CN113704306B - Database data processing method and device, storage medium and electronic equipment - Google Patents
Database data processing method and device, storage medium and electronic equipment Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The embodiment of the invention discloses a data processing method, a data processing device, a storage medium and electronic equipment of a database, wherein the method firstly acquires all flow data and all query sentences of the database; then constructing a virtual table according to each flow data and query statement; and performing hierarchical classification processing on the virtual table. The method constructs the data information searched in a certain time into the virtual table based on the data flow and the query statement, so that the data information which is not searched in a certain time, namely the cold data, is removed, and the cold data is not classified in a grading manner when the virtual table is classified in a grading manner, thereby reducing the complexity of the data classification and improving the effect of the data classification.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a data processing method and apparatus for a database, a storage medium, and an electronic device.
Background
Currently, database applications have been extended to various fields, with more and more data being deposited. The subsequent mass data can cause leakage and even tampering of sensitive data in various links such as acquisition, storage, use, outgoing and the like. The data classification and grading strategy is introduced to realize automatic classification and grading of the database, the table and the field, so that different storage, audit and security management strategies are implemented for different types or grades of data, and the efficiency of data security management is improved while the accurate security management of the data is realized.
However, some cold data exists in the database, namely, data which is not searched for in a long time, and the existing data classification method still classifies the cold data in a classification mode, and classification of the cold data is invalid, so that the complexity of data classification is increased, and the effect of data classification is affected.
Disclosure of Invention
In view of this, embodiments of the present invention provide a data processing method, apparatus, storage medium, and electronic device for a database, which mainly solve the problem that the existing data classification method still performs classification on the cold data, but the classification on the cold data is ineffective, thereby increasing the complexity of the data classification and affecting the effect of the data classification.
In a first aspect, an embodiment of the present invention provides a data processing method of a database, including:
acquiring all flow data and all query sentences of a database;
constructing a virtual table according to each flow data and query statement;
and carrying out hierarchical classification processing on the virtual table.
In one possible implementation manner, the constructing a virtual table according to each data flow and query statement includes:
analyzing each query statement to obtain target table information and target field information, wherein the target table information is information of a table searched by the query statement, and the target field information is information of a field searched by the query statement;
based on each flow data, obtaining data information transmitted by each flow data;
and constructing a virtual table according to all the target table information, the target field information and the data information.
In one possible implementation manner, the classifying the virtual table in a grading manner includes:
judging whether the data information of each virtual table is a sensitive table, and if the virtual table is the sensitive table, determining the type of the sensitive table; and if the virtual table is not a sensitive table, determining that the virtual table is a non-sensitive table.
In one possible implementation manner, the determining whether each virtual table is a sensitive table includes:
judging whether the target field information of each virtual table is sensitive information, and if the target field information of the virtual table is sensitive information, determining that the virtual table is a sensitive table; and if all the target field information of the virtual table is not sensitive information, determining that the virtual table is not a sensitive table.
In one possible implementation manner, the determining that the virtual table is a sensitive table further includes:
determining the position of sensitive information of the sensitive table and the type of the sensitive information;
based on the position of the sensitive information and the type of the sensitive information, searching the sensitive information and marking a label corresponding to the type.
In one possible implementation manner, the determining the location of the sensitive information of the sensitive table includes:
generating corresponding mirror image flow data according to each flow data;
identifying each mirror image flow data to obtain database asset information;
establishing an association relationship among the asset information, the target table information and the target field information of each database;
and determining the position of the sensitive information of the sensitive table based on the association relation among the asset information of each database, the target table information and the target field information.
In one possible implementation, the classifying the virtual table in a hierarchical manner includes:
acquiring an association relation among the virtual tables;
determining an association table associated with a first virtual table according to the association relation among the virtual tables, wherein the first virtual table is any virtual table in all virtual tables;
and determining the type of the first virtual table according to the target field information of the first virtual table and the associated table.
