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From Reinis Vicups <mah...@orbit-x.de>
Subject Re: Mahout 1.0: parallelism/number tasks during SimilarityAnalysis.rowSimilarity
Date Mon, 13 Oct 2014 16:54:20 GMT
Hello,

>When you set the Spark config as below do you still get one task?

Unfortunately yes.

Currently I am looking for the very first shuffle stage in 
SimilarityAnalysis#rowSimilarity but cannot find it. There is a lot of 
mapping, wrapping and caching during 
SimilarityAnalysis#sampleDownAndBinarizeand I don't get where to look 
for the code of "%*%" in:

// Compute row similarity cooccurrence matrix AA'
val drmAAt = drmA %*% drmA.t

I would like to hard code partition number in that first shuffle just 
for the sake of experiment.

On 13.10.2014 18:29, Pat Ferrel wrote:
> I see no place where the spark.default.parallelism is set so your config can be set it
to whatever you wish. When you set the Spark config as below do you still get one task? The
test suite sets the spark.default.parallelism to 10 before the context is initialized. To
do this with the SimilarityAnalysis.rowSimilarity (here I assume you are modifying the driver)
put the  .set("spark.default.parallelism", 400) in RowSimilarityDriver.start and see if that
changes things.
>
> If this doesn’t work it may be that the blas optimizer is doing something with the
value but I’m lost in that code There is only one place the value is read, which is in Par.scala
>
>          // auto adjustment, try to scale up to either x1Size or x2Size.
>          val clusterSize = rdd.context.getConf.get("spark.default.parallelism", "1").toInt
>
>          val x1Size = (clusterSize * .95).ceil.toInt
>          val x2Size = (clusterSize * 1.9).ceil.toInt
>
>          if (rdd.partitions.size <= x1Size)
>            rdd.coalesce(numPartitions = x1Size, shuffle = true)
>          else if (rdd.partitions.size <= x2Size)
>            rdd.coalesce(numPartitions = x2Size, shuffle = true)
>          else
>            rdd.coalesce(numPartitions = rdd.partitions.size)
>
>
> Dmitriy can you shed any light on the use of spark.default.parallelism, how to increase
it or how to get more than one task created when performing ABt?
>
>
> On Oct 13, 2014, at 8:56 AM, Reinis Vicups <mahout@orbit-x.de> wrote:
>
> Hi,
>
> I am currently testing SimilarityAnalysis.rowSimilarity and I am wondering, how could
I increase number of tasks to use for distributed shuffle.
>
> What I currently observe, is that SimilarityAnalysis is requiring almost 20 minutes for
my dataset only with this stage:
>
> combineByKey at ABt.scala:126
>
> When I view details for the stage I see that only one task is spawned running on one
node.
>
> I have my own implementation of SimilarityAnalysis and by tuning number of tasks I have
reached HUGE performance gains.
>
> Since I couldn't find how to pass the number of tasks to shuffle operations directly,
I have set following in spark config
>
> configuration = new SparkConf().setAppName(jobConfig.jobName)
>         .set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
>         .set("spark.kryo.registrator", "org.apache.mahout.sparkbindings.io.MahoutKryoRegistrator")
>         .set("spark.kryo.referenceTracking", "false")
>         .set("spark.kryoserializer.buffer.mb", "200")
>         .set("spark.default.parallelism", 400) // <- this is the line supposed to
set default parallelism to some high number
>
> Thank you for your help
> reinis
>


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