CN116579300A - Automatic conversion method and device for multi-source heterogeneous data - Google Patents
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Abstract
The application provides an automatic conversion method and device for multi-source heterogeneous data, and relates to the technical field of data management, wherein the method comprises the following steps: receiving data sent by a plurality of data sources, wherein the data structure of the data comprises a plurality of formats; for current data in one format, identifying the format type of the current data, and determining a corresponding code; determining a corresponding conversion rule according to the codes; and converting the format of the current data according to the conversion rule, and outputting standardized data. In this way, the input data can be automatically identified and converted, so that the efficiency of data conversion can be improved, and the cost of data conversion can be reduced.
Description
Technical Field
Embodiments of the present application relate generally to the field of data management technology, and more particularly, to an automated conversion method and apparatus for multi-source heterogeneous data.
Background
In big data management systems, various types of raw input data need to be read and converted. Since these data are often heterogeneous data of multiple sources, i.e., not only of different sources but also of different structures, extensive manual pre-analysis is often required. The manual processing mode is low in efficiency, repeated work can be carried out frequently, waste of labor cost is caused, and meanwhile management of data is not facilitated.
Disclosure of Invention
In view of the foregoing, embodiments of the present application provide an automatic conversion method and apparatus for multi-source heterogeneous data, which are used for automatically identifying and converting input data.
In a first aspect of the present application, an automated conversion method for multi-source heterogeneous data is provided, including:
receiving data sent by a plurality of data sources, wherein the data structure of the data comprises a plurality of formats;
for current data in one format, identifying the format type of the current data, and determining a corresponding code;
determining a corresponding conversion rule according to the codes;
and converting the format of the current data according to the conversion rule, and outputting standardized data.
In some embodiments, the identifying the format type of the current data, determining the corresponding code, includes:
and identifying the format type of the data by using a unified interface definition identification mode, and determining the corresponding code.
In some embodiments, the determining a corresponding conversion rule according to the encoding includes:
and matching the code with the conversion rules in the conversion rule library, and determining the successfully matched conversion rule as the coded conversion rule.
In some embodiments, the conversion rule base stores different coding identifications and conversion rules corresponding to the coding identifications;
the step of matching the code with the conversion rules in the conversion rule base, and determining the successfully matched conversion rule as the coded conversion rule comprises the following steps:
and matching the code with the code identification in the conversion rule library, and if the matching is successful, determining the successfully matched conversion rule as the conversion rule of the code.
In some embodiments, further comprising:
if the matching is unsuccessful, the coding conversion rule is determined manually, and the coding identification of the coding and the conversion rule are stored in the conversion rule base.
In some embodiments, the data structure of the data includes json format, txt format, xls format, and csv format.
In some embodiments, after the identifying the format type of the current data and determining the corresponding encoding, the method further comprises:
the identified data is divided into a plurality of categories according to codes, and then the format of the data is converted according to the categories.
In a second aspect of the present application, there is provided an automated conversion apparatus for multi-source heterogeneous data, comprising:
the data receiving module is used for receiving data sent by a plurality of data sources, wherein the data structure of the data comprises a plurality of formats;
the format type identification module is used for identifying the format type of the current data of one format and determining the corresponding code;
the conversion rule determining module is used for determining a corresponding conversion rule according to the codes;
and the format conversion module is used for converting the format of the current data according to the conversion rule and outputting standardized data.
In a third aspect of the application, there is provided an electronic device comprising a memory having a computer program stored thereon and a processor implementing a method as described above when executing the program.
In a fourth aspect of the application, a computer readable storage medium is provided, having stored thereon a computer program which when executed by a processor implements a method as described above.
By the automatic conversion method of the multi-source heterogeneous data, the input data can be automatically identified and converted, so that the data conversion efficiency can be improved, and the data conversion cost can be reduced.
The matters described in the summary section are not intended to limit the critical or essential features of the embodiments of the application nor to limit the scope of the application. Other features of the present application will become apparent from the description that follows.
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The above and other features, advantages and aspects of embodiments of the present application will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, wherein like or similar reference numerals denote like or similar elements, in which:
FIG. 1 is a flow chart of an automated conversion method of multi-source heterogeneous data according to a first embodiment of the present application;
fig. 2 is a schematic structural diagram of an automatic conversion device for multi-source heterogeneous data according to a second embodiment of the present application;
FIG. 3 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the application;
fig. 4 shows a data format conversion schematic of an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
The automatic conversion method of the multi-source heterogeneous data can automatically identify and convert the input data, so that the efficiency of data conversion can be improved. Specifically, as shown in fig. 1, a flowchart of an automated conversion method of multi-source heterogeneous data according to a first embodiment of the present application is shown. In this embodiment, the automatic conversion method of multi-source heterogeneous data may include the following steps:
s101: and receiving data sent by a plurality of data sources, wherein the data structure of the data comprises a plurality of formats.
