Return-Path: X-Original-To: apmail-spark-user-archive@minotaur.apache.org Delivered-To: apmail-spark-user-archive@minotaur.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 04DE617A5E for ; Tue, 6 Jan 2015 01:08:46 +0000 (UTC) Received: (qmail 96044 invoked by uid 500); 6 Jan 2015 01:08:39 -0000 Delivered-To: apmail-spark-user-archive@spark.apache.org Received: (qmail 95951 invoked by uid 500); 6 Jan 2015 01:08:37 -0000 Mailing-List: contact user-help@spark.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list user@spark.apache.org Received: (qmail 95939 invoked by uid 99); 6 Jan 2015 01:08:37 -0000 Received: from nike.apache.org (HELO nike.apache.org) (192.87.106.230) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 06 Jan 2015 01:08:37 +0000 X-ASF-Spam-Status: No, hits=2.8 required=5.0 tests=HTML_MESSAGE,RCVD_IN_DNSWL_LOW,SPF_PASS,URI_HEX X-Spam-Check-By: apache.org Received-SPF: pass (nike.apache.org: domain of tim@mesosphere.io designates 209.85.223.197 as permitted sender) Received: from [209.85.223.197] (HELO mail-ie0-f197.google.com) (209.85.223.197) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 06 Jan 2015 01:08:12 +0000 Received: by mail-ie0-f197.google.com with SMTP id x19so1837192ier.0 for ; Mon, 05 Jan 2015 17:07:25 -0800 (PST) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=mesosphere.io; s=google; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :content-type; bh=lBRAm6QoSl6OZKVmBCZiSYhMu7V7XAtOVi4lYnyYTkQ=; b=gjQaVe3yhVAfqkF0yJi32WWoW6Bdvbx3LX57KTNWTY5Q9Fmy3DOJe28Bkbw87h85Ug Gwqx1DieBPuXSck1ChVSOESo4q2DkI1qm6aI8y6xwNyawq6elxESccK6b0YR6cJNdkQ1 BxOKYFi+IMCgyJ8PozMMopNtNj8foxy5FtrYY= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20130820; h=x-gm-message-state:mime-version:in-reply-to:references:date :message-id:subject:from:to:content-type; bh=lBRAm6QoSl6OZKVmBCZiSYhMu7V7XAtOVi4lYnyYTkQ=; b=iEFgIT3KOIVAoTMK2TdkuX4DTPxDXbwUR8BdtS4yQTT0JPoQMsiwzQu4AHuiMhPKh4 JA+zaGZ6VwqIbEc5Jrk3bL8UciBJg57wrIOo4wJ0mdcFpIUmXWhsEd/mkOeDpE0GWBYq azBx4QpNbJKbCFN/Cbq8hV3QfgzsQRH8MT554XkRf8UjOv7httJ/XomqqM8S2NaDMKMl NGHdKr+gN+NjIM92r8OP/aeBXmY63r13WmKSZbfOKrRDiu5AI1JcTwp6tyWDkRBprsDf GjA+4CikxjANxneuFphsEHrTZEIus2w+SNtC7Uoss+eBJdcQrM42007Q0h0le8/F7TPm 8ssQ== X-Gm-Message-State: ALoCoQmdXvVqVcjI5zOwbHRtMQAEaZTHieKF9Nj4bNNzj2v//nwshQUs4/7urVoyRNC3zbcaIM9R MIME-Version: 1.0 X-Received: by 10.60.134.237 with SMTP id pn13mr55919633oeb.82.1420506445307; Mon, 05 Jan 2015 17:07:25 -0800 (PST) Received: by 10.76.173.226 with HTTP; Mon, 5 Jan 2015 17:07:25 -0800 (PST) In-Reply-To: References: <1420436255756-20966.post@n3.nabble.com> Date: Mon, 5 Jan 2015 17:07:25 -0800 Message-ID: Subject: Fwd: Controlling number of executors on Mesos vs YARN From: Tim Chen To: user Content-Type: multipart/alternative; boundary=047d7b471e3a1308fe050bf16e37 X-Virus-Checked: Checked by ClamAV on apache.org --047d7b471e3a1308fe050bf16e37 Content-Type: text/plain; charset=UTF-8 Forgot to hit reply-all. ---------- Forwarded message ---------- From: Tim Chen Date: Sun, Jan 4, 2015 at 10:46 PM Subject: Re: Controlling number of executors on Mesos vs YARN To: mvle Hi Mike, You're correct there is no such setting in for Mesos coarse grain mode, since the assumption is that each node is launched with one container and Spark is launching multiple tasks in that container. In fine-grain mode there isn't a setting like that, as it currently will launch an executor as long as it satisfies the minimum container resource requirement. I've created a JIRA earlier about capping the number of executors or better distribute the # of executors launched in each node. Since the decision of choosing what node to launch containers is all in the Spark scheduler side, it's very easy to modify it. Btw, what's the configuration to set the # of executors on YARN side? Thanks, Tim On Sun, Jan 4, 2015 at 9:37 PM, mvle wrote: > I'm trying to compare the performance of Spark running on Mesos vs YARN. > However, I am having problems being able to configure the Spark workload to > run in a similar way on Mesos and YARN. > > When running Spark on YARN, you can specify the number of executors per > node. So if I have a node with 4 CPUs, I can specify 6 executors on that > node. When running Spark on Mesos, there doesn't seem to be an equivalent > way to specify this. In Mesos, you can somewhat force this by specifying > the > number of CPU resources to be 6 when running the slave daemon. However, > this > seems to be a static configuration of the Mesos cluster rather something > that can be configured in the Spark framework. > > So here is my question: > > For Spark on Mesos, am I correct that there is no way to control the number > of executors per node (assuming an idle cluster)? For Spark on Mesos > coarse-grained mode, there is a way to specify max_cores but that is still > not equivalent to specifying the number of executors per node as when Spark > is run on YARN. > > If I am correct, then it seems Spark might be at a disadvantage running on > Mesos compared to YARN (since it lacks the fine tuning ability provided by > YARN). > > Thanks, > Mike > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Controlling-number-of-executors-on-Mesos-vs-YARN-tp20966.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscribe@spark.apache.org > For additional commands, e-mail: user-help@spark.apache.org > > --047d7b471e3a1308fe050bf16e37 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Forgot to hit reply-all.

