I did as you suggested Matt and attacked the problem with Groovy. Since I'm
stronger at manipulating json than csv using Groovy, I first converted the
incoming to json using a ConverRecord processor. I inferred the record
schema from the header assumed in the incoming csv. (still tbd: how I will
Thanks very much for your reply, Matt. Yes sir, a Groovy script is my
fallback option. Because we would rather build flows using "out of the NiFi
box" processors instead of custom scripts that may need to be maintained, I
was saving that as my last resort. But I do believe I can do it with Groovy.
I should mention for aggregate values like COUNT(), check out the
CalculateRecordStats processor, not sure if it takes a `/` value (or
whatever means 'select all fields') for a RecordPath or not, if not we
should probably support if prudent. It might also be a nice
improvement to add MAX/MIN
Jim,
QueryRecord uses Apache Calcite under the hood and is thus at the
mercy of the SQL standard (and any additional rules/dialect from
Apache Calcite) so in general you can't select "all except X" or "all
except change X to Y". Does it need to be SQL executed against the
individual fields? If
Hello. I recently asked the community a question about processing CSV
files. I received some helpful advice about using processors such as
ConvertRecord and QueryRecord, and was encouraged to employ Readers and
RecordSetWriters. I've done that, and thank all who replied.
My incoming CSV files
