory query based on a comparison result in which the difference between the association degree evaluation value and the preset association degree evaluation value is greater than the preset difference, and performs supervision on operations on a preset proportion of the query data during the query request process.

[0020] Furthermore, the data analysis unit determines, under the condition of secondary selection of the query mode, that the query request is a direct execution query request based on a comparison result that a similarity between the data in the cache and the query request is greater than a similarity threshold.

[0021] Furthermore, under the condition of secondary selection of the query mode, the data analysis unit determines the query request to execute the query request and associates the supervision of the data query process in the cache based on the comparison result that the similarity between the data in the cache and the query request is less than or equal to a similarity threshold.

[0022] Furthermore, the cache management unit determines the creation of a cache for the query request based on the interface of the data source required by the query request, including setting the cache ratio of each data in the status, log, execution parameter, return column and result to eighty-five percent and sixty percent data ratio for cache execution respectively.

[0023] Furthermore, the optimization unit determines a historical accuracy of historical query requests in a corresponding query mode, and determines compensation for the cache or adjustment of a preset association degree evaluation value based on an accuracy difference between the historical accuracy and an accuracy standard.

[0024] Furthermore, based on the usage frequency of similar information data between the data source pooled by the cache management unit through the connection pool and the data source of the query request, the adjustment of the supervision of the query request by the data analysis unit is determined, including adjusting the supervision intensity by an adjustment coefficient based on a comparison result that the usage frequency is less than a usage frequency threshold.

[0025] Compared with the prior art, the beneficial effect of the present invention lies in that the present invention analyzes the user's query request to determine whether the user request exists in the cache, so as to determine the selection of the query mode for the query request, thereby allowing flexible selection during the query process, and by setting different supervision intensities under the corresponding query mode to perform supervision of the query process, the accuracy of control over the data query process is improved, thereby improving data query efficiency and security.

[0026] Furthermore, the present invention determines the number of interfaces of the data source in the database corresponding to the query request under the corresponding query mode, so as to determine the creation method for the cache, thereby realizing flexible control of the query process, and under the corresponding creation method, performs caching of the status, log, execution parameters, return columns and results of each data with different cache ratios, thereby further improving the accuracy of control over the data query process, thereby improving the data query efficiency and security.

[0027] Furthermore, the present invention can dynamically associate permissions: using user information obtained by the user center and metadata management module, dynamic permission association is achieved to ensure that users can only access data for which they have permission, thereby improving data security and privacy protection levels.

[0028] The present invention can update and synchronize data sources in real time: integrate the user center and metadata management module to achieve real-time data source update and synchronization, ensure that the query analysis module can always access the latest data, and improve the real-time and accuracy of the data.

[0029] The present invention can intelligently optimize query and improve performance: utilizing intelligent link selection scheme to select the optimal query path and result set, improve query efficiency and performance, and speed up data query and analysis.

[0030] The present invention can provide one-stop data query and analysis: integrating the user center and metadata management module, realizing one-stop data query and analysis services, and improving work efficiency and user experience.

[0031] The present invention can ensure data security and privacy protection: through multi-level permission control and sensitive data desensitization technology, data security and privacy protection are ensured, and only authorized users can access specific data.

[0032] The present invention can achieve efficient caching and performance optimization: combining full-link efficient caching technology, reducing database operations, improving query performance and response speed, accelerating data query and analysis processes, and improving the overall performance and response speed of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of the structure of a query system based on data analysis according to an embodiment of the present invention;

[0034] Figure 2 A flowchart of determining a query mode in a query system based on data analysis according to an embodiment of the present invention;

[0035] Figure 3 The present invention is a flowchart of determining cache creation in a query system based on data analysis in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0037] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0038] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0039] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal connection of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0040] In the field of big data, query analysis is a very important function that can help enterprises and organizations obtain useful information from massive data. However, there are still problems with the existing query analysis function in the field of big data. For example, joint query of heterogeneous data from multiple data sources. Enterprises often use multiple data sources, which may include relational databases, NoSQL databases, and data lakes. The data structures and storage methods between them may be different. Therefore, it is necessary to be able to implement joint query across data sources so that data can be analyzed under a unified view. Multi-tenant, multi-environment, and cross-project data query and permission control. In large organizations, different departments or projects may need to access and analyze shared data, but they also need to ensure the security and isolation of the data. Therefore, it is necessary to establish a complete multi-tenant data query and permission control mechanism to ensure that only authorized users can access specific data and that data is isolated between different environments and projects. Inefficient query. Traditional query methods are inefficient and cannot meet real-time requirements. Therefore, it is necessary to introduce optimized query engines and technologies, such as data partitioning, index optimization, and query caching, to improve query efficiency and performance.

