Shawn, Your schema indicates that the fields are optional because of the "type" : ["null", "string"] , so IIRC they won't be marked as invalid because they are treated as null (I'm not sure there's a difference in the code between missing and null fields).
You can try "type": "string" in ValidateRecord to see if that fixes it, or there's a "StrNotNullOrEmpty" operator in ValidateCSV. Regards, Matt On Mon, Jan 6, 2020 at 4:35 PM Shawn Weeks <[email protected]> wrote: > > I’m trying to validate that a csv file has the number of fields defined in > it’s Avro schema. Consider the following schema and CSVs. I would like to be > able to reject the invalid csv as missing fields. > > > > { > > "type" : "record", > > "namespace" : "nifi", > > "name" : "nifi", > > "fields" : [ > > { "name" : "c1" , "type" : ["null", "string"] }, > > { "name" : "c2" , "type" : ["null", "string"] }, > > { "name" : "c3" , "type" : ["null", "string"] } > > ] > > } > > > > Good CSV > > c1,c2,c3 > > hello,world,1 > > hello,world, > > hello,, > > > > Bad CSV > > c1,c2,c3 > > hello,world,1 > > hello,world > > hello > >