In a second aspect, an embodiment of the present invention provides a data processing apparatus for a database, including:
the acquisition module is used for acquiring all flow data and query sentences of the database;
the generation module is used for generating corresponding mirror image flow data according to each flow data;
the component module is used for constructing a virtual table according to each flow data, mirror image flow data and query sentences;
and the grading classification module is used for carrying out grading classification processing on the virtual table.
In a third aspect, an embodiment of the present invention provides a computer readable storage medium, where at least one executable instruction is stored, where the executable instruction causes a processor to perform operations corresponding to a data processing method of a database according to any one of the above aspects.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including: the processor, the memory, the communication interface and the communication bus complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to execute operations corresponding to the data processing method of the database according to any one of the foregoing aspects.
According to the data processing method, the device, the storage medium and the electronic equipment of the database, which are provided by the embodiment of the invention, the data information searched in a certain time is constructed into the virtual table based on the data flow and the query statement, so that the data information which is not searched in a certain time, namely, cold data, is removed, and the cold data is not classified in a grading manner when classified in the virtual table, so that the complexity of the data classification is reduced, and the effect of the data classification is improved.
Drawings
The following drawings of the present invention are included as part of the description of embodiments of the invention. The drawings illustrate embodiments of the invention and their description to explain the principles of the invention.
In the accompanying drawings:
FIG. 1 is a flow chart of a method of data processing of a database according to an alternative embodiment of the invention;
FIG. 2 is a flow chart of step S102 according to an alternative embodiment of the present invention;
FIG. 3 is a flow chart of step S103 according to an alternative embodiment of the present invention;
FIG. 4 is a flow chart for determining whether each virtual table is a sensitive table;
fig. 5 is a flowchart after step S402;
FIG. 6 is a flow chart for determining the location of sensitive information of a sensitive table;
FIG. 7 is a flow chart of step S103 according to another alternative embodiment of the present invention;
fig. 8 is a schematic structural view of a data processing apparatus of a database according to an alternative embodiment of the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced without one or more of these details. In other instances, well-known features have not been described in detail in order to avoid obscuring the invention.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is intended to include the plural unless the context clearly indicates otherwise. Furthermore, it will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Exemplary embodiments according to the present invention will now be described in more detail with reference to the accompanying drawings. These exemplary embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. It should be appreciated that these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of these exemplary embodiments to those skilled in the art.
In a first aspect, as shown in fig. 1, an embodiment of the present invention provides a data processing method of a database, including:
step S101: and acquiring all flow data and all query sentences of the database.
The flow data refers to a data flow formed between the database server and the user terminal after the database server responds to a search request initiated by the user and establishes a session with the user terminal through a network. Wherein the user initiated search request is generated by a user performing identifiable operations on a certain computer system, the network including but not limited to wireless network, internet, etc.
The total flow data of the database refers to all flow data in a specified time, and the specified time may be from the time when the database is built to the current time, or may be a period specified by a user, for example, a year or a month, and the specified time is not strictly limited in this embodiment.
When a user has a query requirement, a query statement may be output through a user interface component provided by a data query system running in the computer device. The type of the query statement of the user data may be a structured query language (Structured Query Language, SQL) statement, or may be any other type of statement, which is not limited in this embodiment, and in practical application, may depend on the language supported by the data query system. Similarly, all query sentences refer to all query sentences in a specified time, and the specified time may be from the time of completion of database creation to the current time, or may be a period specified by a user, such as one year or one month, and the specified time is not strictly limited in this embodiment.
Step S102: and constructing a virtual table according to each flow data and the query statement.
In this embodiment, by analyzing each flow data and query statement, a virtual table can be constructed without accessing the database by acquiring the user name and password of the user, thereby avoiding a complex access process, avoiding the risk of data leakage caused by account leakage, having no invasiveness to the database, and improving the security of the database.
Step S103: and carrying out hierarchical classification processing on the virtual table.
