CN111124548A - Rule analysis method and system based on YAML file - Google Patents
Rule analysis method and system based on YAML file Download PDFInfo
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Abstract
The invention discloses a rule analysis method and a rule analysis system based on YAML (Yaml markup language) files, which belong to the technical field of rule analysis and comprise the following steps of S1: configuring a data source; s2: configuring data acquisition operation; s3: configuring YAML file rules; s4: the parsing rules collect data. According to the regular configuration of the YAML file, the program deployment only needs once, and the user can meet different data acquisition requirements only by modifying the configuration without deploying and modifying for many times; the new processing logic can be added in the program, other programs do not need to be modified, and the user can realize the customization requirement only by configuring the newly added logic key words and corresponding information during configuration, so that the flexibility of the program is greatly improved; YAML language is fast to learn, and compared with script language, the YAML language has the characteristics of easy writing, convenient configuration and convenient reading.
Description
Technical Field
The invention relates to the technical field of rule analysis, in particular to a rule analysis method and system based on YAML files.
Background
When the need of judging and selecting the next execution flow according to the configuration value occurs, the prior art is realized by using different methods under different scenes, namely hard coding. Some current systems also use rule parsing methods, but most of them are implemented using scripting languages such as groovy and JavaScript.
In the data acquisition system, according to different configured data sources, processing data are acquired according to different requirements and are written into configured target data sources. If the design of the editable rule is not available, the system is difficult to maintain, can only be applied to a certain fixed special scene, and is difficult to change and expand when new needs exist.
The prior art has certain defects, for example, when the system is modified complicatedly when different requirements are met, a program may need to be deployed for many times; when the requirement needs to be expanded to carry out customized development, the requirements cannot be realized, the difficulty is high, and the program reconstruction is complex; the script language learning cost is high, and a certain programming basis is needed for writing and reading, so that a rule analysis method and a rule analysis system based on YAML files are provided.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to solve the problems of complex system modification, difficult customized development and implementation, high script language learning cost and the like in the prior art, and provides a rule analysis method based on YAML files.
The invention solves the technical problems through the following technical scheme, and the invention comprises the following steps:
s1: configuring data sources
Configuring a data source, wherein the data source comprises a data source item (input item) and a data target source item (output item);
s2: configuring data acquisition operations
Configuring data acquisition operation, namely configuring the flow direction of data;
s3: configuring YAML document rules
Configuring and saving rules of the YAML file, wherein the configured content comprises rule content of configuration processing logic items (filters items) and information in the job configuration according to the step S2 to perfect the whole rule information;
s4: parsing rules to collect data
After the configuration is stored, acquiring flow information according to the completed rule analysis, and performing data acquisition by matching with the corresponding flow.
Further, in the step S1, the data source item and the data target item both support multiple data types, including JDBC, Hbase, ftp, hdfs, and kafka.
Further, in the step S1, the data source item is used to represent configuration information of the data source end, including connection login information and data source information of the data source library; the data target source item is used for representing the connection information of the data target end.
Further, in the step S3, the processing logic item is used to indicate the processing operation performed on the data after the data is read.
Further, the processing operations include operations of removing data, filtering null values, calculating, renaming, adding fields, and the like.
Further, in the step S3, the specific process of refining the whole rule information according to the information in the job configuration of the step S2 is as follows:
s31: acquiring data source names of a data source and a data target source selected by job configuration;
s32: acquiring connection information of each data source according to the name of the data source, such as information of a connection user name, a password and the like;
s33: and supplementing the acquired data source connection information into an input item of the rule, and supplementing the data target source connection information into an output item of the rule, namely completing the whole rule improvement process.
Further, in step S3, the processing logic item includes a plurality of keywords, a plurality of the keywords are designed and determined keywords, and a character string after the keywords stores target information, and the target information can be configured and modified according to actual design requirements.
Further, in the step S4, the rules that have been completed are parsed using the parsing engine of YAML.
Wherein, the YAML file conventional analysis engine is used, which belongs to the open source technology. The YAML file is parsed into class objects, such as MAP, or rule classes designed in the program, and in the present invention, the YAML file is parsed into classes designed in the program. The class comprises map type input and output, list type filters. After parsing into classes, attributes of the classes, such as input, output, and filters, may be obtained. According to the class attribute, specific input, output and filters information can be obtained. The acquisition process is the conventional map and list acquisition.
Furthermore, the process of matching the corresponding flow to perform data acquisition is as follows:
s41: according to the acquired collection process name, such as FTP, acquiring a matched process class name from a program cache (when the program is started, process information supported in the program is stored into the cache, wherein the information comprises the process name and a corresponding class name), wherein the acquired FTP process class name is com.usticinfo.ishare.bdp.transfer.api.Plugins.input.FTP;
s42: and creating a corresponding class entity according to the class name and executing the class.
