CN111124548B - 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 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 rule configuration of the YAML file, the program deployment is only needed once, and a user can meet different data acquisition requirements by only modifying the configuration without deploying and modifying for many times; new processing logic can be added in the program, other programs are not required to be modified, and a user can realize customization requirements by configuring the newly added logic keywords and corresponding information only during configuration, so that the flexibility of the program is greatly improved; the YAML language has the characteristics of quick learning, easy writing, convenient configuration and convenient reading compared with the script language.
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 to determine to select the next execution flow according to the configuration value occurs, the existing technology is implemented by using different methods under different scenes, namely hard coding. Some systems currently use rule parsing, but most of them are implemented using a scripting language such as groovy, javaScript.
In the data acquisition system, the data are acquired and processed according to different configured data sources and different requirements, and the processed data are written into the configured target data sources. If there is no design of editable rules, the system is difficult to maintain, and can only be applied to a certain fixed special scene, and when new needs exist, the system is difficult to change and expand.
Certain defects exist in the prior art, such as complex system modification when corresponding to different requirements, and multiple program deployment may be needed; when the requirement expansion is required to be subjected to customized development, the development is not realized, the difficult implementation is not realized, and the program transformation is complex; the script language has high learning cost and needs a certain programming basis to write and read, so a rule analysis method and a rule analysis system based on YAML files are provided.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to solve the problems of complex system modification, difficulty in customized development and implementation, high script language learning cost and the like in the prior art, and provides a rule analysis method based on a YAML file.
The invention solves the technical problems through the following technical proposal, and the invention comprises the following steps:
s1: configuring a data source
Configuring a data source, wherein the data source comprises a data source item (input item) and a data target source item (output item);
s2: configuration data acquisition operation
Configuring data acquisition operation, namely configuring the flow trend of data;
s3: configuring YAML file rules
Configuring and storing rules of the YAML file, wherein the configured content comprises rule content of configuration processing logic items (files items) and complete rule information according to information in the job configuration of the step S2;
s4: analyzing rule acquisition data
After the configuration is saved, acquiring the information of the acquisition flow according to the perfected rule analysis, and executing data acquisition by matching with the corresponding flow.
Further, in the step S1, the data source item and the data target source item each support multiple data types, including JDBC, hbase, ftp, hdfs, kafka.
Further, in the step S1, the data source item is used for representing 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 connection information of the data target end.
Further, in the step S3, the processing logic is used to represent the processing operation performed on the data after the data is read.
Still further, the processing operations include operations of removing data, null filtering, computing, renaming, adding fields, and the like.
Further, in the step S3, the specific process of perfecting the whole rule information according to the information in the job configuration in the step S2 is as follows:
s31: acquiring data source names of data sources and data target sources selected by operation configuration;
s32: acquiring connection information of each data source, such as connection user name, password and the like, 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, so that the whole rule perfecting process is completed.
Further, in the step S3, the processing logic item includes a plurality of keywords, where the keywords are designed and determined keywords, and the character strings after the keywords store target information, where the target information may be configured and modified according to actual design requirements.
Further, in the step S4, the parsing engine using YAML parses the completed rule.
The YAML file analysis method uses a conventional analysis engine of the YAML file, and belongs to an open source technology. The YAML file is parsed according to the YAML parsing technology of an open source, and can be parsed into class objects, such as MAP, or rule classes designed in a program, and is parsed into the classes designed in the program in the invention. The class includes input and output of map type, filters of list type. After parsing into classes, attributes of the classes, such as input, output, filters, may be obtained. From the class attributes, specific input, output, filters information can be obtained. The acquisition process is conventional map and list acquisition.
