I have the following: Source - kafka topic (trans) Channel - memory Sink - Hdfs (avro_event)
The data in the kafka topic trans has been written using a c# producer and has thousands of avro records. When I run my flume consumer, it starts to sink the data to the hdfs. The problem is that the data is in the format: schema data schema data
instead of:
schema data data
I am guessing this is because flume is expecting a record type with {header} {body} whereas the data coming from kafka will just be {body} I know there is a way you can wrap the avro data been written to the topic in an avroFlumeEvent but then it seems that it is no longer a true avro record and maybe a spark consumer or storm will prefer the data in true avro down the line. Is there a way to process this topic so the data is written without multiple schemas everytime flume rolls the data to hdfs?