Data processing method, data processing equipment and computer readable storage medium

Abstract

The invention relates to the technical field of data management, in particular to a data processing method, data processing equipment and a computer readable storage medium. The method comprises the following steps: receiving query information for querying unstructured data; determining a query condition based on target information in the query information; wherein the target information comprises one or more items in business meta-information and file meta-information of the query file, the business meta-information corresponds to any item in business directory trees, one business directory tree corresponds to one storage directory tree, and parent storage directories in the storage directory trees are in one-to-one correspondence with parent business directories of the business directory trees; the sub-storage directories of the parent storage directories are in one-to-one correspondence with the sub-service directories of the parent service directories; and determining a storage path of the unstructured data in the storage directory tree based on the query condition.

Description

Technical Field

[0001] This disclosure relates to the field of data governance technology, and in particular to a data processing method, a data processing device, and a computer-readable storage medium. Background Technology

[0002] In the field of data governance, with the rise of artificial intelligence technology, enterprises have accumulated massive amounts of unstructured data, including Word, Excel, PDF, HTML documents, as well as images, videos, audio, and other formats. Due to their complex structure and diverse formats, this data usually cannot be directly stored in traditional relational or structured databases, but can only be scattered in various file systems or object storage as raw files.

[0003] Currently, the metadata managed by file systems is mainly limited to technical information related to the physical attributes of files, such as filename, format, size, creation time, and modification time. However, this information is severely disconnected from the business context. For example, metadata crucial for business retrieval—such as the file's business category, product line, department affiliation, business security level, confidentiality level, and whether the file is encrypted—is generally missing. Enterprises can only rely on file content or purely technical tags for retrieval, resulting in low search hit rates, insufficient precision, and an inability to achieve fine-grained access control and security management.

[0004] Therefore, a prominent problem with existing technologies is the low efficiency of file retrieval. Users cannot quickly locate the files they need through dimensions that are directly and semantically relevant to their business, often requiring a significant amount of time for manual screening or content parsing. This not only reduces the utilization rate of data assets but also hinders the in-depth development of intelligent data applications. Summary of the Invention

[0005] To address the aforementioned technical problems, this disclosure provides a data processing method, a data processing apparatus, and a computer-readable storage medium.

[0006] In a first aspect, this disclosure provides a data processing device, comprising: a communicator configured to: receive query information for querying unstructured data; and a controller configured to: determine query conditions based on target information in the query information; wherein the target information includes one or more of business metadata and file metadata of the query file, the business metadata corresponds to any item in a business directory tree, one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory; and the storage path of the unstructured data in the storage directory tree is determined based on the query conditions.

[0007] Secondly, this disclosure provides a data processing method, comprising: receiving query information for querying unstructured data; determining query conditions based on target information in the query information; wherein the target information includes one or more of business metadata and file metadata of the query file, the business metadata corresponds to any item in a business directory tree, one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory; and determining the storage path of the unstructured data in the storage directory tree based on the query conditions.

[0008] Thirdly, this disclosure provides a computer-readable storage medium, comprising: storing a computer program on the computer-readable storage medium, the computer program being executed by a controller using a data processing method as provided in any of the second aspects.

[0009] Fourthly, this disclosure provides a computer program product that, when run on a computer, causes the computer to perform any of the data processing methods provided in the second aspect.

[0010] It should be noted that the aforementioned computer instructions may be stored, in whole or in part, on the first computer-readable storage medium. The first computer-readable storage medium may be encapsulated together with the controller of the data processing device, or it may be encapsulated separately from the controller of the data processing device; this disclosure does not impose any limitations on this.

[0011] The descriptions of the second, third, and fourth aspects in this disclosure can be referenced to the detailed description of the first aspect; and the beneficial effects of the descriptions of the second, third, and fourth aspects can be referenced to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0012] In this disclosure, the names of the aforementioned data processing devices do not limit the devices or functional modules themselves. In actual implementation, these devices or functional modules may appear under other names. As long as the functions of each device or functional module are similar to those of this disclosure, they fall within the scope of this disclosure and its equivalents.

[0013] These or other aspects of this disclosure will become more readily apparent in the following description.