The automatic conversion method of the multi-source heterogeneous data can be applied to a big data management system and used for managing the data input into the big data management system, namely, converting the data with different formats into the data with predefined uniform standard formats, thereby being convenient for the arrangement and management of the data. Wherein the big data management system may be provided with a plurality of data structures, each data interface may interface with one or more data sources. The format of the data sent by the data source into the big data management system may include a variety of formats, such as json format, txt format, xls format, and csv format. This is merely an exemplary format of the description data, and the format of the data sent to the big data management system may include other formats, which are not particularly limited herein.
S102: and identifying the format type of the current data of one format, and determining the corresponding code.
In this embodiment, the big data management system may receive data sent by one or more data sources within a preset period of time. The big data management system may process the received data in the same way. The manner of processing may include parallel or serial, or parallel and serial may be synchronized. The technical scheme of the present application will be described below by taking a data processing procedure as an example. And identifying the format type of the current data for the current data in one format, and determining the corresponding code of the format type of the current data. In determining the corresponding code of the format type of the data, the corresponding code of the format type of the current data can be determined in the form of a keyword.
S103: and determining a corresponding conversion rule according to the codes.
Specifically, in the big data management system, a conversion rule base is provided, and different coding identifiers and conversion rules corresponding to the coding identifiers are stored in the conversion rule base. And the big data management system uses a unified interface definition recognition mode to recognize the format type of the data and determine the corresponding code. After the corresponding codes are determined, the codes are matched with the conversion rules in the conversion rule base, and the successfully matched conversion rules are determined as the conversion rules of the codes.
In this embodiment, after the code is matched with the code identifier in the conversion rule base, whether the code is successfully matched is further determined, and if the code is successfully matched, the conversion rule that is successfully matched is determined as the conversion rule of the code.
If the matching is unsuccessful, the coding conversion rule is manually determined, and the coding identification of the coding and the conversion rule are stored in the conversion rule base, so that the conversion rule base is updated.
S104: and converting the format of the current data according to the conversion rule, and outputting standardized data.
In this embodiment, after determining a conversion rule corresponding to current data, format conversion is performed on the current data according to the conversion rule, the current data is converted into standardized data, and the converted standardized data is output. After outputting the standardized data, the standardized data may be stored.
Specifically, pure text storage is adopted for the data after format conversion, a UTF-8 character set is used, the data after format conversion consists of records, and each row represents one record; each record is divided into a plurality of fields by separators, and the separators are commas; if commas are included in the content of the data after format conversion, escaping is carried out by using a slash mode; if a line feed symbol occurs, the representation is also used in an escape mode; each record is generated automatically ordered.
In this embodiment, after the format conversion, the data in other formats may be converted into a CSV structure file, and a record may be generated and automatically ordered while being converted into the CSV structure file. When one data file is processed, automatically counting the sequence group, the total line number, the total column number, the null value number and the like of the record generated in the generated CSV structure file, and generating a data abstract in the CSV structure file header by combining the data source information and the data column attribute in the original data file to represent file information. And when the next data file is processed, adding the generated data abstract to the back of the previous data abstract, namely sorting the data abstract according to the processing sequence, and sorting the data contents according to the same sequence, wherein all the data summaries are positioned in front of the healed data contents.
Fig. 4 is a schematic diagram of data format conversion according to an embodiment of the present application. And (3) generating the file with the CSV structure after the CSV standardization of the data files with different formats. Wherein [1-2] represents the number of lines corresponding to the file in the data replication, "employee table from MySQL" represents the source of the data and the data format before format conversion, "data column attribute: name (char, 32), gender (char, 1), age (int), phone (char, 12) "indicates what attribute the data columns all include, total number of lines: 2, total number of columns: 4, null number: 2", indicates overall statistics of the data. For the data column attributes of Excel achievement data, namely name, chinese, mathematics, english, total line number, 4, null value number, 1 ', "[4-5] are acquired from Txt films, the data column attributes, namely film name, mapping time, bean segment score, total line number, 3, null value number, 0', can be similarly explained, and will not be explained in detail here.
The automatic conversion method of the multi-source heterogeneous data can automatically identify and convert the input data, so that the efficiency of data conversion can be improved.
Furthermore, as an optional embodiment of the present application, in the foregoing embodiment, after identifying a format type of the current data and determining a corresponding code, the method further includes:
the identified data is divided into a plurality of categories according to codes, and then the format of the data is converted according to the categories. Therefore, format conversion in category concentration is not needed for the data, the converted data is stored according to the category of conversion money, and further management of the data is facilitated.
