CN111353276B - Data access method and device - Google Patents
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Abstract
The application discloses a data access method and device, wherein the method comprises the following steps: after the target data to be accessed is obtained, the analysis sequence and the product identification of the target data can be determined, then a pre-constructed data decoding tree is called, and the analysis sequence and the product identification of the target data are decoded to obtain the data in the standard data format corresponding to the target data. Therefore, the method and the device uniformly utilize the pre-built data decoding tree to decode the analysis sequence and the product identification of each type of determined target data, so that the accessed different types of target data can be output as data in a standard data format, different program codes corresponding to the different types of data are not designed, the code quantity is reduced, the access cost is reduced, and the access efficiency is improved.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a data access method and apparatus.
Background
With the rapid development of communication network technology, in the current network technology application, by accessing different types of data to perform big data analysis on various types of data, the realization of various indexes and data operation has been an important content in the network application. In order to be able to analyze big data, the access of basic data of different types from each product becomes an important content, and the efficiency and quality of the access data directly influence the efficiency and quality of the subsequent analysis and processing and other processes.
The current method for accessing various types of data of each product is generally to access various types of data sources of each product respectively, namely, writing corresponding program codes for each data source respectively, and performing various coding and decoding analysis processing processes on each data source by adopting the corresponding program codes. However, in this data access method, a corresponding program code is required for each type of data source, so that not only is a lot of repeated work required to be added, resulting in high cost of development, testing and the like, but also the code amount is continuously increased and maintenance is difficult as the accessed data source or data amount is increased. In addition, for new types of data sources, the problems of difficult access and long development period also exist.
Disclosure of Invention
In view of the above, the present invention provides a data access method and apparatus, so as to solve the technical problems of difficult access, high access cost and low access efficiency of various types of data in the prior art.
In order to solve the problems, the technical scheme provided by the invention is as follows:
in a first aspect, an embodiment of the present application provides a data access method, including:
acquiring target data to be accessed;
determining the analysis sequence and the product identification of the target data;
and calling a pre-constructed data decoding tree, and decoding the analysis sequence and the product identifier of the target data to obtain data in a standard data format corresponding to the target data.
Optionally, the determining the data packet analysis sequence and the product identifier of the target data includes:
determining a data packet format corresponding to the target data;
and determining a data packet analysis sequence and a product identifier corresponding to the target data according to the data packet format.
Optionally, constructing the data decoding tree includes:
acquiring training data;
determining the analysis sequence and the product identification of the training data;
training an initial data decoding tree according to the analysis sequence of the training data, the product identification and the access data label corresponding to the training data, and generating the data decoding tree.
Optionally, the file composition structure of the initial data decoding tree is a JSON file structure.
Optionally, the method further comprises:
acquiring verification data;
determining the analysis sequence and the product identification of the verification data;
invoking the data decoding tree, and decoding the analysis sequence and the product identifier of the verification data to obtain data in a standard data format corresponding to the verification data;
and when the data in the standard data format corresponding to the verification data is inconsistent with the access data marking result corresponding to the verification data, the verification data is used as the training data again, and the data decoding tree is updated.
In a second aspect, the present application provides a data access device, including:
the first acquisition unit is used for acquiring target data to be accessed;
the first determining unit is used for determining the analysis sequence and the product identification of the target data;
the first calling unit is used for calling a pre-constructed data decoding tree, decoding the analysis sequence and the product identification of the target data, and obtaining data in a standard data format corresponding to the target data.
Optionally, the first determining unit includes:
a first determining subunit, configured to determine a data packet format corresponding to the target data;
and the second determining subunit is used for determining the data packet analysis sequence and the product identifier corresponding to the target data according to the data packet format.
Optionally, the apparatus further includes:
the second acquisition unit is used for acquiring training data;
the second determining unit is used for determining the analysis sequence and the product identification of the training data;
and the training unit is used for training the initial data decoding tree according to the analysis sequence of the training data, the product identification and the access data label corresponding to the training data, and generating the data decoding tree.
Optionally, the file composition structure of the initial data decoding tree is a JSON file structure.