[0014] The technical solution provided in this disclosure has the following advantages compared with the prior art: The data processing device disclosed herein pre-separates the business directory tree and the storage directory tree, for example, by mapping the business directory tree to the storage directory tree, so that one business directory tree corresponds to one storage directory tree. In the storage directory tree, the parent storage directory corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory. Then, the communicator is configured to receive query information for retrieving unstructured data; the controller is configured to determine query conditions based on the target information in the query information; and based on the query conditions, determine the storage path of the unstructured data in the storage directory tree. In this way, users can find the corresponding unstructured data file based on the storage path, thus eliminating the need for users to search through corresponding file directories one by one, improving file retrieval efficiency and solving the problem of low file retrieval efficiency in the prior art. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 One of the flowcharts illustrating the data processing method provided in the embodiments of this application; Figure 2 A schematic diagram illustrating a scenario in which the data processing method provided in the embodiments of this application is applied; Figure 3 A schematic diagram of the business directory tree in the data processing method provided in the embodiments of this application; Figure 4 A schematic diagram illustrating the mapping between the business directory tree and the storage directory tree in the data processing method provided in this application embodiment; Figure 5 A second schematic flowchart illustrating the data processing method provided in this application embodiment; Figure 6 The third schematic flowchart of the data processing method provided in the embodiments of this application; Figure 7 The fourth flowchart illustrating the data processing method provided in this application embodiment; Figure 8 Fifth flowchart illustrating the data processing method provided in the embodiments of this application; Figure 9This is a schematic diagram of the structure of the data processing device provided in the embodiments of this application; Figure 10 This is a schematic diagram of a chip system provided in an embodiment of this application. Detailed Implementation

[0018] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0019] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0020] The display device provided in this application can have various implementation forms, such as a television, a smart television, a laser projection device, a monitor, an electronic bulletin board, an electronic table, etc. Figure 1 and Figure 2 This is one specific embodiment of the display device of this application.

[0021] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0022] In some examples, Elasticsearch in this disclosure is a distributed, highly scalable, and real-time search and data analytics engine capable of rapidly processing massive amounts of data and supporting full-text search, structured queries, and real-time analysis.

[0023] In some examples, MySQL in this disclosure is an open-source relational database management system that uses SQL (Structured Query Language) for data management. It is known for its high performance, stability, and ease of use and is widely used in various application systems.

[0024] The data processing device provided in this disclosure can be a server. When the server executes the data processing method provided in this disclosure, the server's processor may execute the data processing method provided in this disclosure.

[0025] In the following embodiments, the execution subject of the data processing method provided in the embodiments of this disclosure is the aforementioned server, which will be used as an example to illustrate the method of the embodiments of this application.

[0026] This application provides a data processing method, such as... Figure 1 As shown, the data processing method may include S11-S15.

[0027] S11. Receive query information for querying unstructured data.

[0028] In some examples, the architecture applied in embodiments of this disclosure is as follows: Figure 2 As shown, it includes the business end 1 for applying storage business target tree, the storage end 2 for storing files for unstructured data, and the storage end 3 for storing storage paths.

[0029] In some examples, the business directory tree is often multi-level, such as 8 or even 11 levels, and the relationship between the levels often changes continuously with the business model. The data processing method provided in this disclosure separates the business directory tree from the storage directory tree and then maps them to obtain a storage directory tree with the same hierarchical structure as the business directory tree.

[0030] For example, the business directory tree is as follows: Figure 3 As shown.

[0031] Subsequently, following a four-level database-like structure: metalake / catalog / schema / fileset, metalake is like a database cluster instance, catalog is like a database, schema is like a database, fileset is like a database table, and each directory under a fileset is like the data in a database table. During mapping, a last-level storage directory mapping pattern is used. The last-level directory of the business directory is the location where the actual files are stored, which corresponds to the fileset pattern. The files within this directory represent the actual storage directory location of the corresponding fileset. The information about the multiple levels of parent directories to which the last-level directory belongs is maintained by the business side, facilitating direct retrieval and directory movement based on the business directory.

[0032] For example, the mapping relationship is as follows Figure 4 As shown.