Further, the process of executing data collection by matching the corresponding flow is as follows:
s41: according to the acquired acquisition flow names, such as FTP, the matched flow class names are acquired from a program cache (flow information supported in the program is stored in the cache when the program is started, the information comprises the flow names and corresponding class names), and the acquired FTP flow class names are com.ustcinfo.ishare.bdp.transfer.api.plug.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 first configuration module is used for configuring data source items, wherein the data source items comprise data source items and data target source items;
the second configuration module is used for configuring the data acquisition operation, namely configuring the flow trend of the data;
the third configuration module is used for configuring and storing rules of the YAML file, wherein the configured content comprises rule content for configuring a processing logic item and perfecting whole rule information according to information in the operation configuration in the step S2;
the rule analysis module is used for analyzing and acquiring the information of the acquisition flow according to the completed rule after the storage configuration, and matching the acquired information with the corresponding flow to execute 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 rule configuration of the YAML file, program deployment is only needed once, a user only needs to carry out configuration modification to meet different data acquisition requirements, and repeated deployment and repeated modification are not needed; new processing logic can be added in the program, other programs are not required to be modified, and a user can realize customization requirements by configuring the newly added logic keywords and corresponding information only during configuration, so that the flexibility of the program is greatly improved; compared with the script language, the YAML language has the characteristics of easy writing, convenient configuration and convenient reading, and is worth popularizing and using.
Drawings
FIG. 1 is a flow chart of a rule parsing method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an interface for configuring a data source in a third embodiment of the present invention;
FIG. 3 is a schematic diagram of an interface for configuring data collection operations in a third embodiment of the present invention;
FIG. 4 is a schematic diagram of an interface for configuring YAML file rules in a third embodiment of the present invention.
Detailed Description
The following describes in detail the examples of the present invention, which are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of protection of the present invention is not limited to the following examples.
Example 1
As shown in fig. 1 to 4, the present embodiment provides a technical solution: a rule parsing method based on YAML file includes the following steps:
s1: configuring a data source
Configuring a data source, wherein the data source comprises a data source item (input item) and a data target source item (output item);
s2: configuration data acquisition operation
Configuring data acquisition operation, namely configuring the flow trend of data;
s3: configuring YAML file rules
Configuring and storing rules of the YAML file, wherein the configured content comprises rule content of configuration processing logic items (files items) and complete rule information according to information in the job configuration of the step S2;
s4: analyzing rule acquisition data
After the configuration is saved, acquiring the information of the acquisition flow according to the perfected rule analysis, and executing data acquisition by matching with the corresponding flow.
In the step S1, the data source item and the data target source item each support multiple data types, including JDBC, hbase, ftp, hdfs, kafka.
In the step S1, the data source item is used for representing 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 connection information of the data target end.
In the step S3, the processing logic is used to represent the processing operation performed on the data after the data is read.
The processing operations include operations of removing data, null filtering, calculating, renaming, adding fields, and the like.
In the step S3, the specific process of perfecting the whole rule information according to the information in the job configuration in the step S2 is as follows:
s31: acquiring data source names of data sources and data target sources selected by operation configuration;
s32: acquiring connection information of each data source, such as connection user name, password and the like, 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, so that the whole rule perfecting process is completed.
In the step S3, the processing logic item includes a plurality of keywords, where the keywords are designed and determined keywords, and the character strings after the keywords store target information, where the target information may be configured and modified according to actual design requirements.
In the step S4, the parsing engine using YAML parses the already perfected rule.
The YAML file analysis method uses a conventional analysis engine of the YAML file, and belongs to an open source technology. The YAML file is parsed according to the YAML parsing technique of an open source, and can be parsed into class objects, such as MAP, or rule classes designed in the program, in this embodiment into classes designed in the program. The class includes input and output of map type, filters of list type. After parsing into classes, attributes of the classes, such as input, output, filters, may be obtained. From the class attributes, specific input, output, filters information can be obtained. The acquisition process is conventional map and list acquisition.
In the step S4, the process of executing data acquisition by matching the corresponding flow is as follows:
s41: acquiring a matched flow class name from a program cache (flow information supported in the program is stored in the cache when the program is started, and the information comprises the flow name and a corresponding class name) according to the acquired flow name;
s42: and creating a corresponding class entity according to the class name and executing the class.
