Table of Contents

Search

  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. B2B transformation
  7. Aggregator transformation
  8. Cleanse transformation
  9. Data Masking transformation
  10. Data Services transformation
  11. Deduplicate transformation
  12. Expression transformation
  13. Filter transformation
  14. Hierarchy Builder transformation
  15. Hierarchy Parser transformation
  16. Hierarchy Processor transformation
  17. Input transformation
  18. Java transformation
  19. Java transformation API reference
  20. Joiner transformation
  21. Labeler transformation
  22. Lookup transformation
  23. Machine Learning transformation
  24. Mapplet transformation
  25. Normalizer transformation
  26. Output transformation
  27. Parse transformation
  28. Python transformation
  29. Rank transformation
  30. Router transformation
  31. Rule Specification transformation
  32. Sequence Generator transformation
  33. Sorter transformation
  34. SQL transformation
  35. Structure Parser transformation
  36. Transaction Control transformation
  37. Union transformation
  38. Velocity transformation
  39. Verifier transformation
  40. Web Services transformation

Transformations

Transformations

Structure Parser transformation example

Structure Parser transformation example

You need to parse the unstructured data in a log file and write the data to a target file in relational format.
You need to configure an
intelligent structure model
that analyzes unstructured data and discovers its structure.
The following image shows the log file that you want to parse:
The log file shows the log lines in unstructured format.
Create the
intelligent structure model
in Informatica Cloud. The following image shows the
intelligent structure model
details:
The structure definition details show the properties of the NodeLog structure definition, such as the description, structure definition model, user name, time of creation of the structure definition, and the list of output fields in the structure definition.
To parse the log file, use a Structure Parser transformation in a mapping to transform the data in the log file.
In the Mapping Designer, you add a source object that is flat file that contains the path to the log file you want to parse.
The following image shows the selected source file properties:
The source object details show the the connection, type of source, and the input file.
You add a Structure Parser transformation. Configure it to use the
intelligent structure model
that you configured. Select the relational output type.
You connect the source object to the Structure Parser transformation. To map the incoming data to the fields of the transformation, select the Structure Parser transformation. In the
Field Mapping
tab, map
Path
to the Structure Parser Input Fields
Field Path
.
The following image shows the field mapping:
The Field Mapping tab shows the incoming fields that you can map to the Structure Parser input fields.
Add a text file target transformation for the parsed output group that you want to process named TargetFile. Add a separate text file target transformation for data that was not identified named Unidentified.
The following image shows the mapping:
The mapping shows the data flow from the SourceLogFile source to a Structure Parser transformation with name LogParser. The Structure Parser transformations is linked to the TargetFile target.
Run the mapping to write the data in a structured format to the TargetFile transformation. The mapping sends any data that was not identified by the intelligent structure to the Unidentified transformation.
The following image shows the parsed data output file from the TargetFile transformation:
The output file shows the log lines in structured format.
If you need to further parse the data, you can include additional Structure Parser transformations midstream that will parse the output from the preceding parser.

0 COMMENTS

We’d like to hear from you!