Github user Tagar commented on the issue: https://github.com/apache/zeppelin/pull/2802 Thanks for the heads up, yep I figured out that I have to tune up zeppelin.ipython.grpc.framesize to a large number. I looked over the PR. Two quick suggestions 1) Would it be possible to make spark interpreter keep and not close the stream if such an exception happens? We can see a higher limit, but I am sure users will have cases when they will try to go higher. The Spark interpreter is then in a bad state and only way to fix this is to try increase a limit again.. Not sure if this problem belongs to Zeppelin or to grpc, so provisionally opened an issue in grpc too - https://github.com/grpc/grpc-java/issues/4086 2) Should we increase the default? .. 4Mb isn't that hard to hit when ipython returns a mid-size dataset / table.