---------- Forwarded message ----------
From: Tim Chen <tim@mesosphere.io>
Date: Sun, Jan 4, 2015 at 10:46 PMSubject: Re: Controlling number of executors on Mesos vs YARN
To: mvle= <mvle@us.ibm.com>


=
Hi Mike,

You're correct there is no= such setting in for Mesos coarse grain mode, since the assumption is that = each node is launched with one container and Spark is launching multiple ta= sks in that container.

In fine-grain mode there is= n't a setting like that, as it currently will launch an executor as lon= g as it satisfies the minimum container resource requirement.
I've created a JIRA earlier about capping the number of exe= cutors or better distribute the # of executors launched in each node. Since= the decision of choosing what node to launch containers is all in the Spar= k scheduler side, it's very easy to modify it.

Btw, what's the configuration to set the # of executors on YARN side?<= /div>

Thanks,

Tim


On Sun, Jan 4, 2015 at 9= :37 PM, mvle <mvle@us.ibm.com> wrote:
I'm trying to compare the performance of Spark running on Mes= os vs YARN.
However, I am having problems being able to configure the Spark workload to=
run in a similar way on Mesos and YARN.

When running Spark on YARN, you can specify the number of executors per
node. So if I have a node with 4 CPUs, I can specify 6 executors on that node. When running Spark on Mesos, there doesn't seem to be an equivale= nt
way to specify this. In Mesos, you can somewhat force this by specifying th= e
number of CPU resources to be 6 when running the slave daemon. However, thi= s
seems to be a static configuration of the Mesos cluster rather something that can be configured in the Spark framework.

So here is my question:

For Spark on Mesos, am I correct that there is no way to control the number=
of executors per node (assuming an idle cluster)? For Spark on Mesos
coarse-grained mode, there is a way to specify max_cores but that is still<= br> not equivalent to specifying the number of executors per node as when Spark=
is run on YARN.

If I am correct, then it seems Spark might be at a disadvantage running on<= br> Mesos compared to YARN (since it lacks the fine tuning ability provided by<= br> YARN).

Thanks,
Mike



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