Re: Instability issues with Spark 2.0.1 and Kafka 0.10

Here are some examples and details of the scenarios. The KafkaRDD is the most error prone to polling timeouts and concurrentm modification errors. *Using KafkaRDD* - This takes a list of channels and processes them in parallel using the KafkaRDD directly. they all use the same consumer group

Instability issues with Spark 2.0.1 and Kafka 0.10

I am getting the issues using Spark 2.0.1 and Kafka 0.10. I have two jobs, one that uses a Kafka stream and one that uses just the KafkaRDD. With the KafkaRDD, I continually get the "Failed to get records .. after polling". I have adjusted the polling with

Re: Submit job with driver options in Mesos Cluster mode

We were using 1.6, but now we are on 2.0.1. Both versions show the same issue. I dove deep into the Spark code and have identified that the extra java options are /not/ added to the process on the executors. At this point, I believe you have to use spark-defaults.conf to set any values that will

Memory leak warnings in Spark 2.0.1

I am getting excessive memory leak warnings when running multiple mapping and aggregations and using DataSets. Is there anything I should be looking for to resolve this or is this a known issue? WARN [Executor task launch worker-0] org.apache.spark.memory.TaskMemoryManager - leak 16.3 MB memory