Hi, I have a program similar to the BinaryClassifier example that I am running using my data (which is fairly small). I run this for 100 iterations. I observed the following performance:
Standalone mode cluster with 10 nodes (with Spark 1.0.2): 5 minutes Standalone mode cluster with 10 nodes (with Spark 1.1.0): 8.9 minutes Mesos cluster with 10 nodes (with Spark 1.1.0): 17 minutes 1) According to the documentation, Spark 1.1.0 has better performance. So I would like to understand why the runtime is longer on Spark 1.1.0. 2) Why is the performance on mesos significantly higher than in standalone mode? I just wanted to find out if any one else has observed poor performance for Mllib based programs on mesos cluster. I looked through the application detail logs and found that some of the scheduler delay values were higher on mesos compared to standalone mode (40 ms vs. 10 ms). Is the mesos scheduler slower? thanks -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/mllib-performance-on-mesos-cluster-tp14692.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