[0033] Once the storage directory mapping is complete, the storage address on the actual server can be calculated after a file is uploaded to the business directory. For example, it can be mapped to the 4th level directory of the storage directory based on the unique identifier (such as ID) of the last-level directory (such as a subdirectory) of the business directory. In this way, no matter how the parent directory of the business directory changes, the storage directory can always be located at the 4th level.

[0034] This completes the creation of the storage directory tree.

[0035] In some examples, when creating a storage directory tree, the corresponding business directory tree (such as an image of the business directory tree) can be input into a mapping model for mapping to obtain the storage directory tree; the training process of the mapping model includes: Obtain first training sample data and first labeling results for the first training sample data. The first training sample data includes at least one historical business directory tree, and the first labeling results include the historical storage directory tree corresponding to each historical business directory tree.

[0036] The first training sample data is input into the first neural network model for learning, and the first prediction result of the first neural network model on the first training sample data is obtained.

[0037] Based on the first prediction result and the first labeling result, the network parameters of the first neural network model are adjusted until the first neural network model converges to obtain the mapping model.

[0038] S12. Determine the query conditions based on the target information in the query information; wherein, the target information includes one or more of the business metadata and the file metadata of the query file, the business metadata corresponds to any item in the business directory tree, one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory.

[0039] In some examples, when the target information includes business metadata, the sub-business directory corresponding to the business metadata in the business directory tree can be determined based on the business metadata in the query information; query conditions can be generated based on the business identifier corresponding to the sub-business directory corresponding to the business metadata in the business directory tree. Alternatively, when the target information includes file metadata, which includes one or more of the following: file directory, file name, file format, file size, file author, file summary, and file type, query conditions can be generated based on the file metadata in the query information. Or, when the target information includes both business metadata and file metadata, the sub-business directory corresponding to the business metadata in the business directory tree can be determined based on the business metadata in the query information; query conditions can be generated based on the business identifier and file metadata corresponding to the sub-business directory corresponding to the business metadata in the business directory tree.

[0040] In some examples, the target information from the query can be input into the query model for calculation to determine the query conditions; the training process of the query model includes: Obtain the second training sample data and the second labeling result of the second training sample data; wherein, the second training sample data includes the target information in the historical query information, and the second labeling result includes the query conditions corresponding to the target information in each historical query information.

[0041] The second training sample data is input into the second neural network model for learning, and the second prediction result of the second neural network model on the second training sample data is obtained.

[0042] Based on the second prediction result and the second labeling result, the network parameters of the second neural network model are adjusted until the second neural network model converges to obtain the query model.

[0043] S13. Based on the query conditions, determine the storage path of unstructured data in the storage directory tree.

[0044] In some examples, after obtaining the storage path, a prompt message containing that storage path can be generated. This prompt message allows users to determine the storage path of the file they need to access and then find the file according to that path, thus improving the user's search experience.

[0045] In some examples, this storage path, along with business-related metadata and the file's own metadata, is structured and stored in tables within a structured database, such as Elasticsearch or MySQL, for easy retrieval. This allows the system to filter storage paths matching the query criteria within the structured database tables, thereby determining the storage path of unstructured data within the storage directory tree.

[0046] In some examples, the fields of a structured database table include a file path field (used to store the storage path), a file metadata field (used to store the file's own metadata), and a business metadata field (used to store business-related metadata).

[0047] For example, the file path field is shown in Table 1.

[0048] Table 1

[0049] The file path is the file storage path determined based on directory mapping.

[0050] The file metadata fields are shown in Table 2.

[0051] Table 2

[0052] The file metadata needs to be extracted from the file itself.

[0053] The business metadata fields are shown in Table 3.

[0054] Table 3

[0055] Among them, business metadata needs to be implemented through business tags.

[0056] For example, when a business needs to retrieve data based on business fields (such as business metadata) and the file's own field attributes (such as file metadata), the retrieval path and process are as follows: For example, to query the user manuals of all TVs under product line A, first query the ID of the business directory corresponding to product A. After finding the ID, use the business directory information, PDF, TV, user manual, and other business information to generate query conditions, and then query the storage path of the file metadata according to the query conditions. Finally, find the complete file storage location according to the storage path.

