Query language auditing system

Abstract

The invention discloses an auditing system for a query language. The auditing system comprises a cloud management module, an inspection module and a server module, the server module is connected with the checking module and used for collecting the initial query language to be checked and sending the initial query language to the checking module; the checking module is respectively connected with the server module and the cloud management module, and is used for receiving the initial query language sent by the server module and checking the initial query language to obtain a target query language passing the checking; the cloud management module is connected with the checking module and used for providing a target database corresponding to the target query language for the checking module; the checking module is further used for simulating and executing the target query language on the target database to obtain state information of the target query language, and the state information comprises an abnormal state or a normal state. The method and the device aim at improving efficiency and accuracy of query language auditing and reducing auditing cost at the same time.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and more specifically, to an audit system for query language. Background Art

[0002] With the rapid development of information technology, databases are the core components of information systems, and their performance is crucial to ensuring the stable operation of the entire system and data security. As the standard language of relational databases, query languages ​​are widely used in various database management systems. The quality and efficiency of query languages ​​directly affect the performance of databases. Therefore, the review of query languages ​​has become an indispensable part of database development, testing, release, production and operation.

[0003] In the related art, the query language is usually audited through audit tools. However, this method has certain limitations. It requires manual entry of the query language, which has the risk of missed detection, high audit costs and low audit efficiency. Secondly, this method often makes it difficult to comprehensively evaluate the performance of the query language, so the audit accuracy is low. Summary of the invention

[0004] In view of this, the present invention provides a query language audit system, the query language audit system is intended to improve the efficiency and accuracy of query language audit while reducing the audit cost.

[0005] In order to achieve the above object, the present invention adopts the following technical scheme:

[0006] The present invention provides an audit system for query language, the audit system comprising a cloud management module, an inspection module and a server module;

[0007] A server module, connected to the inspection module, for collecting the initial query language to be reviewed and sending the initial query language to the inspection module;

[0008] The inspection module is connected to the server module and the cloud management module respectively, and is used to receive the initial query language sent by the server module, and inspect the initial query language to obtain a target query language that passes the inspection;

[0009] A cloud management module is connected to the inspection module and is used to provide the inspection module with a target database corresponding to the target query language;

[0010] The checking module is also used to simulate the execution of the target query language on the target database to obtain the state information of the target query language, wherein the state information includes an abnormal state or a normal state.

[0011] In one possible implementation, the audit system also includes a publishing module, which is connected to the checking module and is used to send a checking command to the checking module in response to receiving a publishing request, so that the checking module checks the initial query module after receiving the checking command to obtain the target query language.

[0012] In a possible implementation, the publishing module is further configured to receive status information of the target query language sent by the checking module, and stop the publishing process when the status information is in an abnormal state.

[0013] In a possible implementation, the checking module checks the initial query language to obtain a target query language that passes the check, including:

[0014] The checking module performs an initial deduplication operation on the initial query language to obtain the initial query language after the initial deduplication;

[0015] The checking module performs a syntax check on the initial query language after the first deduplication, and obtains a target query language after the check passes.

[0016] In a possible implementation, the checking module performs an initial deduplication operation on the initial query language to obtain the initial deduplication-free initial query language, including:

[0017] The inspection module removes the preset field value of the initial query language, and converts the initial query language after the preset field value is removed into a cryptographic hash function;

[0018] In response to determining that the encrypted hash function has not been processed, the checking module determines the initial query language corresponding to the encrypted hash function as the initial query language after the first deduplication.

[0019] In a possible implementation, the checking module simulates executing the target query language on the target database to obtain state information of the target query language, including:

[0020] The checking module performs a secondary deduplication operation on the target query language on the target database to obtain the target query language after secondary deduplication;

[0021] The checking module performs semantic checking on the target query language after secondary deduplication to obtain semantic checking results;

[0022] The checking module obtains the state information of the target query language at least according to the semantic checking result.