Optionally, the apparatus further includes:
a third acquisition unit configured to acquire authentication data;
a third determining unit, configured to determine an analysis order and a product identifier of the verification data;
the second calling unit is used for calling the data decoding tree, decoding the analysis sequence and the product identifier of the verification data, and obtaining data in a standard data format corresponding to the verification data;
and the updating unit is used for re-using the verification data as the training data and updating the data decoding tree when the data in the standard data format corresponding to the verification data is inconsistent with the access data marking result corresponding to the verification data.
From this, the embodiment of the application has the following beneficial effects:
according to the data access method and device, after the target data to be accessed are obtained, the analysis sequence and the product identification of the target data can be determined, then the pre-constructed data decoding tree is called, the analysis sequence and the product identification of the target data are decoded, and the data in the standard data format corresponding to the target data are obtained. Therefore, the method and the device for decoding the target data of the access type uniformly utilize the pre-built data decoding tree to decode the analysis sequence and the product identification of each type of determined target data, so that the accessed target data of different types can be output as data in a standard data format, different program codes corresponding to the data of different types are not designed, the code quantity is reduced, the access cost is reduced, and the access efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a data access method provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of constructing a data decoding tree according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an initial data decoding tree according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a program code for constructing a data decoding tree according to an embodiment of the present application;
fig. 5 is a schematic flow chart of a verification data decoding tree according to an embodiment of the present application;
fig. 6 is a schematic diagram of a data access device according to an embodiment of the present application.
Detailed Description
In some data access methods, different program codes are designed for different types of data, specifically, since different types of data sources corresponding to different products are not accessed uniformly, common ways are as follows: transmission control protocol (Transmission Control Protocol, abbreviated TCP), (User Datagram Protocol, UDP), hypertext transfer protocol (Http), etc., and it is also possible to use data protocol formats of different transmission contents, such as: original data messages, messages that are expanded on the basis of the original data messages, binary messages, etc., and therefore, it is necessary to design different program codes for each of these differential data sources to support them. However, this data access method increases a lot of repetitive work, resulting in high cost of development, testing, etc., and as the amount of data or data to be accessed increases, the amount of code will continue to increase, making maintenance difficult. In addition, for new types of data sources, the problems of difficult access and long development period also exist.
In order to solve the above-mentioned drawbacks, the embodiment of the present application provides a data access method, after obtaining target data to be accessed, the analysis sequence and the product identifier of the target data may be determined first, then, a pre-constructed data decoding tree is called to decode the analysis sequence and the product identifier of the target data, so as to obtain data in a standard data format corresponding to the target data. Therefore, the method and the device for decoding the target data of the access type uniformly utilize the pre-built data decoding tree to decode the analysis sequence and the product identification of each type of determined target data, so that the accessed target data of different types can be output as data in a standard data format, different program codes corresponding to the data of different types are not designed, the code quantity is reduced, the access cost is reduced, and the access efficiency is improved.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the 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. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
First embodiment
Referring to fig. 1, a flow chart of a data access method provided in this embodiment includes the following steps:
s101: and obtaining target data to be accessed.
In the present embodiment, data to be accessed is defined as target data. It should be noted that, the present embodiment does not limit the acquisition manner of the target data, for example, the target data may be different types of data, such as binary data, received from different data sources in response to the data access command.
S102: and determining the analysis sequence and the product identification of the target data.
In this embodiment, after the target data to be accessed is obtained in step S101, the target data may be processed by using an existing or future data processing method, and the analysis sequence and the product identifier of the target data are determined according to the processing result, so as to execute the subsequent step S103.
The method comprises the steps of determining a data packet format corresponding to target data, and determining a data packet analysis sequence and a product identifier corresponding to the target data according to the determined data packet format.
Illustrating: the packet format of the target data obtained from a certain manufacturer data source may be a binary packet, and the parsing sequence of the target data and the product identifier may be determined, for example, the product identifier may include a message header (for example, may be 4 bytes) of the target data, a message length (for example, may be 4 bytes), a packet type (for example, may be 2 bytes), a login password (for example, may be 16 bytes), a device ID (for example, may be 21 bytes), and specific user data (for example, may include a specific number of bytes corresponding to each of longitude and latitude, a direction angle, an electronic downtilt angle, a mechanical downtilt angle, and the like).
S103: and calling a pre-constructed data decoding tree, and decoding the analysis sequence and the product identification of the target data to obtain data in a standard data format corresponding to the target data.