[0057] As described above, the data processing method provided in this embodiment of the present disclosure separates the business directory tree and the storage directory tree in advance, for example, by mapping the business directory tree to the storage directory tree, so that one business directory tree corresponds to one storage directory tree, and the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory. Then, the communicator is configured to receive query information for querying unstructured data; the controller is configured to determine query conditions based on the target information in the query information; and determine the storage path of the unstructured data in the storage directory tree based on the query conditions. In this way, the user can find the corresponding unstructured data file based on the storage path, thus eliminating the need for the user to search through the corresponding file directories one by one, improving file retrieval efficiency.

[0058] In some feasible examples, combining Figure 1 ,like Figure 5 As shown, the data processing method provided in this embodiment of the disclosure further includes S14 and S15.

[0059] S14. Obtain the business directory tree; wherein, the business directory tree includes at least one business directory; S15. Generate a storage directory tree that maps to the business directory tree according to the mapping method of the last-level storage directory.

[0060] As described above, the data processing method provided in this embodiment of the present disclosure separates the business directory tree and the storage directory tree in advance. For example, it obtains the business directory tree and generates a storage directory tree mapped to the business directory tree according to the mapping method of the last-level storage directory. Then, the communicator is configured to receive query information for querying unstructured data; the controller is configured to determine query conditions based on the target information in the query information; and determine the storage path of the unstructured data in the storage directory tree based on the query conditions. In this way, users can find the corresponding unstructured data file based on the storage path, thus eliminating the need for users to search through the corresponding file directories one by one, improving file retrieval efficiency.

[0061] In some feasible examples, the target information includes business metadata; combined with Figure 1 ,like Figure 6 As shown, the above S12 can be implemented by the following S120 and S121.

[0062] S120. Based on the business element information in the query information, determine the sub-business directory corresponding to the business element information in the business directory tree; S121. Generate query conditions based on the business identifier corresponding to the sub-business directory in the business directory tree based on the business metadata.

[0063] In some examples, since the storage directory tree and the business directory tree have the same hierarchical relationship, the storage identifier in the storage directory tree that is identical to the business identifier of the corresponding sub-business directory in the business directory tree can be determined. Furthermore, the storage path can be determined based on this storage identifier, such as the storage path at the level corresponding to that storage identifier. Then, when a user queries based on this storage path, they can see the various unstructured data files under that storage path.

[0064] As described above, the data processing method provided in this embodiment of the present disclosure separates the business directory tree and the storage directory tree in advance, for example, by mapping the business directory tree to the storage directory tree, so that one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory. Then, the communicator is configured to receive query information for querying unstructured data; the controller is configured to: determine the sub-business directory corresponding to the business element information in the business directory tree based on the business element information in the query information; generate query conditions based on the business identifier corresponding to the sub-business directory corresponding to the business element information in the business directory tree; and determine the storage path of the unstructured data in the storage directory tree based on the query conditions. In this way, users can find the corresponding unstructured data file based on the storage path, thus eliminating the need for users to search through the corresponding file directories one by one, improving file retrieval efficiency.

[0065] In some feasible examples, the target information includes file metadata, which includes one or more of the following: file directory, file name, file format, file size, file author, file summary, and file type; combined with Figure 1 ,like Figure 7 As shown, the above S12 can be implemented in the following S122.

[0066] S122. Generate query conditions based on the file metadata in the query information.

[0067] In some examples, when determining the storage path of unstructured data in the storage directory tree based on query conditions, the actual metadata that matches the file metadata, as well as the corresponding unstructured data file, can be determined based on the file metadata. Then, the storage path of the unstructured data in the storage directory tree is determined as the storage path of the unstructured data file corresponding to each actual metadata. As described above, the data processing method provided in this embodiment of the present disclosure separates the business directory tree and the storage directory tree in advance, for example, by mapping the business directory tree to the storage directory tree, so that one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory. Then, the communicator is configured to receive query information for querying unstructured data; the controller is configured to generate query conditions based on the file metadata in the query information; and determine the storage path of the unstructured data in the storage directory tree based on the query conditions. In this way, users can find the corresponding unstructured data file based on the storage path, thus eliminating the need for users to search through the corresponding file directories one by one, improving file retrieval efficiency.

