Does increasing the number of partition helps? You could try out something 3 times what you currently have. Another trick i used was to partition the problem into multiple dataframes and run them sequentially and persistent the result and then run a union on the results.
Hope this helps. On Fri, Jan 22, 2016, 3:48 AM Darren Govoni <dar...@ontrenet.com> wrote: > Me too. I had to shrink my dataset to get it to work. For us at least > Spark seems to have scaling issues. > > > > Sent from my Verizon Wireless 4G LTE smartphone > > > -------- Original message -------- > From: "Sanders, Isaac B" <sande...@rose-hulman.edu> > Date: 01/21/2016 11:18 PM (GMT-05:00) > To: Ted Yu <yuzhih...@gmail.com> > Cc: user@spark.apache.org > Subject: Re: 10hrs of Scheduler Delay > > I have run the driver on a smaller dataset (k=2, n=5000) and it worked > quickly and didn’t hang like this. This dataset is closer to k=10, n=4.4m, > but I am using more resources on this one. > > - Isaac > > On Jan 21, 2016, at 11:06 PM, Ted Yu <yuzhih...@gmail.com> wrote: > > You may have seen the following on github page: > > Latest commit 50fdf0e on Feb 22, 2015 > > That was 11 months ago. > > Can you search for similar algorithm which runs on Spark and is newer ? > > If nothing found, consider running the tests coming from the project to > determine whether the delay is intrinsic. > > Cheers > > On Thu, Jan 21, 2016 at 7:46 PM, Sanders, Isaac B < > sande...@rose-hulman.edu> wrote: > >> That thread seems to be moving, it oscillates between a few different >> traces… Maybe it is working. It seems odd that it would take that long. >> >> This is 3rd party code, and after looking at some of it, I think it might >> not be as Spark-y as it could be. >> >> I linked it below. I don’t know a lot about spark, so it might be fine, >> but I have my suspicions. >> >> >> https://github.com/alitouka/spark_dbscan/blob/master/src/src/main/scala/org/alitouka/spark/dbscan/exploratoryAnalysis/DistanceToNearestNeighborDriver.scala >> >> - Isaac >> >> On Jan 21, 2016, at 10:08 PM, Ted Yu <yuzhih...@gmail.com> wrote: >> >> You may have noticed the following - did this indicate prolonged >> computation in your code ? >> >> org.apache.commons.math3.util.MathArrays.distance(MathArrays.java:205) >> org.apache.commons.math3.ml.distance.EuclideanDistance.compute(EuclideanDistance.java:34) >> org.alitouka.spark.dbscan.spatial.DistanceCalculation$class.calculateDistance(DistanceCalculation.scala:15) >> org.alitouka.spark.dbscan.exploratoryAnalysis.DistanceToNearestNeighborDriver$.calculateDistance(DistanceToNearestNeighborDriver.scala:16) >> >> >> On Thu, Jan 21, 2016 at 5:13 PM, Sanders, Isaac B < >> sande...@rose-hulman.edu> wrote: >> >>> Hadoop is: HDP 2.3.2.0-2950 >>> >>> Here is a gist (pastebin) of my versions en masse and a stacktrace: >>> https://gist.github.com/isaacsanders/2e59131758469097651b >>> >>> Thanks >>> >>> On Jan 21, 2016, at 7:44 PM, Ted Yu <yuzhih...@gmail.com> wrote: >>> >>> Looks like you were running on YARN. >>> >>> What hadoop version are you using ? >>> >>> Can you capture a few stack traces of the AppMaster during the delay and >>> pastebin them ? >>> >>> Thanks >>> >>> On Thu, Jan 21, 2016 at 8:08 AM, Sanders, Isaac B < >>> sande...@rose-hulman.edu> wrote: >>> >>>> The Spark Version is 1.4.1 >>>> >>>> The logs are full of standard fair, nothing like an exception or even >>>> interesting [INFO] lines. >>>> >>>> Here is the script I am using: >>>> https://gist.github.com/isaacsanders/660f480810fbc07d4df2 >>>> >>>> Thanks >>>> Isaac >>>> >>>> On Jan 21, 2016, at 11:03 AM, Ted Yu <yuzhih...@gmail.com> wrote: >>>> >>>> Can you provide a bit more information ? >>>> >>>> command line for submitting Spark job >>>> version of Spark >>>> anything interesting from driver / executor logs ? >>>> >>>> Thanks >>>> >>>> On Thu, Jan 21, 2016 at 7:35 AM, Sanders, Isaac B < >>>> sande...@rose-hulman.edu> wrote: >>>> >>>>> Hey all, >>>>> >>>>> I am a CS student in the United States working on my senior thesis. >>>>> >>>>> My thesis uses Spark, and I am encountering some trouble. >>>>> >>>>> I am using https://github.com/alitouka/spark_dbscan, and to determine >>>>> parameters, I am using the utility class they supply, >>>>> org.alitouka.spark.dbscan.exploratoryAnalysis.DistanceToNearestNeighborDriver. >>>>> >>>>> I am on a 10 node cluster with one machine with 8 cores and 32G of >>>>> memory and nine machines with 6 cores and 16G of memory. >>>>> >>>>> I have 442M of data, which seems like it would be a joke, but the job >>>>> stalls at the last stage. >>>>> >>>>> It was stuck in Scheduler Delay for 10 hours overnight, and I have >>>>> tried a number of things for the last couple days, but nothing seems to be >>>>> helping. >>>>> >>>>> I have tried: >>>>> - Increasing heap sizes and numbers of cores >>>>> - More/less executors with different amounts of resources. >>>>> - Kyro Serialization >>>>> - FAIR Scheduling >>>>> >>>>> It doesn’t seem like it should require this much. Any ideas? >>>>> >>>>> - Isaac >>>> >>>> >>>> >>>> >>> >>> >> >> > >