[0023] In a possible implementation, the checking module obtains the state information of the target query language at least according to the semantic checking result, including:

[0024] The checking module determines that the state information of the target query language is in an abnormal state in response to the semantic checking result being failed;

[0025] In response to the semantic check result being passed, the check module performs an execution efficiency check on the target query language after the semantic check to obtain an execution efficiency check result;

[0026] The checking module obtains the status information of the target query language according to the execution efficiency checking result.

[0027] In a possible implementation, the checking module obtains the state information of the target query language according to the execution efficiency checking result, including:

[0028] The checking module determines that the state information of the target query language is in an abnormal state in response to the execution efficiency checking result being failed;

[0029] In response to the semantic check result being passed, the checking module determines that the state information of the target query language is in a normal state.

[0030] In a possible implementation, the checking module performs semantic checking on the target query language after secondary deduplication, and obtains semantic checking results, including:

[0031] The checking module determines whether the target query language after secondary deduplication satisfies the preset statement type;

[0032] In response to determining that the target query language after the second deduplication satisfies the preset statement type, the checking module determines that the semantic checking result is passed;

[0033] In response to determining that the target query language after secondary deduplication does not satisfy a preset statement type, the checking module determines that a semantic checking result is failed.

[0034] In a possible implementation, the audit system further includes a front-end module, which is connected to the inspection module and is used to display status information of the target query language.

[0035] Compared with the prior art, the audit system of the query language provided by the present invention achieves at least the following beneficial effects: the audit system includes a cloud management module, an inspection module and a server module; the server module is connected to the inspection module, and is used to collect the initial query language to be audited, and send the initial query language to the inspection module; the inspection module is connected to the server module and the cloud management module respectively, and is used to receive the initial query language sent by the server module, and to check the initial query language to obtain the target query language that has passed the inspection; the cloud management module is connected to the inspection module, and is used to provide the inspection module with a target database corresponding to the target query language; the inspection module is also used to simulate the execution of the target query language on the target database to obtain the status information of the target query language, wherein the status information includes an abnormal state or a normal state. The audit system of the query language of the present invention automatically collects the initial query language through the server module, and sends it to the inspection module for audit, which reduces manual intervention and improves the efficiency and accuracy of the audit. Further, the inspection module can not only check the initial query language, but also simulate the execution of the target query language through the target database provided by the cloud management module to obtain the status information of the target query language. The above audit system can realize the audit of the target query language while improving the efficiency and accuracy of the query language audit and reducing the audit cost.

[0036] Of course, any product implementing the present invention does not necessarily need to achieve all of the above technical effects at the same time.

[0037] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0039] Figure 1 It is a structural diagram of a query language audit system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0041] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0042] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0043] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0044] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0045] Reference Figure 1 , Figure 1 It is a structural diagram of an audit system for a query language provided by an embodiment of the present invention. Among them, the audit system 100 includes a cloud management module 11, an inspection module 12 and a server module 13. The server module 13 is connected to the inspection module 12, and is used to collect the initial query language to be audited, and send the initial query language to the inspection module 12; the inspection module 12 is connected to the server module 13 and the cloud management module 11 respectively, and is used to receive the initial query language sent by the server module 13, and check the initial query language to obtain a target query language that passes the inspection; the cloud management module 11 is connected to the inspection module 12, and is used to provide the inspection module 12 with a target database corresponding to the target query language; the inspection module 12 is also used to simulate the execution of the target query language on the target database to obtain the status information of the target query language, wherein the status information includes an abnormal state or a normal state.

[0046] It should be noted that a query language is a computer language used to interact with a database or information system. Users can use the query language to send requests to the system to retrieve, update, delete or insert data. Query languages ​​can be used to access and manipulate structured data in a database, allowing users to extract the required data simply and directly while ensuring efficient interaction with the database or information system.