[0068] In some feasible examples, the target information includes business metadata and file metadata; combined with Figure 1 ,like Figure 8 As shown, the above S12 can be specifically implemented through the following S120 and S123.

[0069] S120. Based on the business element information in the query information, determine the sub-business directory corresponding to the business element information in the business directory tree; S123. Generate query conditions based on the business identifier and file metadata corresponding to the sub-business directory in the business directory tree.

[0070] In some examples, when determining the storage path of unstructured data in the storage directory tree based on query conditions, since the storage directory tree and the business directory tree have the same hierarchical relationship, the storage identifier in the storage directory tree that matches the business identifier of the corresponding sub-business directory in the business directory tree can be determined. Then, based on file metadata, the actual metadata of each unstructured data file stored at the level corresponding to that storage identifier is matched, thereby determining each piece of actual metadata that matches that file metadata, and the unstructured data file corresponding to each piece of actual metadata. Finally, the storage path of the unstructured data in the storage directory tree is determined as the storage path of the unstructured data file corresponding to each piece of actual metadata.

[0071] As described above, the data processing method provided in this embodiment of the present disclosure separates the business directory tree and the storage directory tree in advance, for example, by mapping the business directory tree to the storage directory tree, so that one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directories of each parent storage directory correspond one-to-one with the child business directories of each parent business directory. Then, the communicator is configured to receive query information for querying unstructured data; the controller is configured to: determine the sub-business directory corresponding to the business metadata in the business directory tree based on the business metadata in the query information; generate query conditions based on the business identifier and file metadata corresponding to the sub-business directory corresponding to the business metadata in the business directory tree; and determine the storage path of the unstructured data in the storage directory tree based on the query conditions. In this way, users can find the corresponding unstructured data file based on the storage path, thus eliminating the need for users to search through the corresponding file directories one by one, improving file retrieval efficiency.

[0072] In some feasible examples, the business directory tree is used to store business information, the storage directory tree is used to store storage files containing unstructured data, and the file metadata of the storage files.

[0073] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0074] This application embodiment can divide the data processing device into functional modules according to the above method example. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing unit. The integrated modules can be implemented in hardware or as software functional modules. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0075] like Figure 9 As shown in the diagram, an embodiment of this application provides a schematic diagram of a data processing device. It includes a communicator 101 and a controller 102.

[0076] Communicator 101 is configured to receive query information for querying unstructured data; Controller 102 is configured as follows: Based on the target information in the query information, the query conditions are determined; wherein, the target information includes one or more of the business meta information and the file meta information of the query file, the business meta information corresponds to any item in the business directory tree, one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directory of each parent storage directory corresponds one-to-one with the child business directory of each parent business directory. Based on the query conditions, determine the storage path of unstructured data in the storage directory tree.

[0077] In some implementable examples, controller 102 is further configured to: determine query conditions based on the target information in the query information before executing the query: Obtain the business directory tree; wherein the business directory tree includes at least one business directory; Generate a storage directory tree that maps to the business directory tree according to the mapping method of the last-level storage directory.

[0078] In some feasible examples, the target information includes business metadata; When the controller 102 determines the query conditions based on the target information in the query information, it is further configured to: Based on the business metadata in the query information, determine the sub-business directory corresponding to the business metadata in the business directory tree; Based on the business identifier corresponding to the sub-business directory in the business directory tree, query conditions are generated.

[0079] In some feasible examples, the target information includes file metadata, which includes one or more of the following: file directory, file name, file format, file size, file author, file summary, and file type. When the controller 102 determines the query conditions based on the target information in the query information, it is further configured to: Query conditions are generated based on the file metadata in the query information.

[0080] In some feasible examples, the target information includes business metadata and file metadata; When the controller 102 determines the query conditions based on the target information in the query information, it is further configured to: Based on the business metadata in the query information, determine the sub-business directory corresponding to the business metadata in the business directory tree; Based on the business identifier and file metadata corresponding to the sub-business directory in the business directory tree, query conditions are generated.

[0081] In some feasible examples, the business directory tree is used to store business information, the storage directory tree is used to store storage files containing unstructured data, and the file metadata of the storage files.