In this embodiment, after determining the analysis sequence and the product identifier of the target data in step S102, the data decoding tree constructed in advance may be further called by using the existing or future data processing method, so as to decode the data, so as to output the data in the standard data format corresponding to the target data. For example, a recursive iteration method may be adopted to repeatedly call a pre-constructed data decoding tree, and decode the data, so as to obtain data in a standard data format corresponding to the target data.
Illustrating: assuming that the data source to which the target data belongs is determined to be the data source 1, and the corresponding product identifier is: the longitude is 4 bytes, the latitude is 4 bytes, the login password is 16 bytes, and the decoding sequence is: business data decoder 1- > longitude and latitude decoder; log data decoder- > log decoder. The pre-constructed data decoding tree can be further called, and the decoders (namely the longitude and latitude decoder and the login decoder) corresponding to the product identifiers are queried and decoded according to the decoding sequence, so that the data in the standard data format corresponding to the target data can be output.
It should be noted that, in order to implement the step S103, a data decoding tree needs to be built in advance, and the specific building process can be referred to the related description of the second embodiment.
In summary, in the data access method provided in this embodiment, after target data to be accessed is obtained, an analysis sequence and a product identifier of the target data may be determined first, and then a pre-constructed data decoding tree is called to decode the analysis sequence and the product identifier of the target data, so as to obtain data in a standard data format corresponding to the target data. Therefore, the method and the device for decoding the target data of the access type uniformly utilize the pre-built data decoding tree to decode the analysis sequence and the product identification of each type of determined target data, so that the accessed target data of different types can be output as data in a standard data format, different program codes corresponding to the data of different types are not designed, the code quantity is reduced, the access cost is reduced, and the access efficiency is improved.
Second embodiment
The present embodiment will explain a specific construction process of the data decoding tree mentioned in the first embodiment. By utilizing the pre-constructed data decoding tree, target data of each type in each data source can be conveniently and rapidly accessed.
Referring to fig. 2, a schematic flow chart of constructing a data decoding tree according to the present embodiment is shown, where the flow chart includes the following steps:
s201: training data is acquired.
In this embodiment, in order to construct the data decoding tree, a large amount of preparation work needs to be performed in advance, first, various types of data corresponding to each data source need to be collected and acquired as training data, for example, data corresponding to products produced by 10 kilobytes of manufacturer a and manufacturer B may be collected in advance, each type of data corresponding to each data source is respectively used as sample data, and access data results corresponding to the sample data are marked manually in advance to train the data decoding tree.
S202: determining the analysis sequence and the product identification of the training data.
In this embodiment, after the training data is obtained through step S201, the training data cannot be directly used for training to generate a data decoding tree, but the analysis sequence of the training data and the product identifier need to be determined, where the analysis sequence of the training data refers to the decoding sequence of the training data, and the product identifier refers to the attribute information of the training data, for example, the number of bytes of longitude and latitude, the number of bytes of login password, etc., and then the determined analysis sequence of the training data and the product identifier may be used for training to obtain the data decoding tree.
S203: training the initial data decoding tree according to the analysis sequence of the training data, the product identification and the access data label corresponding to the training data, and generating a data decoding tree.
In this embodiment, after determining the parsing sequence and the product identifier of the training data in step S202, further, the initial data decoding tree may be trained according to the parsing sequence and the product identifier of the training data and the decoder tag corresponding to the training data, so as to generate the data decoding tree.
An alternative implementation manner is that the file composition structure of the initial data decoding tree is a JSON file structure. Fig. 3 is a schematic diagram of an initial data decoding tree according to an embodiment of the present application.
It should be noted that, different types of target data, corresponding parsing data and product identifiers are different, and the initial data decoding tree shown in fig. 3 is only an example diagram, and the composition structure is a file composition structure and is a JSON file structure, and may also include other decoders. The names and types of the decoders are not limited in the present application, and may be the decoders mentioned in the embodiments of the present application, or may be other names and types of decoders.
For ease of understanding, the present application will show the program code for generating the data decoding tree design according to the parsing order of the training data and the product identification in step S203 as shown in fig. 4.
After the initial data decoding tree is constructed, one sample data may be sequentially extracted from the training data, and multiple rounds of training may be performed until the training end condition is satisfied, at which time the data decoding tree is generated.