The technical scheme of the application is described below with reference to specific examples. For example, the big data management system receives txt format data sent by the data source, and the standardized data output by the predefined big data management system is josn format data. In this way, after the big data management system receives the txt format data sent by the data source, the format of the data is firstly determined, then the code corresponding to the format of the data is determined according to the format of the data, then the determined code is matched with the conversion rule in the conversion rule base, and when the matching is successful, the format conversion is performed on the data sent by the data source by using the predefined conversion rule which is successfully matched, so as to generate standardized data. I.e. generating data in another user predefined format.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of action described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are all alternative embodiments, and that the acts and modules involved are not necessarily required by the present application.
The above description of the method embodiments further describes the solution of the present application by means of device embodiments.
Fig. 2 is a schematic structural diagram of an automatic conversion device for multi-source heterogeneous data according to a second embodiment of the present application. The automatic conversion device for multi-source heterogeneous data of the embodiment comprises:
a data receiving module 201, configured to receive data sent by a plurality of data sources, where a data structure of the data includes a plurality of formats;
a format type identifying module 202, configured to identify, for current data in one format, a format type of the current data, and determine a corresponding code;
a conversion rule determining module 203, configured to determine a corresponding conversion rule according to the encoding;
and the format conversion module 204 is configured to convert the format of the current data according to the conversion rule, and output standardized data.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the described modules may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
Fig. 3 illustrates a block diagram of an exemplary electronic device 300 capable of implementing embodiments of the application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
The electronic device 300 includes a computing unit 301 that can perform various appropriate actions and processes according to a computer program stored in a ROM302 or a computer program loaded from a storage unit 308 into a RAM 303. In the RAM303, various programs and data required for the operation of the electronic device 300 may also be stored. The computing unit 301, the ROM302, and the RAM303 are connected to each other by a bus 304. I/O interface 305 is also connected to bus 304.
Various components in the electronic device 300 are connected to the I/O interface 305, including: an input unit 306 such as a keyboard, a mouse, etc.; an output unit 307 such as various types of displays, speakers, and the like; a storage unit 308 such as a magnetic disk, an optical disk, or the like; and a communication unit 309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as an automated transformation method of multi-source heterogeneous data. For example, in some embodiments, the automated conversion method of multi-source heterogeneous data may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 300 via the ROM302 and/or the communication unit 309. When the computer program is loaded into the RAM303 and executed by the computing unit 301, one or more steps of the above-described automated conversion method of multi-source heterogeneous data may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform an automated conversion method of multi-source heterogeneous data by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present application, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or electronic device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or electronic device, or any suitable combination of the preceding. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Moreover, although operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the application. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (10)
1. The automatic conversion method of the multi-source heterogeneous data is characterized by comprising the following steps of:
receiving data sent by a plurality of data sources, wherein the data structure of the data comprises a plurality of formats;
for current data in one format, identifying the format type of the current data, and determining a corresponding code;
determining a corresponding conversion rule according to the codes;
and converting the format of the current data according to the conversion rule, and outputting standardized data.
2. The automated transformation method of claim 1, wherein the identifying the format type of the current data, determining the corresponding code, comprises:
and identifying the format type of the data by using a unified interface definition identification mode, and determining the corresponding code.
3. The automated transformation method of claim 2, wherein the determining the corresponding transformation rule from the encoding comprises:
and matching the code with the conversion rules in the conversion rule library, and determining the successfully matched conversion rule as the coded conversion rule.
4. The automated conversion method according to claim 3, wherein the conversion rule library stores different code identifiers and conversion rules corresponding to the code identifiers;
the step of matching the code with the conversion rules in the conversion rule base, and determining the successfully matched conversion rule as the coded conversion rule comprises the following steps:
and matching the code with the code identification in the conversion rule library, and if the matching is successful, determining the successfully matched conversion rule as the conversion rule of the code.
5. The automated transformation method of claim 4, further comprising:
if the matching is unsuccessful, the coding conversion rule is determined manually, and the coding identification of the coding and the conversion rule are stored in the conversion rule base.
6. The automated transformation method of claim 5, wherein the data structure of the data comprises json format, txt format, xls format, and csv format.
7. The automated transformation method of claim 6, wherein after the identifying the format type of the current data, determining the corresponding encoding, the method further comprises:
the identified data is divided into a plurality of categories according to codes, and then the format of the data is converted according to the categories.
8. An automated conversion device for multi-source heterogeneous data, comprising:
the data receiving module is used for receiving data sent by a plurality of data sources, wherein the data structure of the data comprises a plurality of formats;
the format type identification module is used for identifying the format type of the current data of one format and determining the corresponding code;
the conversion rule determining module is used for determining a corresponding conversion rule according to the codes;
and the format conversion module is used for converting the format of the current data according to the conversion rule and outputting standardized data.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, wherein the processor, when executing the program, implements the method of any of claims 1-7.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1-7.
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