[0041] The technical differences and complexity between different data sources are also a challenge. For example, the query syntax and performance characteristics of relational databases and NoSQL databases are different, so it is necessary to select appropriate query tools and technologies for different data sources.

[0042] Automatic SQL query generation tools allow users to select the required database tables and fields in a simple interactive way, and then describe the expected results to automatically generate the corresponding SQL query statements. This tool can automatically build the structure of SQL query statements based on user selections, and provide real-time preview and verification functions to ensure that the generated query statements meet user expectations.

[0043] Security issues: Since big data platforms often contain sensitive data, security has become a critical consideration. To ensure data security, we need to adopt strict identity authentication and access control measures, as well as data encryption technology to protect the confidentiality and integrity of the data.

[0044] Subscription task SQL and periodic report generation: Users may need to subscribe to data of a specific type or condition in order to periodically generate reports or perform other subsequent processing. To achieve this requirement, it is necessary to design the SQL query of the subscription task and integrate it with the timing scheduling system to generate reports or perform other tasks at the specified time. Ensure that the report can be generated on time and sent to relevant users.

[0045] To sum up, in the face of the above challenges, it is necessary to comprehensively use appropriate tools and technologies, such as distributed query engines, data virtualization, and permission management systems, to achieve efficient, secure, and reliable big data query and analysis functions.

[0046] The query system based on data analysis in the embodiment of the present invention adopts one-stop data query, integrates the user center and source data management module, supports data query of multiple data by providing a unified query entry interface, and supports joint query of multiple data sources. It supports export and subscription of queried data, supports the selection of library tables for people who are not familiar with SQL, and then intelligently generates the required SQL through a large model for reference and use after writing the requirements, provides rich query functions and visual analysis tools, and meets the diverse needs of users for data.

[0047] In the embodiments of the present invention, identity authentication and access control measures are both existing technologies and will not be described in detail here.

[0048] See also Figure 1-Figure 3 As shown, Figure 1 is a schematic diagram of the structure of a query system based on data analysis according to an embodiment of the present invention, Figure 2 A flowchart of determining a query mode in a query system based on data analysis according to an embodiment of the present invention; Figure 3The present invention is a flowchart of determining cache creation in a query system based on data analysis in an embodiment of the present invention.

[0049] The query system based on data analysis in the embodiment of the present invention includes:

[0050] User information management module, which is used to implement dynamic rights management for users;

[0051] A data source management module, which is connected to the user information management module, includes:

[0052] A request acquisition unit for acquiring a user's query request,

[0053] a data analysis unit for analyzing the query request,

[0054] A cache management unit for caching the query data according to the data query situation and usage situation,

[0055] A data management unit used to manage data sources during the query process.

[0056] A security management unit for performing security management on the data queried by the query request,

[0057] and an optimization unit for optimizing the query process;

[0058] The database management module is connected to the data source management module and is used to manage a number of databases.

[0059] In the embodiment of the present invention, several databases include but are not limited to Data storage, Oracle--Oracle database, Mysq l, Postgresq l and SQL Server.

[0060] In the embodiment of the present invention, the user information management module uses the dynamic permission association function to query the permissions of the user according to the user login information, and associates with the metadata of the data source, database, data table and table details, and adds permission verification logic before the database query statement and in the query to ensure that users can only access the data for which they have permission. Add permission logic when querying the table. Double-click to jump to the approval center. If the approval is passed, the permission center will have application information. If the user has handwritten a library, table, or column without permission, parse SQL in the query to obtain the library, table, and column information. Query the authentication interface here to prevent the invalidation of permissions.

[0061] In the query system based on data analysis of the embodiment of the present invention, the data analysis unit determines whether there is data similar to the query request in the cache under the condition that the request acquisition unit acquires the query request of the user, so as to determine the selection of the query mode for the query request;

[0062] If not, the data analysis unit determines to execute the query request in a first query mode;

[0063] If so, the data analysis unit determines to perform a secondary selection on the query mode.