The embodiment also provides a rule parsing system based on the YAML file, which comprises the following steps:
the first configuration module is used for configuring data source items, wherein the data source items comprise data source items and data target source items;
the second configuration module is used for configuring the data acquisition operation, namely configuring the flow trend of the data;
the third configuration module is used for configuring and storing rules of the YAML file, wherein the configured content comprises rule content for configuring a processing logic item and perfecting whole rule information according to information in the operation configuration in the step S2;
the rule analysis module is used for analyzing and acquiring the information of the acquisition flow according to the completed rule after the storage configuration, and matching the acquired information with the corresponding flow to execute 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 perform data acquisition processing according to configuration data and matching corresponding program flows, the system can be flexibly applied to multiple scenes, and the embodiment provides the following technical scheme:
1. rule files based on the following YAML format:
2. rule description
The Input is used for representing configuration information of the data source end, and describes connection login information and data source information of the data source library. And after program analysis, connecting a data source according to the input information and reading data. The Input support includes a variety of data sources, such as JDBC, hbase, ftp, hdfs, kafka. Only JDBC is shown in the YAML file example, and the JDBC can be modified into other data source information according to scene requirements;
filters are used to process 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 operations are configured, namely which processing is performed. The method enables the program to be realized by the user by configuring the program according to the needs under the condition of supporting various operations;
output, similar to input, is used to describe connection information of the data destination. After program analysis, the target source is connected according to the configuration information of output to write the processed data, so that the whole data acquisition and processing work is realized. Data sources such as JDBC, hbase, ftp, hdfs, kafka are supported in the output as well, and can be configured according to actual scenes;
the flag key field in the rule is designed in the program, and it is understood that the key preceding the colon is the key that has been designed and determined. Different keywords represent different meanings. For example, JDBC expresses that is a JDBC connection, remove in filters expresses the meaning of the remove field. The information user after the keywords can be configured and modified according to the actual design requirements.
The manner in which the configuration modification is made includes, but is not limited to, the following:
1) The rule can be edited in the editing frame of the interface configuration directly to modify the configuration;
2) The developer can develop the rule according to the actual requirement, for example, the time format of 20191230 needs to be converted into the format of 2019-12-30, the time format of the column names and targets needs to be obtained, and the information of the column names and the target time formats needs to be provided when the rule is edited by the interface.
3. Rule parsing
After the YAML format rule is configured, the program reads the rule, uses the analysis engine of the YAML to analyze the rule, obtains three important information of a data source, processing logic and a data source target source, and matches the information obtained after analysis to the corresponding program flow for execution. For example, the data source read data which needs to be connected with the JDBC is acquired, the program is connected with the JDBC data source, and if the data source is the FTP data source, the program is connected with the FTP. Matching program flow execution is also performed on the processing logic and the target source based on the acquired configuration information. Finally, the data are collected to the target end according to the processing flow designed by the user.
The process of executing data acquisition by matching the corresponding flow is as follows:
1) According to the acquired acquisition flow names, such as FTP, the matched flow class names are acquired from a program cache (flow information supported in the program is stored in the cache when the program is started, the information comprises the flow names and corresponding class names), and the acquired FTP flow class names are com.ustcinfo.ishare.bdp.transfer.api.plug.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 analysis method based on YAML files, which comprises the following specific implementation steps:
1. configuring a data source
The configured data sources comprise data sources and data target sources, and support multiple data types;
2. configuration data acquisition operation
Configuration data collection jobs, i.e., flow trends from where configuration data is to be located;
3. configuring YAML rules
The acquisition rules are configured, the configured rules mainly configure rule contents of filters, for input and output without special requirement keywords, the program can automatically perfect the whole rule information according to the information in the previous operation configuration, for example, in fig. 4, the input keywords have no contents, the output keywords display dateType keywords with CSV values, that is, the information in the operation configuration can be displayed or not displayed, and the program can judge perfect.
