Data management method and device, electronic device and computer readable storage medium

Abstract

The embodiment of the present invention provides a data management method and device, an electronic device, and a computer-readable storage medium. The method includes: generating an attribute metadata table according to attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information; obtaining first-category attribute data corresponding to the first-category attribute information of target object data, and second-category attribute data corresponding to the second-category attribute information; and writing the first-category attribute data and the second-category attribute data of the target object data into the attribute metadata table. The embodiment of the present invention creates an attribute metadata table by setting attribute field information, extracts two-level attribute data from object data, and writes the two-level attribute data into the attribute metadata table, thereby realizing unified management of unstructured data.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing technology, and in particular to a data management method and device, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the development of cloud technology, a cloud service network architecture has emerged in which storage and computing are completely separated, which can take advantage of high-speed and high-throughput network channels to fully utilize the advantages of hardware concentration. In such cloud services, how to efficiently and conveniently store and use large amounts of data in cloud databases becomes very important.

[0003] Currently, in cloud storage systems, there are two types of data: structured data and unstructured data. Among them, structured data has a regular data structure, so it is very convenient in data construction and analysis.

[0004] However, for unstructured data, since it does not have a unified and standardized data structure, it can only be stored as a whole, and different features must be extracted according to different data formats (for example, videos, images, text, etc.). The extracted features have great differences in data construction and analysis. Therefore, it can only be processed one by one, which is not conducive to batch construction and analysis of large amounts of data. Summary of the invention

[0005] Embodiments of the present invention provide a data management method and device, an electronic device, and a computer-readable storage medium to solve the defect in the prior art that unstructured data is difficult to manage uniformly.

[0006] To achieve the above object, an embodiment of the present invention provides a data management method, including:

[0007] Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information;

[0008] Acquire first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data;

[0009] The first type of attribute data and the second type of attribute data of the target object data are written into the attribute metadata table.

[0010] The embodiment of the present invention further provides a data management device, including:

[0011] A generating module, used to generate an attribute metadata table according to attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information;

[0012] A first acquisition module, used to acquire first-category attribute data corresponding to the first-category attribute information of the target object data, and second-category attribute data corresponding to the second-category attribute information;

[0013] The writing module is used to write the first type of attribute data and the second type of attribute data of the target object data into the attribute metadata table.

[0014] The embodiment of the present invention also provides a data management method, including:

[0015] Sending a data acquisition request, the data acquisition request at least including attribute field information and location information of the data to be acquired, wherein the attribute field information includes first-category attribute information and second-category attribute information; and

[0016] Receive data corresponding to the attribute field information included in the data acquisition request.

[0017] An embodiment of the present invention further provides an electronic device, including:

[0018] Memory, used to store programs;

[0019] A processor, configured to run the program stored in the memory, to:

[0020] Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information;

[0021] Acquire first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data;

[0022] The first type of attribute data and the second type of attribute data of the target object data are written into the attribute metadata table.

[0023] An embodiment of the present invention further provides a computer-readable storage medium, on which instructions are stored, the instructions comprising:

[0024] Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information;

[0025] Acquire first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data;

[0026] The first type of attribute data and the second type of attribute data of the target object data are written into the attribute metadata table.

[0027] An embodiment of the present invention further provides a computer-readable storage medium, on which instructions are stored, the instructions comprising:

[0028] Sending a data acquisition request, the data acquisition request at least including attribute field information and location information of the data to be acquired, wherein the attribute field information includes first-category attribute information and second-category attribute information; and

[0029] Receive data corresponding to the attribute field information included in the data acquisition request.

[0030] The data management method and device, electronic device and computer-readable storage medium provided by the embodiments of the present invention can achieve unified management of unstructured data by setting attribute field information to create an attribute metadata table, performing two-level attribute data extraction on object data to write into the attribute metadata table.

