datasherlock commented on PR #101:
URL: https://github.com/apache/bahir/pull/101#issuecomment-1416768410

   The backpressure implementation seems buggy. My understanding is that the 
backpressure mechanism will control the input rate but never exceed the 
`spark.streaming.receiver.maxRate`. But this doesn't seem to be honoured since 
we're noticing that the receiver input rate breaches the 
`spark.streaming.receiver.maxRate` every now and then and tends to put a lot of 
pressure on the pipeline. 
   
   Context - I created a Spark Scala app with 900 receivers, 
`spark.streaming.receiver.maxRate=1500` and `batchInterval=60s`. My 
understanding is that the total number of records per batch should not be 
greater than `900*1500*60 = 81,000,000 records`. But I am noticing that some 
batches are going as high as 776,732,455 records where the `processing time is 
>>> batchInterval`


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