Custom Analyzer

By Ashwin Venugopal -

 




Create a Custom Analyzer

When you define the index, you provide a custom analyzer. The Azure site does not allow you to define a custom index, instead, you must use JSON code.

During the design phase, make use of the index's analyzers section. One tokenizer, one or more character filters, and one or more token filters may be included.

Use a unique name for your analyzer and set the @odata.type property to Microsoft.Azure.Search.CustomAnalyzer.

Test Custom Analyzer

You can utilize the REST API's Analyze Text function after defining your custom analyzer as part of your index.

To submit test text and make sure the analyzer returns tokens appropriately, use the text function. Create these queries using any REST testing tool, like the well-known Postman program.

Be sure to test with lots of different text values until you're sure that the custom analyzer behaves as you expect.

Use a Custom Analyzer For a Field

You can set up your index to utilize a custom analyzer once you've defined and tested it. For every field in your index, you can designate an analyst.

If you wish to utilize the same analyzer for both indexing and searching, you can use the analyzer field. It's also possible to use a different analyzer when indexing the field and when searching the field.

Enhance an Index To Include Multiple Languages

A search index can be made multilingual. By supplying all of the translated text fields in each of the languages you wish to support, you can manually add language support.

Another option is to employ Azure AI Services to deliver translated text via an enrichment pipeline.

Conclusion

We have successfully learnt about custom analyzer.






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