[0031] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0033] Figure 1 A schematic diagram of an application scenario of a business system provided by an embodiment of the present invention;

[0034] Figure 2 A flow chart of an embodiment of the data management method provided by the present invention;

[0035] Figure 3 A flow chart of another embodiment of the data management method provided by the present invention;

[0036] Figure 4 is a flow chart of a process for extracting attribute field information in an embodiment of the present invention;

[0037] Figure 5 A schematic diagram of the structure of an embodiment of a data management device provided by the present invention;

[0038] Figure 6 A schematic diagram of the structure of another embodiment of the data management device provided by the present invention;

[0039] Figure 7 A schematic structural diagram of an electronic device embodiment provided by the present invention. DETAILED DESCRIPTION

[0040] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0041] Due to the individual differences in data structure, unstructured data cannot be uniformly extracted and stored in terms of metadata and features of object data compared to structured data. It can only be stored as a whole and has great differences in data construction and analysis. Therefore, it can only be processed in a targeted manner object by object, which is not conducive to the batch construction and analysis of large amounts of data.

[0042] Therefore, in response to the defects of the prior art, the present application proposes a data management method, whose main principle is: setting attribute field information to create an attribute metadata table, performing two-level attribute data extraction on object data to write into the attribute metadata table, thereby performing unified metadata extraction and creation on unstructured data to achieve standardized management of unstructured data.

[0043] The method provided by the embodiment of the present invention can be applied to any business system with data processing function. Figure 1 A schematic diagram of an application scenario of a business system provided by an embodiment of the present invention, Figure 1 The structure shown is only one example of a business system to which the technical solution of the present invention can be applied. Figure 1As shown, when the business system manages unstructured object data, first, it needs to generate an attribute metadata table according to specific attribute field information. The attribute field information includes two types of attribute information, namely, first-class attribute information and second-class attribute information, wherein the first-class attribute information is used to identify basic attribute data such as type, name, creation time, submitter information, size, etc. of the object data, and the second-class attribute information is used to identify various characteristic data unique to the unstructured object data. After creating the attribute metadata table based on the above attribute field information as the table header, the business system extracts the first-class attribute data corresponding to the first-class attribute information and the second-class attribute data corresponding to the second-class attribute information for the target object data to be processed. With regard to the extraction of the first-class attribute data, its basic attribute data can be directly obtained from the target object data; with regard to the extraction of the second-class attribute data, the corresponding characteristic data can be obtained by calling various application programming interfaces (Application Programming Interface; hereinafter referred to as: API), for example, it can be extracted by calling machine learning model feature extraction API, calling multimedia processing API, calling machine intelligence API, etc. By extracting two levels of attribute data from the target object data and writing them into the attribute metadata table, unified management of unstructured data can be achieved. For example, the attribute metadata table can be created and managed in the form of a database schema definition language (Data Definition Language; hereinafter referred to as: DDL), which can conveniently and flexibly provide metadata views of object data, especially unstructured data. It can also perform associated queries with other structured data using the Structured Query Language (hereinafter referred to as: SQL), thereby achieving standardized and unified management of unstructured data and structured data.

[0044] The above embodiments are illustrations of the technical principles and exemplary application frameworks of the embodiments of the present invention. The specific technical solutions of the embodiments of the present invention are further described in detail below through multiple embodiments.

[0045] Embodiment 1

[0046] Figure 2 This is a flow chart of an embodiment of the data management method provided by the present invention. The execution subject of the method can be the above-mentioned business system, or a cloud service platform that can provide cloud services, or various server devices that support the cloud service platform, or a device or chip integrated on these server devices. Figure 2 As shown, the data management method includes the following steps:

[0047] S201, generating an attribute metadata table according to attribute field information.

[0048] In the embodiment of the present invention, the attribute field information includes first-class attribute information and second-class attribute information. The first-class attribute information is used to identify basic attribute data such as type, name, creation time, submitter information, size, etc. of the object data, and the second-class attribute information is used to identify various characteristic data unique to the unstructured object data. When managing the unstructured object data, first, it is necessary to generate an attribute metadata table according to the specific attribute field information. The attribute field information can be set manually, or the attribute field information can be extracted from the sample object data by analyzing it.

[0049] S202, acquiring first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data.