Specifically, when the training is performed in this round, the target data in the first embodiment may be replaced by the sample data extracted in this round according to steps S101 to S103 in the first embodiment, and the decoder corresponding to the sample data may be identified according to the execution process in the first embodiment through the current initial data decoding tree, so as to obtain the data in the standard data format corresponding to the sample data. Then, the data can be compared with the manual labeling result (i.e. the manually labeled access data label), and parameters (such as the type and the name of a decoder) of the data decoding tree are updated according to the difference between the data and the manual labeling result (i.e. the manually labeled access data label) until preset conditions are met, such as the change amplitude of the difference is small, the updating of the parameters is stopped, the training of the data decoding tree is completed, and a trained data decoding tree is generated.
By the above embodiment, after the data decoding tree can be generated by using the training data, further, the generated data decoding tree can be verified by using the verification data.
The following describes a data decoding tree verification method provided in an embodiment of the present application with reference to the accompanying drawings.
Referring to fig. 5, a flow diagram of a verification data decoding tree provided in an embodiment of the present application is shown, and as shown in fig. 5, the method includes:
s501: verification data is acquired.
In practical application, in order to implement verification of the data decoding tree, verification data is first acquired, where the verification data refers to data that can be used to perform verification of the data decoding tree, and after the verification data is acquired, the subsequent step S502 may be continuously performed.
S502: and determining the analysis sequence of the verification data and the product identification.
In practical application, after the verification data is obtained through step S501, the verification data cannot be directly used for the verification data decoding tree, but the analysis sequence of the verification data and the product identifier need to be determined, wherein the analysis sequence of the verification data refers to the decoding sequence of the verification data, and the product identifier refers to the attribute information of the verification data, for example, the number of bytes of longitude and latitude, the number of bytes of login password, and the like, so that the determined analysis sequence of the verification data and the determined product identifier can be utilized to verify the obtained data decoding tree.
S503: and calling a data decoding tree, and decoding the analysis sequence and the product identification of the verification data to obtain data in a standard data format corresponding to the verification data.
In the specific implementation process, after determining the analysis sequence and the product identifier of the verification data in step S502, further, the data decoding tree may be called to decode the analysis sequence and the product identifier of the verification data, so as to obtain data in a standard data format corresponding to the verification data, and further, the subsequent step S504 may be continuously executed.
S504: and when the data in the standard data format corresponding to the verification data is inconsistent with the access data marking result corresponding to the verification data, the verification data is re-used as training data, and the data decoding tree is updated.
In practical application, after obtaining the data in the standard data format corresponding to the verification data in step S503, when the data in the standard data format corresponding to the verification data is inconsistent with the manual labeling result (i.e. the manually labeled access data) corresponding to the verification data, the verification data can be re-used as training data to update the data decoding tree.
Through the embodiment, the data decoding tree can be effectively verified by using the verification data, and when the data in the standard data format corresponding to the verification data is inconsistent with the manual marking result corresponding to the verification data, the data decoding tree can be timely adjusted and updated, so that the decoding precision and accuracy of the data decoding tree can be improved.
In summary, the data decoding tree trained by the embodiment can decode the data in the standard data format corresponding to the target data according to the analysis sequence and the product identifier of the target data, and greatly reduces the code amount and the calculation amount in the decoding process, thereby effectively improving the access efficiency of the target data and reducing the access cost.
Third embodiment
The present embodiment will be described with reference to a data access device, and for relevant content, reference is made to the above-mentioned method embodiment.
Referring to fig. 6, a schematic composition diagram of a data access device according to this embodiment is provided, where the device includes:
a first obtaining unit 601, configured to obtain target data to be accessed;
a first determining unit 602, configured to determine an analysis order and a product identifier of the target data;
the first invoking unit 603 is configured to invoke a pre-built data decoding tree, and decode the analysis sequence and the product identifier of the target data, to obtain data in a standard data format corresponding to the target data.
In one implementation of the present embodiment, the first determining unit 602 includes:
a first determining subunit, configured to determine a data packet format corresponding to the target data;
and the second determining subunit is used for determining the data packet analysis sequence and the product identifier corresponding to the target data according to the data packet format.
In one implementation of this embodiment, the apparatus further includes:
the second acquisition unit is used for acquiring training data;
the second determining unit is used for determining the analysis sequence and the product identification of the training data;
and the training unit is used for training the initial data decoding tree according to the analysis sequence of the training data, the product identification and the access data label corresponding to the training data, and generating the data decoding tree.