The invention also provides a rule analysis system based on the YAML file, which comprises the following steps:
the data processing system comprises a first configuration module, a second configuration module and a third configuration module, wherein the first configuration module is used for configuring data source items, and the data source items comprise data source items and data target source items;
the second configuration module is used for configuring data acquisition operation, namely configuring the flow direction of data;
a third configuration module, configured and saved for configuring the rules of YAML file, the configured content includes the rule content of configuration processing logic items and the information in job configuration according to step S2 to complete the whole rule information;
the rule analysis module is used for acquiring acquisition process information according to the perfect rule analysis after the configuration is stored, and matching the corresponding process to perform data acquisition;
the central processing module is used for sending instructions to other modules to complete related actions;
the first configuration module, the second configuration module, the third configuration module and the rule analysis module are all electrically connected with the central processing module.
Compared with the prior art, the invention has the following advantages: according to the rule analysis method based on the YAML file, according to the rule configuration of the YAML file, the program deployment only needs one time, and the user only needs to modify the configuration to meet different data acquisition requirements without deploying for multiple times and modifying for multiple times; the new processing logic can be added in the program, other programs do not need to be modified, and the user can realize the customization requirement only by configuring the newly added logic key words and corresponding information during configuration, so that the flexibility of the program is greatly improved; YAML language learns fast, compares with the script language, has the characteristics of easy writing, convenient configuration and convenient reading, is worth being popularized and used.
Drawings
FIG. 1 is a schematic flow chart illustrating a rule parsing method according to an embodiment of the present invention;
FIG. 2 is a schematic interface diagram of a configuration data source according to a third embodiment of the present invention;
FIG. 3 is a schematic interface diagram of a configuration data collection operation according to a third embodiment of the present invention;
fig. 4 is a schematic interface diagram of configuring YAML file rules in the third embodiment of the present invention.
Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
Example one
As shown in fig. 1 to 4, the present embodiment provides a technical solution: a rule parsing method based on YAML files comprises the following steps:
s1: configuring data sources
Configuring a data source, wherein the data source comprises a data source item (input item) and a data target source item (output item);
s2: configuring data acquisition operations
Configuring data acquisition operation, namely configuring the flow direction of data;
s3: configuring YAML document rules
Configuring and saving rules of the YAML file, wherein the configured content comprises rule content of configuration processing logic items (filters items) and information in the job configuration according to the step S2 to perfect the whole rule information;
s4: parsing rules to collect data
After the configuration is stored, acquiring flow information according to the completed rule analysis, and performing data acquisition by matching with the corresponding flow.
In step S1, the data source item and the data target item both support multiple data types, including JDBC, Hbase, ftp, hdfs, and kafka.
In step S1, the data source item is used to represent configuration information of the data source end, including the connection registration information and the data source information of the data source library; the data target source item is used for representing the connection information of the data target end.
In step S3, the processing logic item is used to indicate the processing operation performed on the data after the data is read.
The processing operations include operations to remove data, null filtering, compute, rename, add fields, and so on.
In the step S3, the specific process of refining the whole rule information according to the information in the job configuration of the step S2 is as follows:
s31: acquiring data source names of a data source and a data target source selected by job configuration;
s32: acquiring connection information of each data source according to the name of the data source, such as information of a connection user name, a password and the like;
s33: and supplementing the acquired data source connection information into an input item of the rule, and supplementing the data target source connection information into an output item of the rule, namely completing the whole rule improvement process.
In step S3, the processing logic item includes a plurality of keywords, where the plurality of keywords are designed and determined keywords, and a character string after the keywords stores target information, and the target information may be configured and modified according to actual design requirements.
In step S4, the rules that have been completed are parsed using the parsing engine of YAML.
Wherein, the YAML file conventional analysis engine is used, which belongs to the open source technology. The YAML file is parsed into class objects, such as MAPs, or rule classes designed in the program, in this embodiment, into classes designed in the program. The class comprises map type input and output, list type filters. After parsing into classes, attributes of the classes, such as input, output, and filters, may be obtained. According to the class attribute, the specific information of input, output and filters can be obtained. The acquisition process is the conventional map and list acquisition.
In step S4, the process of matching the corresponding flow to perform data acquisition is as follows:
s41: according to the acquired collection process name, acquiring a matched process class name from a program cache (process information supported in the program is stored in the cache when the program is started, and the information comprises the process name and a corresponding class name);
s42: and creating a corresponding class entity according to the class name and executing the class.