[0050] In the embodiment of the present invention, after creating the attribute metadata table based on the above attribute field information as the table header, the first type of attribute data corresponding to the first type of attribute information and the second type of attribute data corresponding to the second type of attribute information are extracted for the target object data to be processed. With regard to the extraction of the first type of attribute data, its basic attribute data can be directly obtained from the target object data; with regard to the extraction of the second type of attribute data, the corresponding feature data can be obtained by calling various APIs.

[0051] S203: Write the first type of attribute data and the second type of attribute data of the target object data into an attribute metadata table.

[0052] In an embodiment of the present invention, after obtaining the first type of attribute data and the second type of attribute data of the target object data, the first type of attribute data and the second type of attribute data are written into the attribute metadata table according to the attribute field information in the attribute metadata table. For example, a DDL CREATE TABLE statement may be used to create the attribute metadata table.

[0053] The data management method provided by the embodiment of the present invention creates an attribute metadata table by setting attribute field information, extracts two-level attribute data from object data, and writes the two-level attribute data into the attribute metadata table, thereby realizing unified management of unstructured data.

[0054] Embodiment 2

[0055] Figure 3 FIG. 1 is a flow chart of another embodiment of the data management method provided by the present invention. Figure 3 As shown in the above Figure 2 Based on the illustrated embodiment, the data management method provided in this embodiment may further include the following steps:

[0056] S301: Acquire at least one sample object data according to location information input by a user.

[0057] S302: extract attribute field information for at least one sample object data.

[0058] In an embodiment of the present invention, the sample object data may be analyzed to extract attribute field information therefrom. Specifically, the sample object data may be acquired through location information input by a user, and the attribute field information may be extracted by analyzing the sample object data. The acquired sample object data may be one or more. When the acquired sample object data is multiple, at least one sample object data may be selected from the multiple sample object data according to a preset rule to extract the attribute field information.

[0059] When extracting the first type of attribute information in the attribute field information, a type analysis can be performed on at least one of the above-mentioned sample object data, such as pictures, videos, columnar compressed data, etc.; then, based on the analysis results, at least one of the type, name, creation time, submitter information or size of the sample object data is obtained, and the first type of attribute information is determined based on the information obtained.

[0060] When extracting the second type of attribute information in the attribute field information, you can call an API to obtain feature data of at least one sample object data. For example, you can extract it by calling a machine learning model feature extraction API, calling a multimedia processing API, calling a machine intelligence API, etc.; then, determine the second type of attribute information based on the acquired feature data.

[0061] S303: Generate an attribute metadata table according to the attribute field information.

[0062] S304, obtaining first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data.

[0063] S305: Write the first type of attribute data and the second type of attribute data of the target object data into the attribute metadata table.

[0064] In the embodiment of the present invention, steps S303 to S305 are the same as above. Figure 2 Steps S201 to S203 in the illustrated embodiment are the same and will not be described in detail herein.

[0065] In the embodiment of the present invention, after the attribute metadata table for each target object data is created through the above steps, a unified operation may be performed on the attribute metadata table, which may specifically include the following steps:

[0066] S306: According to the adjustment instruction for the location information input by the user, add, modify or delete the attribute field in the attribute metadata table corresponding to the location information.

[0067] S307: For the added, modified or deleted attribute fields, add, modify or delete columns of the corresponding attribute data in the attribute metadata table.

[0068] Specifically, for deleted attribute fields, a column deletion operation can be performed on the corresponding attribute data in the attribute metadata table; for added or modified attribute fields, the first-category attribute data and the second-category attribute data of the target object data can be re-acquired, and an add or modify column operation can be performed in the attribute metadata table based on the re-acquired first-category attribute data and the second-category attribute data. For example, a DDL ALTER TABLE statement can be used to adjust the attribute metadata table.

[0069] S308: Delete the attribute metadata table corresponding to the location information according to the deletion instruction input by the user for the location information.

[0070] In the embodiment of the present invention, a DDL DROP TABLE statement may also be used to delete the attribute metadata table.

