I am not sure if you really need a keyby, your load will be distributed among your map function without it. But could you explain a bit what is your sink doing?
As for setting parallelism on the consumer remember that you wont have higher parallelism than number of partitions in your topic. If you have 240 partitions that's fine, but if you have less than other subtasks will be idle. Only one task can read from one partition in parallel. On Tue, Apr 18, 2017 at 3:38 PM Telco Phone <[email protected]> wrote: > > I am trying to use the task number as a keyby value to help fan out the > work load reading from kafka. > > > Given: > > DataStream<SchemaRecord> stream = > env.addSource(new > FlinkKafkaConsumer010<SchemaRecord>("topicA", schema, properties) > ).setParallelism(240).flatMap(new > SchemaRecordSplit()).setParallelism(240). > name("TopicA splitter").keyBy("partition", > "keyByHelper", "schemaId"); > > stream.addSink(new CustomMaprFsSink()).name("TopicA > Sink").setParallelism(240); > > > In the DeserialClass I am trying to get to the > > getRuntimeContext().getIndexOfThisSubtask(); > > Which is only avaliable in the RichSinkFunction > > > > The above is partition (by hour) , schemaID (avro schemaId) and I would > like to add the task number so that all 240 readers / writers have > something to do. > > Any ideas ? > > > >