[0082] All relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and their functions will not be repeated here.

[0083] Of course, the data processing device provided in this application embodiment includes, but is not limited to, the modules described above. For example, the data processing device may also include a memory 103. The memory 103 may be used to store the program code of the data processing device, and may also be used to store data generated by the data processing device during operation, such as data in write requests.

[0084] like Figure 10 As shown, this application embodiment also provides a chip system that can be applied to the data processing device in the foregoing embodiments. The chip system includes at least one processor 1501 and at least one interface circuit 1502. The processor 1501 may be the processor in the aforementioned data processing device. The processor 1501 and the interface circuit 1502 are interconnected via a line. The processor 1501 can receive and execute computer instructions from the memory of the aforementioned data processing device through the interface circuit 1502. When the computer instructions are executed by the processor 1501, the data processing device can perform the various steps executed by the data processing device in the foregoing embodiments. Of course, the chip system may also include other discrete devices, and this application embodiment does not specifically limit this.

[0085] This application also provides a computer-readable storage medium for storing computer instructions for operating the aforementioned data processing device.

[0086] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data processing device, characterized in that, include: The communicator is configured to receive query information for querying unstructured data; The controller is configured as follows: Based on the target information in the query information, query conditions are determined; wherein, the target information includes one or more of the business metadata and the file metadata of the query file, the business metadata corresponds to any item in the business directory tree, one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directory of each parent storage directory corresponds one-to-one with the child business directory of each parent business directory; Based on the query conditions, the storage path of the unstructured data in the storage directory tree is determined.

2. The data processing device according to claim 1, characterized in that, Before executing the query based on the target information in the query information to determine the query conditions, the controller is also configured to: Obtain the business directory tree; wherein the business directory tree includes at least one business directory; Generate a storage directory tree that maps to the business directory tree according to the mapping method of the last-level storage directory.

3. The data processing device according to claim 1, characterized in that, The target information includes the business metadata; When the controller determines the query conditions based on the target information in the query information, it is further configured to: Based on the business element information in the query information, determine the sub-business directory corresponding to the business element information in the business directory tree; Based on the business identifier corresponding to the sub-business directory in the business directory tree, the business metadata is used to generate query conditions.

4. The data processing device according to claim 1, characterized in that, The target information includes the file metadata, which includes one or more of the following: file directory, file name, file format, file size, file author, file summary, and file type. When the controller determines the query conditions based on the target information in the query information, it is further configured to: Based on the file metadata in the query information, query conditions are generated.

5. The data processing device according to claim 1, characterized in that, The target information includes the business metadata and the file metadata; When the controller determines the query conditions based on the target information in the query information, it is further configured to: Based on the business element information in the query information, determine the sub-business directory corresponding to the business element information in the business directory tree; Based on the business identifier corresponding to the sub-business directory in the business directory tree and the file metadata, query conditions are generated.

6. The data processing apparatus according to any one of claims 1-5, characterized in that, The business directory tree is used to store business information, and the storage directory tree is used to store storage files containing unstructured data, as well as the file metadata of the storage files.

7. A data processing method, characterized in that, include: Receive query information for querying unstructured data; Based on the target information in the query information, query conditions are determined; wherein, the target information includes one or more of the business metadata and the file metadata of the query file, the business metadata corresponds to any item in the business directory tree, one business directory tree corresponds to one storage directory tree, the parent storage directory in the storage directory tree corresponds one-to-one with the parent business directory of the business directory tree, and the child storage directory of each parent storage directory corresponds one-to-one with the child business directory of each parent business directory; Based on the query conditions, the storage path of the unstructured data in the storage directory tree is determined.

8. The data processing method according to claim 7, characterized in that, The step of determining the query conditions based on the target information in the query information includes: Obtain the business directory tree; wherein the business directory tree includes at least one business directory; Generate a storage directory tree that maps to the business directory tree according to the mapping method of the last-level storage directory.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the data processing method as described in claim 7 or 8.

10. A computer program product, characterized in that, When the computer program product is run on a computer, it causes the computer to implement the data processing method as described in claim 7 or 8.

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