RE: spark on yarn wastes one box (or 1 GB on each box) for am container

Are you using  Yarn   to  run  spark jobs only  ?. Are you  configuring  spark   properties in  spark-submit parameters? . If  so  did  you  try  with  --no - of - executors x*53 (where  x is  no of  nodes ) --spark executor-memory 1g --spark-driver-memory 1g. You  might  see  yarn  allocating

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

I mean Jonathan On Tue, Feb 9, 2016 at 10:41 AM, Alexander Pivovarov wrote: > I decided to do YARN over-commit and add 896 > to yarn.nodemanager.resource.memory-mb > it was 54,272 > now I set it to 54,272+896 = 55,168 > > Kelly, can I ask you couple questions > 1. it is

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

I decided to do YARN over-commit and add 896 to yarn.nodemanager.resource.memory-mb it was 54,272 now I set it to 54,272+896 = 55,168 Kelly, can I ask you couple questions 1. it is possible to add yarn label to particular instance group boxes on EMR? 2. in addition to maximizeResourceAllocation

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Thanks Jonathan Actually I'd like to use maximizeResourceAllocation. Ideally for me would be to add new instance group having single small box labelled as AM I'm not sure "aws emr create-cluster" supports setting custom LABELS , the only settings awailable are:

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Interesting, I was not aware of spark.yarn.am.nodeLabelExpression. We do use YARN labels on EMR; each node is automatically labeled with its type (MASTER, CORE, or TASK). And we do set yarn.app.mapreduce.am.labels=CORE in yarn-site.xml, but we do not set spark.yarn.am.nodeLabelExpression. Does

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

If it's too small to run an executor, I'd think it would be chosen for the AM as the only way to satisfy the request. On Tue, Feb 9, 2016 at 8:35 AM, Alexander Pivovarov wrote: > If I add additional small box to the cluster can I configure yarn to select > small box to run

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

If I add additional small box to the cluster can I configure yarn to select small box to run am container? On Mon, Feb 8, 2016 at 10:53 PM, Sean Owen wrote: > Typically YARN is there because you're mediating resource requests > from things besides Spark, so yeah using every

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

How about running in client mode, so that the client from which it is run becomes the driver. Regards, Praveen On 9 Feb 2016 16:59, "Steve Loughran" wrote: > > > On 9 Feb 2016, at 06:53, Sean Owen wrote: > > > > > > I think you can let YARN

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

> On 9 Feb 2016, at 06:53, Sean Owen wrote: > > > I think you can let YARN over-commit RAM though, and allocate more > memory than it actually has. It may be beneficial to let them all > think they have an extra GB, and let one node running the AM > technically be

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Sean, I'm not sure if that's actually the case, since the AM would be allocated before the executors are even requested (by the driver through the AM), right? This must at least be the case with dynamicAllocation enabled, but I would expect that it's true regardless. However, Alex, yes, this

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Praveen, You mean cluster mode, right? That would still in a sense cause one box to be "wasted", but at least it would be used a bit more to its full potential, especially if you set spark.driver.memory to higher than its 1g default. Also, cluster mode is not an option for some applications, such

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

On Tue, Feb 9, 2016 at 12:16 PM, Jonathan Kelly wrote: > And we do set yarn.app.mapreduce.am.labels=CORE That sounds very mapreduce-specific, so I doubt Spark (or anything non-MR) would honor it. -- Marcelo

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

You can set custom per-instance-group configurations (e.g., ["classification":"yarn-site",properties:{"yarn.nodemanager.labels":"SPARKAM"}]) using the Configurations parameter of http://docs.aws.amazon.com/ElasticMapReduce/latest/API/API_InstanceGroupConfig.html. Unfortunately, it's not currently

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Oh, sheesh, how silly of me. I copied and pasted that setting name without even noticing the "mapreduce" in it. Yes, I guess that would mean that Spark AMs are probably running even on TASK instances currently, which is OK but not consistent with what we do for MapReduce. I'll make sure we set

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Can you add an ability to set custom yarn labels instead/in addition to? On Feb 9, 2016 3:28 PM, "Jonathan Kelly" wrote: > Oh, sheesh, how silly of me. I copied and pasted that setting name without > even noticing the "mapreduce" in it. Yes, I guess that would mean that >

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Great! Thank you! On Tue, Feb 9, 2016 at 4:02 PM, Jonathan Kelly wrote: > You can set custom per-instance-group configurations (e.g., > ["classification":"yarn-site",properties:{"yarn.nodemanager.labels":"SPARKAM"}]) > using the Configurations parameter of >

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Am container starts first and yarn selects random computer to run it. Is it possible to configure yarn so that it selects small computer for am container. On Feb 9, 2016 12:40 AM, "Sean Owen" wrote: > If it's too small to run an executor, I'd think it would be chosen for >

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

You should be able to use spark.yarn.am.nodeLabelExpression if your version of YARN supports node labels (and you've added a label to the node where you want the AM to run). On Tue, Feb 9, 2016 at 9:51 AM, Alexander Pivovarov wrote: > Am container starts first and yarn

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Alex, That's a very good question that I've been trying to answer myself recently too. Since you've mentioned before that you're using EMR, I assume you're asking this because you've noticed this behavior on emr-4.3.0. In this release, we made some changes to the maximizeResourceAllocation

spark on yarn wastes one box (or 1 GB on each box) for am container

Lets say that yarn has 53GB memory available on each slave spark.am container needs 896MB. (512 + 384) I see two options to configure spark: 1. configure spark executors to use 52GB and leave 1 GB on each box. So, some box will also run am container. So, 1GB memory will not be used on all

Re: spark on yarn wastes one box (or 1 GB on each box) for am container

Typically YARN is there because you're mediating resource requests from things besides Spark, so yeah using every bit of the cluster is a little bit of a corner case. There's not a good answer if all your nodes are the same size. I think you can let YARN over-commit RAM though, and allocate more