[0064] Specifically, the data analysis unit analyzes the query request in the first query mode, determines the target database corresponding to the query request, determines the correlation evaluation value between the query request and the data source, and determines whether to execute the supervisory query according to the comparison result between the correlation evaluation value and the preset correlation evaluation value;

[0065] If the association degree evaluation value is greater than a preset association degree evaluation value, the data analysis unit determines to perform a supervisory query on the query request;

[0066] If the association degree evaluation value is less than or equal to a preset association degree evaluation value, the data analysis unit determines to perform an unsupervised query on the query request.

[0067] In the embodiment of the present invention, the preset association degree evaluation value is 0.3, which is obtained when there is one target database and the proportion of sensitive data is 20% of the data volume in the corresponding database. However, the value is not limited to this, and technicians in this field can also adjust the value according to actual conditions.

[0068] Specifically, the data analysis unit calculates the association degree evaluation value according to the following formula, setting:

[0069]

[0070] Among them, Z represents the association degree evaluation value, Wi represents the amount of sensitive data in the i-th target database, Wz is the total amount of data in the i-th target database, n is the number of target databases, and Y is the proportion of target databases corresponding to the query request.

[0071] In the embodiment of the present invention, the target database ratio is the ratio of the target database to the total number of databases.

[0072] Specifically, the data analysis unit calculates the difference between the association degree evaluation value and the preset association degree evaluation value under the supervision query condition, and determines the supervision intensity under the supervision query condition according to the comparison result between the difference and the preset difference;

[0073] If the difference is less than or equal to a preset difference, the data analysis unit determines the supervision intensity of the supervisory query to be to supervise the operation of a preset proportion of sensitive data during the query request query process;

[0074] If the difference is greater than a preset difference, the data analysis unit determines the supervision intensity of the supervisory query as supervising the operation of a preset proportion of the query data during the query request query process.

[0075] In the embodiment of the present invention, the preset ratio is 80%, but the value is not limited thereto, and those skilled in the art may also adjust the value according to actual conditions.

[0076] In the embodiment of the present invention, the preset difference value is 0.2, but the value is not limited thereto, and those skilled in the art may also adjust the value according to actual conditions.

[0077] Specifically, the data analysis unit determines the selection of the query mode of the query request according to the similarity between the data in the cache and the query request under the condition of secondary selection of the query mode;

[0078] If the similarity is greater than the similarity threshold, the data analysis unit determines to execute the query request in a third query mode, where the third query mode is to directly execute the query request;

[0079] If the similarity is less than or equal to the similarity threshold, the data analysis unit determines to execute the query request in a second query mode, where the second query mode is to execute the query request and associate it with supervision of the data query process in the cache.

[0080] In an embodiment of the present invention, the similarity is the ratio of the request data of a single historical query request in the cache and the same data amount of the query request to the total amount of request data of a single historical query request in the cache, and the similarity threshold is 0.8.

[0081] In the query system based on data analysis in the embodiment of the present invention, the cache management unit determines whether to cache the query request and its corresponding query process and the cache creation method in a corresponding query mode.

[0082] Specifically, when the request acquisition unit obtains the query request, the cache management unit generates a unique key for the query SQL and returns it to the front end, and performs SQL verification, SQL replacement, SQL parsing, and SQL desensitization operations asynchronously; obtains the data source link, and packages the status, logs, execution parameters, return columns, and results of this process into the cache, using full-link efficient caching technology to establish a cache system, reduce database operations, and improve query performance and response speed. Data query frequency and usage, optimize cache strategies, and ensure that commonly used data and query results can be cached in time and respond quickly. The data of the exported results and the execution of the subscription tasks do not need to be executed again. You only need to obtain parameters in the cache. At the same time, the catalog log for the joint query does not need to be created every time. You only need to query the cache. If it does not exist, create it again. After creation, put it into the cache, which greatly improves the execution efficiency of the entire system.

[0083] Specifically, the cache management unit determines the creation mode according to a comparison result between the number of interfaces of the data source required by the query request and a preset number under the cache creation mode determination condition;

[0084] If the number of interfaces is less than or equal to the preset number, the cache management unit determines to create the cache in a first creation mode;

[0085] If the number of interfaces is greater than the preset number, the cache management unit determines to create the cache in a second creation mode.

[0086] In the embodiment of the present invention, the value of the preset number is 5, but the value is not limited thereto, and those skilled in the art may also adjust the value according to actual conditions.

[0087] Specifically, the cache management unit sets the cache ratio of each data in the status, log, execution parameter, return column and result to 85% data ratio execution cache in the first creation mode;

[0088] In the second creation mode, the cache management unit sets the cache ratio of each data in the status, log, execution parameter, return column and result to 60% data ratio for execution cache.