In one implementation manner of this embodiment, the file composition structure of the initial data decoding tree is a JSON file structure.
In one implementation of this embodiment, the apparatus further includes:
a third acquisition unit configured to acquire authentication data;
a third determining unit, configured to determine an analysis order and a product identifier of the verification data;
the second calling unit is used for calling the data decoding tree, decoding the analysis sequence and the product identifier of the verification data, and obtaining data in a standard data format corresponding to the verification data;
and the updating unit is used for re-using the verification data as the training data and updating the data decoding tree when the data in the standard data format corresponding to the verification data is inconsistent with the access data marking result corresponding to the verification data.
In summary, in the data access device provided in this embodiment, after target data to be accessed is obtained, an analysis sequence and a product identifier of the target data may be determined first, and then a pre-constructed data decoding tree is called to decode the analysis sequence and the product identifier of the target data, so as to obtain data in a standard data format corresponding to the target data. Therefore, the method and the device for decoding the target data of the access type uniformly utilize the pre-built data decoding tree to decode the analysis sequence and the product identification of each type of determined target data, so that the accessed target data of different types can be output as data in a standard data format, different program codes corresponding to the data of different types are not designed, the code quantity is reduced, the access cost is reduced, and the access efficiency is improved.
From the above description of embodiments, it will be apparent to those skilled in the art that all or part of the steps of the above described example methods may be implemented in software plus necessary general purpose hardware platforms. Based on such understanding, the technical solutions of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a media gateway, etc.) to perform the methods described in the embodiments or some parts of the embodiments of the present application.
It should be noted that, in the present description, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. A method of data access, the method comprising:
acquiring target data to be accessed;
determining a data packet format corresponding to the target data;
determining a data packet analysis sequence and a product identifier corresponding to the target data according to the data packet format;
invoking a pre-constructed data decoding tree, and decoding the analysis sequence and the product identifier of the target data to obtain data in a standard data format corresponding to the target data;
constructing the data decoding tree, including:
acquiring training data;
determining the analysis sequence and the product identification of the training data;
training an initial data decoding tree according to the analysis sequence of the training data, the product identification and the access data label corresponding to the training data, and generating the data decoding tree.
2. The method of claim 1, wherein the file composition structure of the initial data decoding tree is a JSON file structure.
3. The method according to any one of claims 1 to 2, further comprising:
acquiring verification data;
determining the analysis sequence and the product identification of the verification data;
invoking the data decoding tree, and decoding the analysis sequence and the product identifier of the verification data to obtain data in a standard data format corresponding to the verification data;
and when the data in the standard data format corresponding to the verification data is inconsistent with the access data marking result corresponding to the verification data, the verification data is used as the training data again, and the data decoding tree is updated.
4. A data access device, the device comprising:
the first acquisition unit is used for acquiring target data to be accessed;
the first determining unit is used for determining the analysis sequence and the product identification of the target data;
the first calling unit is used for calling a pre-constructed data decoding tree, decoding the analysis sequence and the product identifier of the target data and obtaining data in a standard data format corresponding to the target data;
the first determination unit includes:
a first determining subunit, configured to determine a data packet format corresponding to the target data;
the second determining subunit is used for determining a data packet analysis sequence and a product identifier corresponding to the target data according to the data packet format;
the apparatus further comprises:
the second acquisition unit is used for acquiring training data;
the second determining unit is used for determining the analysis sequence and the product identification of the training data;
and the training unit is used for training the initial data decoding tree according to the analysis sequence of the training data, the product identification and the access data label corresponding to the training data, and generating the data decoding tree.
5. The apparatus of claim 4, wherein the file composition structure of the initial data decoding tree is a JSON file structure.
6. The apparatus according to any one of claims 4 to 5, further comprising:
a third acquisition unit configured to acquire authentication data;
a third determining unit, configured to determine an analysis order and a product identifier of the verification data;
the second calling unit is used for calling the data decoding tree, decoding the analysis sequence and the product identifier of the verification data, and obtaining data in a standard data format corresponding to the verification data;
and the updating unit is used for re-using the verification data as the training data and updating the data decoding tree when the data in the standard data format corresponding to the verification data is inconsistent with the access data marking result corresponding to the verification data.
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