The specific judging and perfecting process is as follows:
1) Resolving the rules into rule classes after the program acquires the rules;
2) Respectively obtaining the values of input and output after analyzing the attributes of the rule class;
3) Judging whether the data source information is empty or not according to the acquired value, if so, no information is needed, supplementing and perfecting according to the information of the operation configuration, if not, continuously judging whether the data source information is relevant information, designing the data source information as sourceInfo in the rule, and if not, supplementing.
4. Analyzing rule acquisition data
After the configuration is saved, an acquisition program is started, the program analyzes and acquires acquisition flow information according to the perfected rule, and the acquisition program is matched with different flows to execute data acquisition.
The main key interpretation table in the rules is as follows:
TABLE 1 keyword interpretation Table
In summary, according to the rule parsing method based on the YAML file in the three sets of embodiments, according to rule configuration of the YAML file, program deployment only needs to be performed once, and a user only needs to perform configuration modification to realize meeting different data acquisition requirements, so that multiple deployment and multiple modification are not needed; new processing logic can be added in the program, other programs are not required to be modified, and a user only needs to configure the newly added logic keywords and corresponding information (corresponding information refers to parameter information required in the operation process corresponding to the keywords, such as split operation in a rule, field names of field-split, sep-split separators and data subscripts acquired after index-split) in configuration so as to realize customization requirements, so that the flexibility of the program is greatly improved; compared with the script language, the YAML language has the characteristics of easy writing, convenient configuration and convenient reading, and is worth popularizing and using.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means 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 present invention. In this specification, schematic representations of the above terms are not necessarily directed 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, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (2)
1. The rule analysis method based on the YAML file is characterized by comprising the following steps of:
s1: configuring a data source
Configuring a data source, wherein the data source comprises a data source item and a data target source item;
s2: configuration data acquisition operation
Configuring data acquisition operation, namely configuring the flow trend of data;
s3: configuring YAML file rules
Configuring and storing rules of the YAML file, wherein the configured content comprises rule content for configuring a processing logic item and perfecting whole rule information according to information in the operation configuration of the step S2;
s4: analyzing rule acquisition data
After the configuration is saved, acquiring acquisition flow information according to the perfected rule analysis, and executing data acquisition by matching with the corresponding flow;
in the step S1, the data source item and the data target source item each support multiple data types, where the multiple data types include JDBC, hbase, ftp, hdfs, kafka;
in the step S1, the data source item is used for representing 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 connection information of the data target end;
in the step S3, the processing logic item is used to represent a processing operation performed on the data after the data is read, where the processing operation includes removing the data, filtering null values, calculating, renaming, and adding fields;
in the step S3, the processing logic item includes a plurality of keywords, where the keywords are designed and determined keywords, and the character strings after the keywords store target information, where the target information is configured and modified according to actual design requirements;
in the step S3, the specific process of perfecting the whole rule information according to the information in the job configuration in the step S2 is as follows:
s31: acquiring data source names of data sources and data target sources selected by operation configuration;
s32: acquiring connection information of each data source according to the name of the data source;
s33: the acquired data source connection information is supplemented to the input item of the rule, and the data target source connection information is supplemented to the output item of the rule, so that the whole rule perfecting process is completed;
in the step S4, parsing engine using YAML parses the completed rule;
in the step S4, the process of executing data collection by matching the corresponding flow includes the following steps:
s41: acquiring a matched process class name according to the acquired acquisition process name;
s42: and creating a corresponding class entity according to the class name and executing the class.
2. A YAML file-based rule parsing system, wherein the rule parsing work is performed using the rule parsing method of claim 1, comprising:
the first configuration module is used for configuring data source items, wherein the data source items comprise data source items and data target source items;
the second configuration module is used for configuring the data acquisition operation;
the third configuration module is used for configuring and storing rules of the YAML file, wherein the configured content comprises rule content for configuring a processing logic item and perfecting whole rule information according to information in the operation configuration in the step S2;
the rule analysis module is used for analyzing and acquiring the information of the acquisition flow according to the completed rule after the storage configuration, and matching the acquired information with the corresponding flow to execute 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.
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