[0071] Figure 4 FIG. 1 is a flowchart of the process of extracting attribute field information in an embodiment of the present invention. Figure 4 As shown, in the above embodiment of the present invention, when extracting attribute field information, the following steps may be adopted:

[0072] S401, obtaining location information input by a user.

[0073] S402, determine whether the location information corresponds to object data or a directory. If it corresponds to object data, execute step S403; if it corresponds to a directory, execute step S405.

[0074] S403: Determine the parent directory of the object data as the location attribute of the attribute metadata table, and determine the object data as sample object data.

[0075] S404, extract the first type of attribute information from the sample object data, and execute step S412.

[0076] S405: Determine the directory as a location attribute of the attribute metadata table.

[0077] In the embodiment of the present invention, after the user inputs the location information, at least one sample object data is obtained according to the location information input by the user. For example, if the location information is a Uniform Resource Locator (URL), it is determined whether the URL corresponds to an object data or a directory. If it corresponds to an object data, the object data is used as the sample object data to extract the first type of attribute information; if it corresponds to a directory, all the object data or part of the object data under the directory is used as the sample object data to extract the first type of attribute information. For details, see the following steps S406 to S408.

[0078] S406, determine whether to use object name filtering, if yes, execute step S407, otherwise, execute step S408.

[0079] S407: Filter the object data in the directory according to a preset rule, and determine the filtered object data as sample object data.

[0080] S408: Determine all object data in the directory as sample object data.

[0081] In the embodiment of the present invention, if object name filtering is set, filtering is performed according to preset filtering rules, and the filtered object data is used as sample object data. If it is not set, all object data under the directory is used as sample object data.

[0082] S409: extracting the first type of attribute information from the sample object data.

[0083] S410, determining whether the first type of attribute information of all sample object data is consistent, if so, executing step S412, otherwise, executing step S411.

[0084] S411, an error message is returned, indicating that the attributes of the sample object data are inconsistent.

[0085] In the embodiment of the present invention, if multiple sample object data are extracted, it is necessary to determine whether the first type of attribute information extracted from all sample object data is consistent. Only when they are consistent, the subsequent second type of attribute information extraction operation is performed.

[0086] S412, determining whether there is object data with the second type of attribute information in the sample object data corresponding to the location attribute, if yes, executing step S413, otherwise, executing step S414.

[0087] S413, extracting the second type of attribute information from the sample object data.

[0088] S414: Store the extracted attribute information as attribute field information.

[0089] In an embodiment of the present invention, if there is sample object data with second-category attribute information in the directory, the second-category attribute information extraction operation is performed on it, and then the extracted first-category attribute information, or the first-category attribute information and the second-category attribute information, is stored as attribute field information.

[0090] The data management method provided by the embodiment of the present invention creates an attribute metadata table by setting attribute field information, extracts two-level attribute data from object data, and creates and manages the attribute metadata table, which can conveniently and flexibly provide metadata views of unstructured data. It can also perform associated queries with other structured data, thereby achieving standardized and unified management of unstructured data and structured data.

[0091] Embodiment 3

[0092] Figure 5 A schematic diagram of a data management device according to an embodiment of the present invention can be used to perform the following steps: Figure 2 The method steps shown. Figure 5 As shown, the data management device may include: a generating module 51 , a first acquiring module 52 and a writing module 53 .

[0093] Among them, the generation module 51 is used to generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first acquisition module 52 is used to acquire the first-category attribute data corresponding to the first-category attribute information of the target object data, and the second-category attribute data corresponding to the second-category attribute information; the writing module 53 is used to write the first-category attribute data and the second-category attribute data of the target object data into the attribute metadata table.