According to the data processing method of the database, which is provided by the embodiment of the invention, the data information searched in a certain time is constructed into the virtual table based on the data flow and the query statement, so that the data information (namely, cold data) which is not searched in a certain time is removed, and the cold data is not classified in a grading manner when the virtual table is classified in a grading manner, so that the complexity of data classification is reduced, and the effect of data classification is improved.
In one possible implementation, as shown in fig. 2, step S102 specifically includes:
step S201: analyzing each query statement to obtain target table information and target field information, wherein the target table information is information of a table searched by the query statement, and the target field information is information of a field searched by the query statement.
The target table information includes, but is not limited to, table names of tables looked up by the query statement, and the target field information includes, but is not limited to, field names of fields looked up by the query statement. Both the table name and the field name may be expressed in a literal form, for example, the table name is "customer information table" and the field name is "name". Of course, the table names and field names may also be represented in other forms, which the present invention is not limited to.
When the query statement is an SQL statement, the regular expression or other third-party SQL statement analysis can be applied, so that target table information and target field information are obtained. Under the condition that other sentences are adopted in the query sentences, corresponding analysis modes can be adopted for analysis to obtain corresponding target information and target field information.
Step S202: based on each flow data, data information transmitted by each flow data is obtained.
Analyzing each flow data to obtain data information transmitted by each flow data, namely result data obtained by user inquiry.
Step S203: and constructing a virtual table according to all the target table information, the target field information and the data information.
Based on all the target table information, the target field information and the data information, a corresponding virtual table can be constructed and formed by utilizing the corresponding relation among each target table information, the target field information and the data information.
Exemplary, the target table information includes a "customer information table" and a "sales performance table", wherein the target field information of the "customer information table" includes a "customer name", "gender", the data information of the "customer name" includes a "Zhang Sang", "Lisi", and the data information of the corresponding "gender" includes a "woman", "man"; the target field information of the sales performance table comprises a sales person name, a sales amount and data information of the sales person name, the data information of the sales person name comprises a small light and a small red, and the data information of the corresponding sales amount comprises a 100-element and a 150-element, so that a virtual table 1 of the client information table and a virtual table 2 corresponding to the sales performance table are constructed.
Virtual table 1 customer information table
| Customer name | Sex (sex) |
| Zhang San | Female |
| Li Si | Man's body |
Virtual table 2 sales performance table
| Customer name | Sales performance |
| Xiaoming (Ming) | 100 yuan |
| Xiao Hong | 150 yuan |
In this embodiment, by analyzing each query statement and flow data, corresponding target table information, target field information and data information are obtained to construct a corresponding virtual table, and access to the database by acquiring the user name and password is not required, so that a complex access process is avoided, the risk of data leakage caused by account leakage is avoided, and the database is not invasive. Meanwhile, the data which is not queried in a specific time, namely cold data, cannot appear in the virtual table, so that the cold data cannot be classified in a grading manner when the virtual table is classified in a grading manner later, the complexity of data grading and classifying is reduced, and the effect of data grading and classifying is improved.
In another possible implementation, as shown in fig. 3, step S103 includes:
step S301: judging whether each virtual table is a sensitive table, if so, executing step S302; if the virtual table is not the sensitive table, step S303 is performed.
Step S302: the type of the sensitive table is determined.
Step S303: the virtual table is determined to be a non-sensitive table.
In this embodiment, first, whether the virtual table is a sensitive table is determined, and if the virtual table is a sensitive table, the table is classified and the sensitive level is determined; if the virtual table is not a sensitive table, the table is directly determined to be a non-sensitive table, and then a hierarchical classification report can be formed and displayed to a user so as to be convenient for the user to check.
In the above embodiment, as shown in fig. 4, determining whether each virtual table is a sensitive table specifically includes:
step S401: judging whether the target field information of each virtual table is sensitive information, and if the target field information of the virtual table is sensitive information, executing step S402; if all the target field information of the virtual table is not sensitive information, step S403 is executed.
Step S402: the virtual table is determined to be a sensitive table.