[0047] For example, the server module 13 can collect the initial query language to be reviewed from the outside, and send the initial query language to the inspection module 12 for further processing. The inspection module 12 can check the initial query language to ensure the legality of the initial query language, whether the format is correct, whether it meets the prescribed standards, etc. After the inspection, the initial query language will be converted into the target query language. Furthermore, the inspection module 12 can not only check the syntax and structure of the initial query language, but also confirm its execution effect through simulated execution. Specifically, the target query language can be simulated and executed on the target database provided by the cloud management module 11 to avoid running potentially risky queries directly in the production environment. Among them, the result of the simulated execution will generate a status information, and the status information includes an abnormal state or a normal state. The abnormal state indicates that there may be problems with the query language, such as syntax errors, insufficient permissions, overly complex queries, etc.; the normal state indicates that the query language can be successfully executed on the target database.

[0048] For example, the main function of the cloud management module 11 is to provide the target database required for the target query language execution to the inspection module 12, and to assist the inspection module 12 in completing the simulated execution of the query, and to dynamically allocate appropriate database resources according to the content of the target query language.

[0049] By way of example, the query language includes but is not limited to SQL (Structured Query Language), XQuery (XML Query Language), SPARQL (SPARQL Protocol and RDFQuery Language), and Datalog (Data Logic Query Language), etc. The present invention is described using SQL as an example.

[0050] SQL is a database query language that is widely used in relational databases. SQL allows users to perform various operations, such as querying data (ˋSELECTˋ), inserting data (ˋINSERTˋ), updating data (ˋUPDATEˋ), and deleting data (ˋDELETEˋ). SQL usually uses the ˋSELECTˋ statement, which can specify the columns and tables to be queried, and can accurately query through conditions, sorting, and grouping. Its simple and intuitive syntax makes it the foundation of the database field.

[0051] For example, the server module 13 includes a plugin, which adds specific functions or extended functions to an existing software application without modifying the core code of the application. Plugins are usually modular, and users can enable or disable different plugins according to their needs to customize the functions of the application. In the present invention, the plugin on the server can be responsible for collecting the initial query language to be reviewed. After the plugin collects the initial query language, it reports the initial query language to the inspection module 12 through the interface provided by the inspection module 12.

[0052] For example, the cloud management module 11 includes database metadata, which is information about database structure and data, and is used to define and describe the structure, tables, columns, indexes, constraints, views, and other information about the configuration and organization of the database system.

[0053] The audit system 100 of the query language provided by the present invention achieves at least the following beneficial effects: the audit system 100 includes a cloud management module 11, an inspection module 12 and a server module 13; the server module 13 is connected to the inspection module 12, and is used to collect the initial query language to be audited, and send the initial query language to the inspection module 12; the inspection module 12 is connected to the server module 13 and the cloud management module 11 respectively, and is used to receive the initial query language sent by the server module 13, and to check the initial query language to obtain the target query language that has passed the inspection; the cloud management module 11 is connected to the inspection module 12, and is used to provide the inspection module 12 with a target database corresponding to the target query language; the inspection module 12 is also used to simulate the execution of the target query language on the target database, and obtain the status information of the target query language, wherein the status information includes an abnormal state or a normal state. The audit system 100 of the query language of the present invention automatically collects the initial query language through the server module 13, and sends it to the inspection module 12 for audit, which reduces manual intervention and improves the efficiency and accuracy of the audit. Furthermore, the checking module 12 can not only check the initial query language, but also simulate the execution of the target query language through the target database provided by the cloud management module 11 to obtain the status information of the target query language. The above-mentioned audit system 100 can improve the efficiency and accuracy of the query language audit while auditing the target query language, and reduce the audit cost.

[0054] Optionally, the audit system 100 also includes a publishing module 14, which is connected to the checking module 12 and is used to send a checking command to the checking module 12 in response to receiving a publishing request, so that the checking module 12 checks the initial query module after receiving the checking command to obtain the target query language.

[0055] The release module 14 may include BONE. BONE is a system for software, content or update release management, and its main functions generally include: version management, managing different versions of content or software to ensure the orderly release of versions; automated release, pushing content, code, etc. to the target server or user device through scripts or automated tools; rollback mechanism, if there is a problem with the released content, it can be quickly rolled back to the previous version; log and monitoring, tracking logs during the release process, monitoring whether the release is successful and the operating status of the system; permission management, assigning release permissions to different users to ensure that only the right people can perform release operations.