The present embodiment further provides a rule parsing system based on YAML files, including:
the data processing system comprises a first configuration module, a second configuration module and a third configuration module, wherein the first configuration module is used for configuring data source items, and the data source items comprise data source items and data target source items;
the second configuration module is used for configuring data acquisition operation, namely configuring the flow direction of data;
a third configuration module, configured and saved for configuring the rules of YAML file, the configured content includes the rule content of configuration processing logic items and the information in job configuration according to step S2 to complete the whole rule information;
the rule analysis module is used for acquiring acquisition process information according to the perfect rule analysis after the configuration is stored, and matching the corresponding process to perform data acquisition;
the central processing module is used for sending instructions to other modules to complete related actions;
the first configuration module, the second configuration module, the third configuration module and the rule analysis module are all electrically connected with the central processing module.
Example two
In order to flexibly match corresponding program flows to perform data acquisition and processing according to configuration data, so that the system can be flexibly applied to multiple scenes, the embodiment provides the following technical scheme:
1. rule files based on the following YAML format:
2. description of the rules
The Input is used for representing configuration information of a data source end and describing connection login information and data source information of a data source library. And after the program is analyzed, connecting a data source according to the information of the input and reading the data. The Input supports various data sources, such as JDBC, Hbase, ftp, hdfs, kafka, and other data sources. The YAML file example only displays JDBC, and can be modified into other data source information according to the scene requirement;
filters are used for processing data after the program reads the data. The configuration includes operations of removing data, filtering null values, calculating, renaming, adding fields, and the like. After the data is read, the data is processed item by item according to the configured filters rule, and which processing operation is configured to perform which processing. The program can be realized by the user through self configuration according to the requirement under the condition of supporting various operation;
output is similar to input and is used for describing the connection information of the data target end. And after program analysis, connecting a target source according to configuration information of output to write the processed data into the target source, so as to realize the collection and processing work of the whole data. Data sources such as JDBC, Hbase, ftp, hdfs, kafka and the like are also supported in output, and configuration can be performed according to an actual scene;
the flag key field in the rule is programmed, and it is understood that the key preceding the colon is the key that has been already determined by design. Different keywords represent different meanings. For example, JDBC expresses the JDBC connection, and remove in filters expresses the meaning of removing a field. The information user behind the keyword can carry out configuration modification according to actual design requirements.
The manner in which the configuration modification is made includes, but is not limited to, the following:
1) the rules can be directly edited in an editing frame of the interface configuration to modify and configure;
2) the developer can develop rules according to actual requirements, for example, the time format of 20191230 needs to be converted into the format of 2019-12-30, the development needs to acquire column names needing to be converted and the time format of the target, and the information of the converted column names and the target time format needs to be provided when the rules are edited on the interface.
3. Rule parsing
After YAML format rules are configured, the program reads the rules, and analyzes the rules by using an analysis engine of YAML to obtain three important information of a data source, processing logic and a data source target source, and matches the information obtained after analysis to a corresponding program flow for execution. For example, the data source read data needing to be connected with JDBC is acquired, namely the program is connected with the JDBC data source, and if the data source is an FTP data source, the program is connected with FTP. The same is performed on the processing logic and the target source according to the acquired configuration information matching program flow. And finally, acquiring the data to a target end according to a processing flow designed by the user.
The process of matching the corresponding flow to perform data acquisition is as follows:
1) acquiring a matched flow class name from a program cache (flow information supported in a program is stored in the cache when the program is started, wherein the information comprises the flow name and a corresponding class name) according to an acquired collection flow name, such as FTP (file transfer protocol), wherein the acquired FTP flow class name is com.usticinfo.ishare.bdp.transfer.api.Plugins.input.FTP;
2) and creating a corresponding class entity according to the class name and executing the class.
EXAMPLE III
The embodiment provides a rule parsing method based on a YAML file, which includes the following specific implementation steps:
1. configuring data sources
The configured data source comprises a data source and a data target source and supports various data types;
2. configuring data acquisition operations
Configuration data collection operation, namely the flow trend of where the configuration data goes from;
3. configuring YAML rules
The method comprises the steps of configuring collection rules, wherein the configured rules mainly configure rule contents of filters, input and output without special requirement keywords do not need to be listed during page configuration, a program can automatically complete the information of the whole rule according to information in previous job configuration, for example, in the figure 4, no content exists behind the input keywords, and the fact that the datatype keyword value is CSV is displayed behind the output keywords, namely, the existing information in the job configuration can be displayed or not displayed during configuration, and the program can judge to be complete.