[0094] In the embodiment of the present invention, the first type of attribute information is used to identify basic attribute data such as the type, name, creation time, submitter information, size, etc. of the object data, and the second type of attribute information is used to identify various characteristic data unique to the unstructured object data. When managing the unstructured object data, first, it is necessary to generate an attribute metadata table according to specific attribute field information. The attribute field information can be set manually, or the attribute field information can be extracted from the sample object data by analyzing it. The generation module 51 creates an attribute metadata table based on the above attribute field information as a table header. Then, the first acquisition module 52 performs an extraction operation of the first type of attribute data corresponding to the first type of attribute information and the second type of attribute data corresponding to the second type of attribute information for the target object data to be processed. With respect to the extraction of the first type of attribute data, its basic attribute data can be directly obtained from the target object data; with respect to the extraction of the second type of attribute data, the corresponding characteristic data can be obtained by calling various APIs. Then, the writing module 53 writes the first type of attribute data and the second type of attribute data obtained by the first acquisition module 52 into the attribute metadata table according to the attribute field information in the attribute metadata table. For example, a DDL CREATE TABLE statement may be used to create a property metadata table.

[0095] The data management device provided by the embodiment of the present invention creates an attribute metadata table by setting attribute field information, extracts two-level attribute data from object data, and writes the two-level attribute data into the attribute metadata table, thereby realizing unified management of unstructured data.

[0096] Embodiment 4

[0097] Figure 6 A schematic diagram of another embodiment of the data management device provided by the present invention can be used to perform the following steps: Figure 3 The method steps shown. Figure 6 As shown in the above Figure 5 On the basis of the illustrated embodiment, the data management device provided by the embodiment of the present invention may further include: a second acquisition module 61 and an extraction module 62 .

[0098] The second acquisition module 61 may be used to acquire at least one sample object data according to the location information input by the user; the extraction module 62 may be used to extract attribute field information from the at least one sample object data acquired by the second acquisition module 61 .

[0099] Specifically, the second acquisition module 61 may include: a first acquisition unit 611 and a selection unit 612 .

[0100] Among them, the first acquisition unit 611 can be used to acquire multiple sample object data according to the location information input by the user; the selection unit 612 can be used to select at least one sample object data from the multiple sample object data acquired by the first acquisition unit 611 according to a preset rule.

[0101] In the embodiment of the present invention, the attribute field information can be extracted from the sample object data by analyzing the sample object data. Specifically, the second acquisition module 61 can acquire the sample object data through the location information input by the user, and the extraction module 62 extracts the attribute field information by analyzing the sample object data. The sample object data acquired by the second acquisition module 61 can be one or more. When the sample object data acquired by the first acquisition unit 611 in the second acquisition module 61 is multiple, the selection unit 612 can select at least one sample object data from the multiple sample object data according to a preset rule to extract the attribute field information.

[0102] In addition, the extraction module 62 may include: an analyzing unit 621 , a second acquiring unit 622 , and a first determining unit 623 .

[0103] Among them, the analysis unit 621 can be used to perform type analysis on at least one sample object data; the second acquisition unit 622 can be used to obtain at least one of the type, name, creation time, submitter information or size of the sample object data according to the analysis result of the analysis unit 621; the first determination unit 623 can be used to determine the first category of attribute information according to at least one of the type, name, creation time, submitter information or size of the sample object data obtained by the second acquisition unit 622.

[0104] The extraction module 62 may further include: a calling unit 624 and a second determining unit 625 .

[0105] Among them, the calling unit 624 can be used to call the API to obtain feature data of at least one sample object data. For example, it can be extracted by calling the machine learning model feature extraction API, calling the multimedia processing API, calling the machine intelligence API, etc.; then, the second type of attribute information is determined based on the acquired feature data; the second determination unit 625 can be used to determine the second type of attribute information based on the feature data acquired by the calling unit 624.

[0106] Furthermore, the data management device provided by the embodiment of the present invention may also include: an adjustment module 63. The adjustment module 63 may be used to add, modify or delete attribute fields in the attribute metadata table corresponding to the location information according to the adjustment instruction for the location information input by the user; for the deleted attribute fields, delete the corresponding attribute data in the attribute metadata table; or, for the added or modified attribute fields, reacquire the first and second attribute data of the target object data, and add or modify the columns in the attribute metadata table according to the reacquired first and second attribute data. For example, the DDL ALTER TABLE statement may be used to adjust the attribute metadata table.