[0056] For example, the publishing module 14 can manage the publishing process of the query language. When there is a publishing request, the publishing module 14 can respond to the request and send a check command to the checking module 12 to start the checking process of the initial query language. After receiving the check command, the checking module 12 will check the initial query language according to a predetermined process, obtain the target query language, simulate the execution of the target query language, and generate relevant status information.

[0057] The above embodiments can automatically respond to publishing requests and start the inspection process based on the publishing module 14 without human intervention, thereby reducing human errors and the audit cost of the query language and improving the efficiency of query language audit and publishing.

[0058] Optionally, the publishing module 14 is further configured to receive the state information of the target query language sent by the checking module 12, and stop the publishing process when the state information is in an abnormal state.

[0059] For example, the publishing module 14 can not only start the inspection process, but also receive the status information sent by the inspection module 12. When the status information of the target query language is in a normal state, the publishing module 14 can allow the publishing process to continue, that is, allow the publishing operation of the query language. If the status information is in an abnormal state, such as a query syntax error, high execution risk or other potential problems, the publishing module 14 will stop the publishing process, thereby preventing the problematic query language from being published to the actual database or environment, and avoiding impact or errors on the system.

[0060] Optionally, the checking module 12 checks the initial query language to obtain a target query language that passes the check, including: the checking module 12 performs an initial deduplication operation on the initial query language to obtain the initial query language after the initial deduplication; the checking module 12 performs a syntax check on the initial query language after the initial deduplication to obtain the target query language that passes the check.

[0061] For example, the checking module 12 can remove field values ​​that do not affect the actual execution, or other optional query parameters in the initial query language, thereby being able to obtain the deduplicated initial query language based on the initial deduplication operation, and then perform a syntax check on the initial query language after the initial deduplication to obtain the target query language after the check passes.

[0062] The above method can prevent the execution of repeated query statements, thereby improving query efficiency and reducing resource waste.

[0063] Optionally, the checking module 12 performs an initial deduplication operation on the initial query language to obtain the initial query language after the initial deduplication, including: the checking module 12 removes the preset field value of the initial query language, and converts the initial query language after removing the preset field value into an encrypted hash function; in response to determining that the encrypted hash function has not been processed, the checking module 12 determines the initial query language corresponding to the encrypted hash function as the initial query language after the initial deduplication.

[0064] The preset field value is used to represent the field value in the initial query language that does not affect the actual execution, for example, including but not limited to comments, blank characters, etc.

[0065] For example, the inspection module 12 can remove the preset field values ​​of the initial query language and convert the processed initial query language into an encrypted hash function. The encrypted hash function is a fixed-length string generated by the query language through an encrypted hash algorithm. Each unique query language will generate a different hash value, while the same query will generate the same hash value. In this way, the inspection module 12 can quickly determine whether a query language has been processed and check whether the generated encrypted hash function already exists. If the query language corresponding to the hash value has been processed, it can be identified that this is a repeated query, so there is no need to check and execute it again, thereby saving system resources.

[0066] The above method can avoid repeated processing of duplicate queries based on the initial deduplication operation, saving system computing resources and significantly improving system performance and response speed. Furthermore, effective deduplication through encrypted hash functions can avoid redundant query execution, reduce database load, and optimize system resource usage.

[0067] Optionally, the checking module 12 simulates the execution of the target query language on the target database to obtain the status information of the target query language, including: the checking module 12 performs a secondary deduplication operation on the target query language on the target database to obtain the target query language after the secondary deduplication; the checking module 12 performs a semantic check on the target query language after the secondary deduplication to obtain a semantic check result; the checking module 12 obtains the status information of the target query language at least based on the semantic check result.

[0068] On the basis of the above embodiment, the checking module 12 performs a semantic check on the target query language after the second deduplication and obtains a semantic check result, including: the checking module 12 determines whether the target query language after the second deduplication satisfies the preset statement type; the checking module 12 determines that the semantic check result is passed in response to determining that the target query language after the second deduplication satisfies the preset statement type; the checking module 12 determines that the semantic check result is failed in response to determining that the target query language after the second deduplication does not satisfy the preset statement type.