[0089] In the query system based on data analysis of the embodiment of the present invention, the optimization unit determines the historical accuracy of historical query requests in the corresponding query mode, and determines whether to optimize the query process according to the comparison result of the historical accuracy and the accuracy standard;

[0090] If the historical accuracy rate is less than the accuracy rate standard, the optimization unit determines to optimize the query process;

[0091] If the historical accuracy is greater than or equal to the accuracy standard, the optimization unit determines not to optimize the query process.

[0092] In the embodiment of the present invention, the value of the accuracy standard is 0.8, but the value is not limited thereto, and those skilled in the art may also adjust the value according to actual conditions.

[0093] Specifically, the optimization unit calculates the accuracy difference between the historical accuracy and the accuracy standard under the optimization condition for the query process, and determines the optimization method for the corresponding query mode according to the comparison result of the accuracy difference and the preset accuracy difference;

[0094] If the accuracy difference is less than or equal to a preset accuracy difference, the optimization unit determines to compensate the cache ratio with a compensation coefficient;

[0095] If the accuracy difference is greater than a preset accuracy difference, the optimization unit determines to adjust the preset correlation degree evaluation value by an adjustment coefficient.

[0096] In the embodiment of the present invention, the preset accuracy difference value is 0.15, but the value is not limited thereto, and those skilled in the art may also adjust the value according to actual conditions.

[0097] Specifically, the optimization unit calculates the compensation coefficient according to the following formula and sets:

[0098] X = log 3.5 (2-△P)+0.8

[0099] Wherein, X is the compensation coefficient, and ΔP is the accuracy difference.

[0100] Specifically, the optimization unit calculates the adjustment coefficient according to the following formula and sets:

[0101] K = 1-log 2.5 (△P+1)

[0102] Wherein, K is the adjustment coefficient, and ΔP is the accuracy difference.

[0103] Specifically, the optimization unit determines whether to adjust the supervision intensity based on the comparison result of the usage frequency of information data whose information similarity between the information of the data source pooled by the cache management unit through the connection pool and the information of the data source of the current query request is greater than the preset similarity and the usage frequency threshold value under the condition that the cache creation is completed;

[0104] If the usage frequency is less than the usage frequency threshold, the optimization unit determines to adjust the supervision intensity;

[0105] If the usage frequency is greater than or equal to the usage frequency threshold, the optimization unit determines not to adjust the supervision intensity.

[0106] In the embodiment of the present invention, the information data includes but is not limited to database links, threads and data structures.

[0107] In the embodiment of the present invention, the preset similarity value is 0.95, and the usage frequency threshold value is 0.6, but the above values ​​are not limited thereto, and those skilled in the art may also adjust the similarity according to actual needs.

[0108] Specifically, the optimization unit determines the adjustment coefficient to adjust the supervision intensity according to the usage frequency and the usage frequency threshold under the condition of adjusting the supervision intensity, and sets:

[0109]

[0110] Wherein, A is the adjustment coefficient, R is the usage frequency, and R0 is the usage frequency threshold.

[0111] In the embodiment of the present invention, the preset ratio of the supervision of the operation on sensitive data or the supervision of the operation on query data under the adjusted supervision intensity is set to 0.8A.

[0112] In the embodiment of the present invention, a large number of data source links are prevented during the query process, and the data source information of the original data management is cached in redis through a unique key. When querying, the data source information is pooled through the pool2 connection pool to reduce the number of links and improve the query efficiency. The event-driven mechanism is designed through zk to update and synchronize metadata information from the data source in real time. At the same time, the new data source will be verified using the md5 value, and the link information will not be updated accordingly.

[0113] In the embodiment of the present invention, the security center and the authority center of the original data management are integrated. The above mentioned library table authority also supports row and column authority. It also supports desensitization of multiple dimensions of data. After the SQL is parsed, the library table and field information of the parsed SQL will be called at the same time by the authority center and the security center. The authority center will return whether there is authority. If there is authority, the conditions of the row authority will be spliced ​​into a where condition (such as where id < 100). Data security will encrypt or intercept the queried library table field through various functions to generate a new SQL return. At this time, the SQL of the security center and the where condition of the authority center are spliced ​​together, and the original SQL subquery or with statement is spliced ​​to achieve data security and limit the access rights of sensitive data. Through syntax analysis and query rule optimization, the best query execution plan is selected. Using the optimizer algorithm, according to the structure, conditions and data distribution of the query statement, the appropriate index, partition and connection method are dynamically selected, and the execution efficiency of different engines in the recent period of time is recorded. According to the strategies of different dimensions, the fastest executing engine is selected to improve query performance.