Step S403: the virtual table is determined to be not a sensitive table.
Specifically, a sensitive dictionary may be pre-stored in the processing system, the sensitive dictionary may store all the sensitive words, each target field information of each virtual table may be matched with the sensitive words in the sensitive dictionary one by one, if one or several target field information of the virtual table is successfully matched with the sensitive words, the virtual table is determined to be a sensitive table, and if all the target field information of the virtual table is not matched with all the sensitive words of the sensitive dictionary, the virtual table is determined to be not a sensitive table. The sensitive words in the sensitive dictionary can be added or subtracted by a user according to actual requirements.
For example, assuming that the sensitive words of the sensitive dictionary are "user name" and "user phone", the target field information "user name" in the virtual table 1 in the above example is successfully matched with the sensitive word "user name", the virtual table 1 is determined to be a sensitive table, the target field information in the virtual table 2 is not matched with the "user name" and "user phone", and the virtual table 2 is determined to be not a sensitive table.
Further, the sensitivity level of the sensitivity table can be determined according to the quantity of the sensitive information, that is, the higher the quantity of the sensitive information contained in the sensitivity table, the higher the sensitivity level. Each sensitivity level corresponds to a threshold of the amount of sensitive information of a certain amount, and if the sensitive information included in the sensitive table reaches the threshold of the amount of sensitive information of one of the sensitivity levels, the sensitivity level of the sensitive table can be determined. For example, assuming that the threshold of the number of sensitive information corresponding to the first sensitive level is 3 and the threshold of the number of sensitive information corresponding to the second sensitive level is 6, if the sensitive table 1 contains 4 sensitive information in total, the sensitive table 1 is the first sensitive level.
In yet another possible implementation manner, as shown in fig. 5, step S402 further includes:
step S501: the location of the sensitive information of the sensitive table and the type of the sensitive information are determined.
The sensitive dictionary also stores the sensitive word type corresponding to each sensitive word, and when the field information of the virtual table is successfully matched with the sensitive word, the type of the sensitive word is determined as the type of the sensitive information. For example, assuming that the type corresponding to the sensitive word "user cell phone" is "user contact", and the sensitive information in the virtual table includes "user cell phone", the type of the field information "user cell phone" is determined as "user contact".
Step S502: based on the position of the sensitive information and the type of the sensitive information, searching the sensitive information and marking the label corresponding to the type.
The labels may be words of the same type as the labels, or may be corresponding specific symbols, which are not strictly limited in this application. The label of the type "user contact" may be "user contact" or "a" by way of example.
Specifically, as shown in fig. 6, determining the location of the sensitive information of the sensitive table includes:
step S601: and generating corresponding mirror image flow data according to each flow data.
The mirror image flow data refers to flow data flowing through a certain device, which is used for copying or intercepting part of information according to the requirement based on preset conditions, and transmitting the flow data to other appointed receiving devices for flow processing. For example, the mirrored traffic data may be obtained by copying or intercepting the traffic data from the dimensions of the port, VLAN, etc.
Step S602: and identifying each mirror image flow data to obtain database asset information.
The database asset information mainly comprises, but is not limited to, database asset IP, port, database type and the like, so that the database asset information can be combed out by analyzing mirror image flow information without pre-combing the database asset information.
Step S603: and establishing an association relationship among the asset information, the target table information and the target field information of each database.
And establishing an association relationship between each database asset information and the corresponding target table information and target field information in the database.
Step S604: and determining the position of the sensitive information of the sensitive table based on the association relation among the asset information of each database, the target table information and the target field information.
Based on the association relation among each database asset information, the target table information and the target field information, the target table information, the sensitive information and the corresponding database asset information of the sensitive table can be searched, so that the database where the sensitive table is located can be searched according to the database asset information, then the sensitive table is found according to the target table information of the sensitive table, and then the sensitive information is searched in the sensitive table according to the corresponding relation between the target table information and the sensitive information of the sensitive table, thereby determining the position of the sensitive information.