[0069] By way of example, the secondary deduplication operation includes, but is not limited to, checking whether the target database has enabled the audit of the target query language, whether the verification of the target query language has passed, whether the target database is the database corresponding to the target query language, whether the release task has enabled the audit, and whether the target query language is in the whitelist, etc. The present invention is not limited to this.

[0070] For example, after all the verifications of the above secondary deduplication operations are passed, the target query language after secondary deduplication can be obtained. Thus, the execution of repeated query operations can be avoided, thereby effectively saving database load, ensuring the uniqueness and efficiency of the query, and preventing redundant operations.

[0071] For example, a semantic check may be performed on the target query language after the second deduplication to obtain a semantic check result. That is, it is determined whether the target query language after the second deduplication satisfies the preset statement type. The preset statement type includes but is not limited to INSERT, DML (Data Manipulation Language), SELECT, and UPDATE.

[0072] It should be noted that INSERT is a data manipulation language operation used to insert new records into a database table. There are usually two ways: inserting a single or multiple specific data records, and selecting data from other tables through SELECT statements and inserting them into the target table. DML is a data manipulation language used to insert, update, delete and query data. SELECT is a query data operation used to retrieve data from the database. UPDATE is used to update existing records and modify data in the table.

[0073] For example, after the target query language after secondary deduplication satisfies the above preset statement type, the semantic check result can be determined as passed; if it is determined that the target query language after secondary deduplication does not satisfy the preset statement type, the semantic check result is determined as failed.

[0074] The above method not only avoids the execution of repeated queries, but also identifies potential logical problems in the query language and generates corresponding status information for system decision-making, which improves the security and efficiency of query execution and makes the audit of query language more stable and efficient.

[0075] Optionally, the checking module 12 obtains the status information of the target query language at least based on the semantic check result, including: the checking module 12 determines that the status information of the target query language is an abnormal state in response to the semantic check result being a failure; the checking module 12 performs an execution efficiency check on the target query language after the semantic check in response to the semantic check result being a pass, and obtains an execution efficiency check result; the checking module 12 obtains the status information of the target query language based on the execution efficiency check result.

[0076] On the basis of the above embodiment, the checking module 12 obtains the status information of the target query language according to the execution efficiency check result, including: the checking module 12 determines that the status information of the target query language is in an abnormal state in response to the execution efficiency check result being failed; the checking module 12 determines that the status information of the target query language is in a normal state in response to the semantic check result being passed.

[0077] For example, the semantic check can be used to detect the logical correctness of the target query language, that is, whether the content of the query statement conforms to the grammatical rules and can be correctly parsed and executed. If the result of the semantic check is not passed, it indicates that there are semantic errors in the target query language, such as incorrect syntax or logical inconsistency. Therefore, the checking module 12 can confirm the state information of the target query language as an abnormal state. If the result of the semantic check is passed, it indicates that the target query language is logically correct, so the efficiency check can be further performed.

[0078] For example, the execution efficiency check is used to evaluate the performance of the query execution, such as the complexity of the query, the response time, the resource usage and other indicators. If the result of the execution efficiency check is not passed, it indicates that the target query language exhibits low efficiency or performance bottlenecks during the execution process, and the state information of the target query language is determined to be abnormal. If the result of the execution efficiency check is passed, it indicates that the target query language is not only grammatically correct, but also has good performance during execution, and the inspection module 12 can determine the state information of the target query language as normal.

[0079] For example, the execution efficiency check includes, but is not limited to, checking whether the target query language is a SELECT statement, whether the target query language is a complex query language, whether the SELECT execution time of the target query language is greater than the timeout time, etc. Further, when the target query language is a SELECT statement, the target query language is not a complex query language, and the SELECT execution time of the target query language is greater than the timeout time, it can be determined that the execution efficiency check result is passed, that is, the state information of the target query language is determined to be in a normal state.

