Developing a custom parser module


A parser is a class that extends the Parser class in BMC Helix Continuous Optimization. For the parser to produce data, you need to implement the abstract parse method. 

About the abstract parse method

 After you implement the abstract parse method, the parser receives the full name (of the file to parse) as the first parameter and returns a DataSetList object containing data that has been extracted.

The parser does not find and select files to parse. The ETL framework does this task in advance as per the configuration present during the creation of the ETL.

For instance, the ETL is configured to access a Secure File Transfer Protocol (SFTP) folder and select files that match a certain pattern. The ETL framework copies the selected files via SFTP to the local ETL engine disk and then, it sequentially calls the parse method of the defined custom parser for each file. This means that the ETL will:

  1. Call the parse method for the first file.
  2. Populate the output dataset with the result.
  3. Call the parse method for the second file.
  4. Append the result to the dataset, and so on.
    After parsing each file and depending on configuration, the ETL framework will rename or move the parsed file.

Consider the following example:

Example

You need to extract the CPU Utilization metric from a text file in the following format:

2023-07-07/CPU:15.2,13,25,15,13,25,15.1,13,25.1,15.1,13,25,15,13,25
2023-07-07/DISK:1,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1
2023-07-08/CPU:15,13,25,15,13,25,15,13,25,15,13,25,15,13,25,15,13,25
2023-07-08/DISK:1,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2,1
.. ..
..

The contents of this file are not columnar; each row has different metrics and contains hourly samples from a 24-hour day. To parse a file in this format, you need to use a custom parser.

Full example code

You can download the full code of the example presented: MyParserP.pm.


 

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