In the above embodiment, as shown in fig. 7, the step of step S103 further includes:
step S701: and obtaining the association relation among the virtual tables.
The association relation between the virtual tables can be obtained through a preset algorithm, and the preset algorithm can adopt a join algorithm to associate two or more virtual tables through the target field information relation between the virtual tables.
For example, the virtual table a, the virtual table B, and the virtual table C are shown below, and the virtual table a and the virtual table B may have an association relationship by "number", and the virtual table B and the virtual table C may have an association relationship by "address number".
Virtual table A product table
| Numbering device | Product name | Price of |
| 12 | Notebook computer | 18999.00 |
| 13 | Mobile phone | 1899.00 |
Virtual table B service subscription information table
| Numbering device | Order time | Address numbering |
| 12 | 2020/12/11 15:32 | 1000 |
| 13 | 2020/12/11 15:32 | 1000 |
Virtual table C address table
| Address numbering | Address of | Name of name |
| 1000 | xx-city xx region | King x |
| 1000 | xx-city xx region | Plum x |
The step determines the association relation among the virtual tables through the target field information, and compared with the existing method for determining the association relation through the main external key of the tables, the obtained association relation is more accurate. Of course, in other embodiments, the association between the virtual tables may be implemented by other algorithms to obtain the association relationship, which is not limited in this application.
Step S702: and determining an association table associated with a first virtual table according to the association relation among the virtual tables, wherein the first virtual table is any one of all the virtual tables.
The association table of the first virtual table comprises a virtual table with a direct association relationship with the first virtual table and a virtual table with an indirect association relationship with the first virtual package.
For example, continuing with the example in step S701, assuming that the virtual table a is the first virtual table, the virtual table B is a virtual table having a direct association relationship with the virtual table a, and the virtual table C is a virtual table having an indirect association relationship with the virtual table a, so that the association tables of the virtual table a are the virtual table B and the virtual table C.
Step S703: and determining the type of the first virtual table according to the target field information of the first virtual table and the associated table.
The step determines the type of the first virtual table by combining the target field information of the first virtual table with the target field information of the associated table, and classification is more accurate than determining the type of the first virtual table by only the target field information in the first virtual table.
Illustratively, continuing with the example in step S702, the first virtual table (virtual table a) includes the target field information "product name", "price", the virtual table B includes the target field information "order time", "address number", and the virtual table C includes the target field information "address", "name". In the prior art, whether the first virtual table is a product table or a service order information table cannot be accurately determined only by the product name and the price of the first virtual table. In this step, the first virtual table is determined to be the product table by combining the "order time" and "address number" of the associated table virtual table B of the first virtual table, thereby obtaining an accurate type.
In a second aspect, an embodiment of the present invention provides a data processing apparatus for a database, as shown in fig. 8, where the apparatus includes:
an obtaining module 801, configured to obtain all flow data and query statements of a database;
a building module 802, configured to build a virtual table according to each flow data and the query statement;
the classification module 803 is configured to perform classification processing on the virtual table.
According to the data processing device of the database, which is provided by the embodiment of the invention, the data information searched in a certain time is constructed into the virtual table based on the data flow and the query statement, so that the data information which is not searched in a certain time, namely the cold data, is removed, and the cold data is not classified in a grading manner when classified in the virtual table, so that the complexity of data classification is reduced, and the effect of data classification is improved. Meanwhile, classification and grading are carried out in a mode of constructing a virtual table, the original database is not required to be processed, the invasiveness to the original database is avoided, and therefore the safety of the database is improved.
In a third aspect, an embodiment of the present invention provides a computer readable storage medium, where at least one executable instruction is stored, where the executable instruction causes a processor to perform operations corresponding to a data processing method of a database according to any one of the above aspects.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including: the processor, the memory, the communication interface and the communication bus, and the processor, the memory and the communication interface complete the communication with each other through the communication bus; the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the data processing of the database according to any scheme.