[0114] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0115] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A query system based on data analysis, characterized in that: include: User information management module, which is used to implement dynamic rights management for users; A data source management module, which is connected to the user information management module, and includes: A request acquisition unit, which is used to acquire a user's query request; A data analysis unit, which is used to determine the selection of a query mode for the query request based on whether there is similar data between the query request and the cache, and determine the supervision intensity of the query request under the corresponding query mode; A cache management unit, configured to determine a cache ratio for the query request based on the number of interfaces of the data source required by the query request; A process optimization unit, which is used to determine the optimization of the corresponding query mode based on the historical query requests under the corresponding query mode, and to determine the adjustment of the proportion of the supervision of the operation of the sensitive data or query data corresponding to the supervision intensity of the query request by the data analysis unit based on the usage frequency of similar information data of the data source pooled by the cache management unit through the connection pool and the data source of the query request; A database management module, which is connected to the data source management module and is used to manage a number of databases; The process optimization unit determines the historical accuracy of historical query requests in the corresponding query mode, and determines compensation for the cache or adjustment of the preset relevance evaluation value based on the accuracy difference between the historical accuracy and the accuracy standard; The process optimization unit calculates the compensation coefficient according to the following formula and sets: Wherein, X is the compensation coefficient, and ΔP is the accuracy difference; The process optimization unit calculates the adjustment coefficient according to the following formula and sets: Wherein, K is the adjustment coefficient, and ΔP is the accuracy difference.

2. The query system based on data analysis according to claim 1, characterized in that: The data analysis unit determines whether there is data similar to the query request in the cache under the condition that the request acquisition unit obtains the query request of the user, so as to determine the selection of a query mode for the query request, wherein the selection includes determining supervision of the query request when there is no data similar to the query request; or performing a secondary selection of the query mode when there is data similar to the query request.

3. The query system based on data analysis according to claim 2, characterized in that: The data analysis unit determines that supervision of the query request includes parsing the query request, determining a target database corresponding to the query request, determining an evaluation value of the degree of association between the query request and the data source, and determining to execute a supervisory query based on a comparison result that the evaluation value of the degree of association is greater than a preset evaluation value of the degree of association.

4. The query system based on data analysis according to claim 3 is characterized in that: When executing a supervisory query, the data analysis unit determines the supervisory intensity of the supervisory query based on a comparison result that the difference between the association degree evaluation value and the preset association degree evaluation value is less than or equal to the preset difference, and performs supervision on operations on a preset proportion of sensitive data during the query request process.

5. The query system based on data analysis according to claim 4 is characterized in that: When executing a supervisory query, the data analysis unit determines the supervisory intensity of the supervisory query based on a comparison result that the difference between the association degree evaluation value and the preset association degree evaluation value is greater than the preset difference, and performs supervision on operations on a preset proportion of the query data during the query request query process.

6. The query system based on data analysis according to claim 5, characterized in that: The data analysis unit determines, under the condition of secondary selection of the query mode, that the query request is a direct execution query request based on a comparison result that a similarity between the data in the cache and the query request is greater than a similarity threshold.

7. The query system based on data analysis according to claim 6, characterized in that: The data analysis unit determines the query request as supervision of executing the query request and associating the query process of the data in the cache based on the comparison result that the similarity between the data in the cache and the query request is less than or equal to a similarity threshold under the condition of secondary selection of the query mode.

8. The query system based on data analysis according to claim 7, characterized in that: The cache management unit determines the creation of a cache ratio for the query request based on the number of interfaces of the data source required by the query request, including setting the cache ratio of each data in the status, log, execution parameter, return column and result to a first ratio or a second ratio of data ratio to execute the cache, wherein the values ​​of the first ratio and the second ratio are different.

9. The query system based on data analysis according to claim 1, characterized in that: The process optimization unit determines the adjustment of the supervision of the query request by the data analysis unit based on the usage frequency of similar information data between the data source of the query request and the data source of the query request through the connection pool pooled by the cache management unit, including adjusting the proportion of supervision performed on the operation of sensitive data or query data corresponding to the supervision intensity by an adjustment coefficient according to the comparison result that the usage frequency is less than the usage frequency threshold.

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