Pat, I was not using spark-submit script. I am using mahout spark-itemsimilarity exactly how it is specified in http://mahout.apache.org/users/recommender/intro-cooccurrence-spark.html
So, what I did is I created a bootstrap action that installs spark and mahout on EMR cluster. Then, I used AWS Java APIs to create an EMR job step which can call a script (amazon provides scriptRunner that can run any script). So, I basically create a command (mahout spark-itemsimilarity <parameters>) and pass it to script runner that runs it. One of the parameters is -ma , so I pass in yarn-client. We use AWS java API to programmatically start EMR cluster (trigger by Quartz job) with whatever parameters that job needs. I used instructions in here: https://github.com/awslabs/emr-bootstrap-actions/tree/master/spark to install spark as bootstrap action. I built mahout-1.0 locally and uploaded a package to s3. I also created a bash script to copy that package from s3 to EMR, unpack, remove mahout 0.9 version that is part for EMR ami. Then I used another boostrap action to invoke that script and install mahout. I had to also make changes to mahout script. Added SPARK_HOME=/home/hadoop/spark (this is where I installed spark on EMR). Modified CLASSPATH=${CLASSPATH}:$MAHOUT_CONF_DIR to CLASSPATH=$MAHOUT_CONF_DIR to avoid including classpath passed in by amazon script-runner since it contains path to the 2.11 version of scala (installed on EMR by Amazon) that conflicts with spark/mahout 2.10.x version. -----Original Message----- From: Pat Ferrel [mailto:p...@occamsmachete.com] Sent: Thursday, March 26, 2015 3:49 PM To: user@mahout.apache.org Subject: Re: mahout 1.0 on EMR with spark item-similarity Finally getting to Yarn. Paul were you trying to run spark-itemsimilarity with the spark-submit script? That shouldn’t work, the job is a standalone app and does not require, nor is it likely to work with spark-submit. Were you able to run on Yarn? How? On Jan 29, 2015, at 9:15 AM, Pat Ferrel <p...@occamsmachete.com> wrote: There are two indices (guava HashBiMaps) that map your ID into and out of Mahout IDs (HashBiMap<int, string>). There is one copy of each (row/user IDs and column/itemIDS) per physical machine that all local tasks consult. They are Spark broadcast values. These will grow linearly as the number of items and users grow and as the size of your IDs, treated as strings, grow. The hashmaps have some overhead but in large collections the main cost is the size of the application IDs stored as strings, Mahout’s IDs are ints. On Jan 22, 2015, at 8:04 AM, Pasmanik, Paul <paul.pasma...@danteinc.com> wrote: I was able to get spark and mahout installed on EMR cluster as bootstrap actions and was able to run spark-itemsimilarity job via an EMR step with some modifications to mahout script (defining SPARK_HOME and making sure CLASSPATH is not picked up from the invoking script which is amazon's script-runner). I was only able to run this job using yarn-client (yarn-master is not able to submit to resource manager). In yarn-client mode the driver program runs in the client process and submits jobs to executors via yarn manager, so my question is how much memory does this driver need? Will the memory requirement vary based on the size of the input to spark-itemsimilarity? Thanks. -----Original Message----- From: Pasmanik, Paul [mailto:paul.pasma...@danteinc.com] Sent: Thursday, January 15, 2015 12:46 PM To: user@mahout.apache.org Subject: mahout 1.0 on EMR with spark Has anyone tried running mahout 1.0 on EMR with Spark? I've used instructions at https://github.com/awslabs/emr-bootstrap-actions/tree/master/spark to get EMR cluster running spark. I am now able to deploy EMR cluster with Spark using AWS JAVA APIs. EMR allows running a custom script as bootstrap action which I can use to install mahout. What I am trying to figure out is whether I would need to build mahout every time I start EMR cluster or have pre-built artifacts and develop a script similar to what awslab is using to install spark? Thanks. ________________________________ The information contained in this electronic transmission is intended only for the use of the recipient and may be confidential and privileged. Unauthorized use, disclosure, or reproduction is strictly prohibited and may be unlawful. If you have received this electronic transmission in error, please notify the sender immediately.