[0107] Furthermore, the data management device provided by the embodiment of the present invention may further include: a deletion module 64. The deletion module 64 may be used to delete the attribute metadata table corresponding to the location information according to the deletion instruction for the location information input by the user. For example, a DDL DROP TABLE statement may be used to delete the attribute metadata table.

[0108] The data management device provided by the embodiment of the present invention can create an attribute metadata table by setting attribute field information, extract two-level attribute data from object data, and create and manage the attribute metadata table, so as to conveniently and flexibly provide metadata views of unstructured data. It can also perform associated queries with other structured data, thereby realizing standardized and unified management of unstructured data and structured data.

[0109] Embodiment 5

[0110] The internal functions and structure of the data management device are described above. The device can be implemented as an electronic device. Figure 7 This is a schematic diagram of the structure of an electronic device embodiment provided by the present invention. Figure 7 As shown, the electronic device includes a memory 71 and a processor 72 .

[0111] The memory 71 is used to store programs. In addition to the above programs, the memory 71 can also be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device, contact data, phone book data, messages, pictures, videos, etc.

[0112] The memory 71 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0113] The processor 72 is not limited to a central processing unit (CPU), but may also be a graphics processing unit (GPU), a field programmable gate array (FPGA) or an artificial intelligence (AI) chip. The processor 72 is coupled to the memory 71 and executes the program stored in the memory 71 to:

[0114] Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information;

[0115] Acquire first-category attribute data corresponding to the first-category attribute information of the target object data, and second-category attribute data corresponding to the second-category attribute information;

[0116] The first-category attribute data and the second-category attribute data of the target object data are written into the attribute metadata table.

[0117] Further, if Figure 7 As shown, the electronic device may also include: a communication component 73, a power component 74, an audio component 75, a display 76 and other components. Figure 7 Only some components are shown schematically, which does not mean that the electronic device only includes Figure 7 Components shown.

[0118] The communication component 73 is configured to facilitate wired or wireless communication between the electronic device and other devices. The electronic device can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 73 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 73 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0119] The power supply assembly 74 provides power to various components of the electronic device. The power supply assembly 74 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device.

[0120] The audio component 75 is configured to output and / or input audio signals. For example, the audio component 75 includes a microphone (MIC), and when the electronic device is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 71 or sent via the communication component 73. In some embodiments, the audio component 75 also includes a speaker for outputting audio signals.

[0121] The display 76 includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0122] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data management method, characterized in that: include: Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first-category attribute information is used to identify basic attribute data of object data; the second-category attribute information is used to identify various characteristic data specific to unstructured object data; Acquire first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data; The first type of attribute data and the second type of attribute data of the target object data are written into the attribute metadata table.

2. The data management method according to claim 1, characterized in that: Before generating the attribute metadata table according to the attribute field information, the method further includes: Acquire at least one sample object data according to the location information input by the user; For the at least one sample object data, attribute field information is extracted.

3. The data management method according to claim 2, characterized in that: The step of acquiring at least one sample object data according to the location information input by the user comprises: Acquire multiple sample object data according to the location information input by the user; At least one sample object data is selected from the plurality of sample object data according to a preset rule.

4. The data management method according to claim 2, characterized in that: The step of extracting attribute field information from the at least one sample object data includes: Performing type analysis on at least one sample object data; According to the analysis result, obtaining at least one of the type, name, creation time, submitter information or size of the sample object data; The first type of attribute information is determined according to at least one of the type, name, creation time, submitter information or size of the acquired sample object data.

5. The data management method according to claim 4, characterized in that: The extracting attribute field information from the at least one sample object data further includes: Calling an application programming interface to obtain feature data of the at least one sample object data; The second type of attribute information is determined according to the acquired feature data.

6. The data management method according to claim 2, characterized in that: Also includes: According to the adjustment instruction input by the user for the location information, add, modify or delete the attribute field in the attribute metadata table corresponding to the location information; For the deleted attribute field, a delete column operation is performed on the corresponding attribute data in the attribute metadata table; or, For the added or modified attribute fields, the first and second attribute data of the target object data are reacquired, and column addition or modification operations are performed in the attribute metadata table according to the reacquired first and second attribute data.