In particular, the program may include program code including computer-operating instructions.
The processor may be a central processing unit, CPU, or specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured as embodiments of the present invention. The one or more processors included in the computer device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
And the memory is used for storing programs. The memory may comprise high-speed RAM memory or may further comprise non-volatile memory, such as at least one disk memory.
The present invention has been illustrated by the above-described embodiments, but it should be understood that the above-described embodiments are for purposes of illustration and description only and are not intended to limit the invention to the embodiments described. In addition, it will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that many variations and modifications are possible in light of the teachings of the invention, which variations and modifications are within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. A method of processing data in a database, comprising:
acquiring all flow data and all query sentences of a database, wherein the flow data refers to data streams formed between a database server and a user terminal after the database server responds to a search request initiated by a user and establishes a session with the user terminal through a network;
constructing a virtual table according to each flow data and query statement;
performing hierarchical classification processing on the virtual table;
the constructing a virtual table according to each flow data and query statement includes:
analyzing each query statement to obtain target table information and target field information, wherein the target table information is information of a table searched by the query statement, and the target field information is information of a field searched by the query statement;
based on each flow data, obtaining data information transmitted by each flow data;
and constructing a virtual table according to all the target table information, the target field information and the data information.
2. The method of claim 1, wherein said hierarchically classifying said virtual table comprises:
judging whether each virtual table is a sensitive table, and if the virtual table is the sensitive table, determining the type of the sensitive table; and if the virtual table is not a sensitive table, determining that the virtual table is a non-sensitive table.
3. The method of claim 2, wherein said determining whether each of said virtual tables is a sensitive table comprises:
judging whether the target field information of each virtual table is sensitive information, and if the target field information of the virtual table is sensitive information, determining that the virtual table is a sensitive table; and if all the target field information of the virtual table is not sensitive information, determining that the virtual table is not a sensitive table.
4. The method of claim 3, wherein the determining that the virtual table is a sensitive table further comprises:
determining the position of sensitive information of the sensitive table and the type of the sensitive information;
based on the position of the sensitive information and the type of the sensitive information, searching the sensitive information and marking a label corresponding to the type.
5. The method of claim 4, wherein determining the location of the sensitive information of the sensitive table comprises:
generating corresponding mirror image flow data according to each flow data;
identifying each mirror image flow data to obtain database asset information;
establishing an association relationship among the asset information, the target table information and the target field information of each database;
and determining the position of the sensitive information of the sensitive table based on the association relation among the asset information of each database, the target table information and the target field information.
6. The method of claim 1, wherein said hierarchically classifying said virtual table comprises:
acquiring an association relation among the virtual tables;
determining an association table associated with a first virtual table according to the association relation among the virtual tables, wherein the first virtual table is any virtual table in all virtual tables;
and determining the type of the first virtual table according to the target field information of the first virtual table and the associated table.
7. A data processing apparatus of a database, comprising:
the system comprises an acquisition module, a query module and a query module, wherein the acquisition module is used for acquiring all flow data and query sentences of a database, wherein the flow data is data flow formed between a database server and a user terminal after the database server responds to a search request initiated by a user and establishes a session with the user terminal through a network;
the construction module is used for constructing a virtual table according to each flow data and the query statement;
the classification module is used for performing classification treatment on the virtual table;
the construction module is specifically configured to parse each query statement to obtain target table information and target field information, where the target table information is information of a table searched by the query statement, and the target field information is information of a field searched by the query statement;
based on each flow data, obtaining data information transmitted by each flow data;
and constructing a virtual table according to all the target table information, the target field information and the data information.
8. A storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the data processing method of a database according to any one of claims 1-6.
9. An electronic device, comprising: the processor, the memory, the communication interface and the communication bus complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the data processing method of the database according to any one of claims 1 to 6.
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| CN116610714B (en) * | 2023-07-14 | 2023-10-31 | 北京数巅科技有限公司 | Data query method, device, computer equipment and storage medium |
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