Projections Of Data

By Ashwin Venugopal -

 





Define Projections

The document structures produced by your indexing process' enrichment pipeline serve as the foundation for the data projections that will be kept in your knowledge store. You can save part or all of the document's fields as projections, and each skill in your skill set successively creates a JSON representation of the enriched data for the pages being indexed.

Using The Shaper Skill

A complex document including the different output fields from the abilities in the skillset is produced by the incremental indexing procedure. This may lead to a schema that is challenging to deal with and contains collections of primitive data values that are difficult to translate into well-formed JSON.

Using the Shaper skill to construct a new field with a simpler structure for the fields you wish to map to projections is a typical way to make the mapping of these field values to projections in a knowledge store easier.

Define Knowledge Store

You must establish a knowledgeStore object in the skillset with the Azure Storage connection string for the storage account where you wish to build projections as well as the definitions of the projections themselves in order to define the knowledge store and the projections you wish to create in it.

Depending on what you want to store, you can construct object projections, table projections, and file projections. However, keep in mind that even if each projection comprises lists for tables, objects, and files, you still need to define a distinct projection for each type of projection.

Only one of the projection type lists can be filled since projection types are mutually exclusive in a projection definition. You have to make a projection for each of the three types if you create them.

If the designated container does not already exist, it will be constructed for object and file projections. For every table projection, an Azure Storage table containing the mapped fields and a unique key field with the name given in the generatedKeyName attribute will be created. Relational joins between the tables for analysis and reporting can be defined using these important attributes.

Conclusion

We have successfully learnt about projections and knowledge store.












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