7. The data management method according to claim 2, characterized in that: Also includes: According to a deletion instruction input by a user for the location information, the attribute metadata table corresponding to the location information is deleted.

8. A data management device, characterized in that: include: A generating module, used to generate an attribute metadata table according to attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first-category attribute information is used to identify basic attribute data of object data; the second-category attribute information is used to identify various characteristic data specific to unstructured object data; A first acquisition module, used to acquire first-category attribute data corresponding to the first-category attribute information of the target object data, and second-category attribute data corresponding to the second-category attribute information; The writing module is used to write the first type of attribute data and the second type of attribute data of the target object data into the attribute metadata table.

9. The data management device according to claim 8, characterized in that: Also includes: A second acquisition module, used to acquire at least one sample object data according to the location information input by the user; The extraction module is used to extract attribute field information from the at least one sample object data.

10. The data management device according to claim 9, characterized in that: The second acquisition module includes: A first acquisition unit, used to acquire a plurality of sample object data according to the position information input by the user; The selection unit is used to select at least one sample object data from the plurality of sample object data according to a preset rule.

11. The data management device according to claim 9, characterized in that: The extraction module comprises: An analysis unit, configured to perform type analysis on at least one sample object data; A second acquisition unit, configured to acquire at least one of the type, name, creation time, submitter information or size of the sample object data according to the analysis result; The first determining unit is used to determine the first type of attribute information according to at least one of the type, name, creation time, submitter information or size of the acquired sample object data.

12. The data management device according to claim 11, characterized in that: The extraction module also includes: A calling unit, configured to call an application programming interface to obtain feature data of the at least one sample object data; The second determining unit is used to determine the second type of attribute information according to the acquired feature data.

13. The data management device according to claim 9, characterized in that: Also includes: An adjustment module is used to add, modify or delete attribute fields in the attribute metadata table corresponding to the location information according to an adjustment instruction input by a user for the location information; for deleted attribute fields, delete columns of corresponding attribute data in the attribute metadata table; or, for added or modified attribute fields, reacquire first-category attribute data and second-category attribute data of the target object data, and add or modify columns in the attribute metadata table according to the reacquired first-category attribute data and second-category attribute data.

14. The data management device according to claim 9, characterized in that: Also includes: The deleting module is used to delete the attribute metadata table corresponding to the location information according to a deletion instruction input by a user for the location information.

15. A data management method, characterized in that: include: Sending a data acquisition request, the data acquisition request at least including attribute field information and location information of the data to be acquired, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first-category attribute information is used to identify basic attribute data of the object data; the second-category attribute information is used to identify various characteristic data specific to the unstructured object data; as well as Receive data corresponding to the attribute field information included in the data acquisition request.

16. An electronic device, characterized in that: include: Memory, used to store programs; A processor, configured to run the program stored in the memory, to: Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first-category attribute information is used to identify basic attribute data of object data; the second-category attribute information is used to identify various characteristic data specific to unstructured object data; Acquire first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data; The first type of attribute data and the second type of attribute data of the target object data are written into the attribute metadata table.

17. A computer-readable storage medium having instructions stored thereon, the instructions comprising: Generate an attribute metadata table according to the attribute field information, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first-category attribute information is used to identify basic attribute data of object data; the second-category attribute information is used to identify various characteristic data specific to unstructured object data; Acquire first-category attribute data corresponding to the first-category attribute information and second-category attribute data corresponding to the second-category attribute information of the target object data; The first type of attribute data and the second type of attribute data of the target object data are written into the attribute metadata table.

18. A computer-readable storage medium having instructions stored thereon, the instructions comprising: Sending a data acquisition request, the data acquisition request at least including attribute field information and location information of the data to be acquired, wherein the attribute field information includes first-category attribute information and second-category attribute information; the first-category attribute information is used to identify basic attribute data of the object data; the second-category attribute information is used to identify various characteristic data specific to the unstructured object data; and Receive data corresponding to the attribute field information included in the data acquisition request.

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