Re: Spilling when not expected

Tom - sorry for the delay. If you try OpenJDK (on a smaller heap), do you see the same problem? Would be great to isolate whether the problem is related to J9 or not. In either case we should fix it though. On Fri, Mar 13, 2015 at 9:33 AM, Tom Hubregtsen thubregt...@gmail.com wrote: I use the

Re: enum-like types in Spark

Let me put a quick summary. #4 got majority vote with CamelCase but not UPPERCASE. The following is a minimal implementation that works for both Scala and Java. In Python, we use string for enums. This proposal is only for new public APIs. We are not going to change existing ones. -Xiangrui ~~~

Re: [mllib] Is there any bugs to divide a Breeze sparse vectors at Spark v1.3.0-rc3?

ping? On Sun, Mar 15, 2015 at 9:38 PM, David Hall david.lw.h...@gmail.com wrote: snapshot is pushed. If you verify I'll publish the new artifacts. On Sun, Mar 15, 2015 at 1:14 AM, Yu Ishikawa yuu.ishikawa+sp...@gmail.com wrote: David Hall who is a breeze creator told me that it's a bug.

Re: Profiling Spark: MemoryStore

Hi Alexander, The stack trace is a little misleading here: all of the time is spent in MemoryStore, but that's because MemoryStore is unrolling an iterator (note the iterator.next()) call so that it can be stored in-memory. Essentially all of the computation for the tasks happens as part of that

InvalidAuxServiceException in dynamicAllocation

Hi, all: Spark1.3.0 hadoop2.2.0 I put the following params in the spark-defaults.conf spark.dynamicAllocation.enabled true spark.dynamicAllocation.minExecutors 20 spark.dynamicAllocation.maxExecutors 300 spark.dynamicAllocation.executorIdleTimeout 300 spark.shuffle.service.enabled true‍

InvalidAuxServiceException in dynamicAllocation

Hi, all: Spark1.3.0 hadoop2.2.0 I put the following params in the spark-defaults.conf spark.dynamicAllocation.enabled true spark.dynamicAllocation.minExecutors 20 spark.dynamicAllocation.maxExecutors 300 spark.dynamicAllocation.executorIdleTimeout 300 spark.shuffle.service.enabled true‍

Using Spark with a SOCKS proxy

I'm trying to figure out how I might be able to use Spark with a SOCKS proxy. That is, my dream is to be able to write code in my IDE then run it without much trouble on a remote cluster, accessible only via a SOCKS proxy between the local development machine and the master node of the cluster

Fixed worker ports in the spark worker

Hi all, I see that spark server opens up random ports, especially in the workers. is there any way to fix these ports or give an set of ports for the worker to choose from? cheers -- Niranda