[0080] The above method can effectively identify and handle syntax errors and performance issues in the target query language, and improve the accuracy of the target query language review.

[0081] Optionally, the audit system 100 further includes a front-end module 15 , which is connected to the checking module 12 and is used to display status information of the target query language.

[0082] For example, the front-end module 15 can also display the review status, that is, the status information of the target query language, the database, the initial query language to be reviewed, the operator and the time, etc. Thus, the user can search for the above conditions based on personal demand information.

[0083] Although some specific embodiments of the present invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will be appreciated by those skilled in the art that the above embodiments may be modified without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A query language audit system, characterized in that: The audit system includes a cloud management module, an inspection module and a server module; The server module is connected to the checking module and is used to collect the initial query language to be reviewed and send the initial query language to the checking module; The inspection module is connected to the server module and the cloud management module respectively, and is used to receive the initial query language sent by the server module, and inspect the initial query language to obtain a target query language that passes the inspection; The cloud management module is connected to the inspection module and is used to provide the inspection module with a target database corresponding to the target query language; The checking module is further used for simulating the execution of the target query language on the target database to obtain state information of the target query language, wherein the state information includes an abnormal state or a normal state.

2. The audit system according to claim 1, characterized in that: The audit system also includes a publishing module, which is connected to the checking module and is used to send a checking command to the checking module in response to receiving a publishing request, so that the checking module checks the initial query module after receiving the checking command to obtain the target query language.

3. The audit system according to claim 2, characterized in that: The publishing module is further configured to receive the state information of the target query language sent by the checking module, and stop the publishing process when the state information is the abnormal state.

4. The audit system according to claim 1, characterized in that: The checking module checks the initial query language to obtain a target query language that passes the check, including: The checking module performs a primary deduplication operation on the initial query language to obtain the initial query language after the primary deduplication; The checking module performs a syntax check on the initial query language after the first deduplication to obtain a target query language after the check passes.

5. The audit system according to claim 4, characterized in that: The checking module performs a primary deduplication operation on the initial query language to obtain the initial query language after the primary deduplication, including: The checking module removes the preset field value of the initial query language, and converts the initial query language after the preset field value is removed into an encrypted hash function; In response to determining that the cryptographic hash function has not been processed, the checking module determines the initial query language corresponding to the cryptographic hash function as the initial query language after the first deduplication.

6. The audit system according to claim 1, characterized in that: The checking module simulates and executes the target query language on the target database to obtain status information of the target query language, including: The checking module performs a secondary deduplication operation on the target query language on the target database to obtain a target query language after secondary deduplication; The checking module performs semantic checking on the target query language after the second deduplication to obtain a semantic checking result; The checking module obtains the state information of the target query language at least according to the semantic checking result.

7. The audit system according to claim 6, characterized in that: The checking module obtains the state information of the target query language at least according to the semantic checking result, including: The checking module determines, in response to the semantic checking result being a failure, that the state information of the target query language is the abnormal state; In response to the semantic check result being passed, the check module performs an execution efficiency check on the target query language after the semantic check to obtain an execution efficiency check result; The checking module obtains the state information of the target query language according to the execution efficiency checking result.

8. The audit system according to claim 7, characterized in that: The checking module obtains the state information of the target query language according to the execution efficiency checking result, including: The checking module determines, in response to a failure in the execution efficiency checking result, that the state information of the target query language is the abnormal state; In response to the semantic check result being passed, the checking module determines that the state information of the target query language is the normal state.

9. The audit system according to claim 7, characterized in that: The checking module performs semantic checking on the target query language after the second deduplication, and obtains a semantic checking result, including: The checking module determines whether the target query language after the second deduplication satisfies a preset statement type; The checking module determines that the semantic checking result is passed in response to determining that the target query language after the second deduplication satisfies the preset statement type; In response to determining that the target query language after the second deduplication does not satisfy the preset statement type, the checking module determines that the semantic checking result is failed.

10. The audit system according to claim 1, characterized in that: The audit system further comprises a front-end module, which is connected to the inspection module and is used to display the status information of the target query language.

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