The specific process of judging perfection is as follows:
1) after the program obtains the rule, the rule is analyzed into a rule class;
2) after analyzing the attribute of the rule class, respectively acquiring the values of input and output;
3) and judging whether the data source information is empty or not according to the acquired value, if so, judging that no information exists, and needing to be supplemented and perfected according to the information configured by the job, if not, continuously judging whether the data source related information exists, designing sourceInfo representing the data source information in the rule, and if not, supplementing.
4. Parsing rules to collect data
After the configuration is stored, the acquisition program is started, and the program analyzes and acquires acquisition flow information according to the completed rule and matches different flows to perform data acquisition.
The main key interpretation table in the rule is as follows:
TABLE 1 Key interpretation Table
In summary, in the rule parsing method based on the YAML file in the three groups of embodiments, according to the rule configuration of the YAML file, the program deployment only needs to be performed once, and the user only needs to modify the configuration to meet different data acquisition requirements without deploying and modifying for many times; a new processing logic can be added in the program, other programs do not need to be modified, and a user can realize the customization requirement only by configuring a newly added logic key word and corresponding information (the corresponding information refers to parameter information required in the operation process corresponding to the key word, such as split operation in a rule, field-split field names, sep-split separators and index-split acquired data subscripts which need to be determined) during configuration, so that the flexibility of the program is greatly improved; YAML language is fast to learn, compared with script language, it has the features of easy to write, convenient to configure and easy to read, and is worth being popularized and used.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A rule parsing method based on YAML files is characterized by comprising the following steps:
s1: configuring data sources
Configuring a data source, wherein the data source comprises a data source item and a data target source item;
s2: configuring data acquisition operations
Configuring data acquisition operation, namely configuring the flow direction of data;
s3: configuring YAML document rules
Configuring and saving rules of the YAML file, wherein the configured content comprises the rule content of the configuration processing logic items and the information in the job configuration according to the step S2 to perfect the whole rule information;
s4: parsing rules to collect data
After the configuration is stored, acquiring flow information according to the completed rule analysis, and performing data acquisition by matching with the corresponding flow.
2. The YAML file-based rule parsing method as claimed in claim 1, wherein: in step S1, the data source item and the data target item both support multiple data types, including JDBC, Hbase, ftp, hdfs, and kafka.
3. The YAML file-based rule parsing method as claimed in claim 1, wherein: in step S1, the data source item is used to represent configuration information of the data source end, including connection login information and data source information of the data source library; the data target source item is used for representing the connection information of the data target end.
4. The YAML file-based rule parsing method as claimed in claim 1, wherein: in step S3, the processing logic item is used to indicate the processing operation performed on the data after the data is read.
5. The YAML file-based rule parsing method of claim 4, wherein: the processing operations include removing data, null filtering, calculating, renaming, adding fields.
6. The YAML file-based rule parsing method as claimed in claim 1, wherein: in step S3, the processing logic item includes a plurality of keywords, where the plurality of keywords are designed and determined keywords, and a character string after the keywords stores target information, and the target information may be configured and modified according to actual design requirements.
7. The YAML file-based rule parsing method as claimed in claim 1, wherein: in the step S3, the specific process of refining the whole rule information according to the information in the job configuration of the step S2 is as follows:
s31: acquiring data source names of a data source and a data target source selected by job configuration;
s32: acquiring connection information of each data source according to the data source name;
s33: and supplementing the acquired data source connection information into an input item of the rule, and supplementing the data target source connection information into an output item of the rule, namely completing the whole rule improvement process.
8. The YAML file-based rule parsing method as claimed in claim 1, wherein: in step S4, the rules that have been completed are parsed using the parsing engine of YAML.
9. The YAML file-based rule parsing method of claim 1, wherein in the step S4, the process of matching the corresponding flow to perform data collection comprises the following steps:
s41: acquiring a matched process class name according to the acquired collection process name;
s42: and creating a corresponding class entity according to the class name and executing the class.
10. A rule parsing system based on YAML files, which is characterized in that the rule parsing work is carried out by the rule parsing method according to any one of claims 1 to 9, and comprises the following steps:
the data processing system comprises a first configuration module, a second configuration module and a third configuration module, wherein the first configuration module is used for configuring data source items, and the data source items comprise data source items and data target source items;
the second configuration module is used for configuring data acquisition operation;
a third configuration module, configured and stored with the rules of YAML file, the configured content includes the rule content of configuration processing logic items and the information in job configuration according to step S2 to complete the whole rule information;
the rule analysis module is used for acquiring acquisition process information according to the perfect rule analysis after the configuration is stored, and performing data acquisition by matching with a corresponding process;
the central processing module is used for sending instructions to other modules to complete related actions;
the first configuration module, the second configuration module, the third configuration module and the rule analysis module are all electrically connected with the central processing module.
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