[GitHub] [spark] HyukjinKwon edited a comment on issue #24724: User friendly dataset, dataframe generation for csv datasources without explicit StructType definitions.

[GitBox <gi...@apache.org>]

HyukjinKwon edited a comment on issue #24724: User friendly dataset, dataframe generation for csv datasources without explicit StructType definitions.
URL: https://github.com/apache/spark/pull/24724#issuecomment-496446607
 
 
   Why don't we just call
   
   ```scala
   import org.apache.spark.sql.Encoders
   val schema = Encoders.product[Person].schema
   spark.read.schema(schema).csv("/tmp/csv").as[Person]
   ```
   
   ?
   
   Once we allow, we have to consider allowing this all the ways. `createDataFrame`, `from_json`, `DataFrame[Stream]Reader.schema`, UDFs, etc. Is this something really worthy?

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