David, glad it helped! And thanks for your clear example. > The only remaining question would then be what a sensible default for *spark.kubernetes.executor.cores *would be. Seeing that I wanted more than 1 and Yinan wants less, leaving it at 1 night be best.
1 as default SGTM. Thanks, Kimoon On Fri, Mar 30, 2018 at 1:38 PM, David Vogelbacher < dvogelbac...@palantir.com> wrote: > Thanks for linking that PR Kimoon. > > > It actually does mostly address the issue I was referring to. As the issue > <https://github.com/apache-spark-on-k8s/spark/issues/352> I linked in my > first email states, one physical cpu might not be enough to execute a task > in a performant way. > > > > So if I set *spark.executor.cores=1* and *spark.task.cpus=1* , I will get > 1 core from Kubernetes and execute one task per Executor and run into > performance problems. > > Being able to specify `spark.kubernetes.executor.cores=1.2` would fix the > issue (1.2 is just an example). > > I am curious as to why you, Yinan, would want to use this property to > request less than 1 physical cpu (that is how it sounds to me on the PR). > > Do you have testing that indicates that less than 1 physical CPU is enough > for executing tasks? > > > > In the end it boils down to the question proposed by Yinan: > > > A relevant question is should Spark on Kubernetes really be opinionated > on how to set the cpu request and limit and even try to determine this > automatically? > > > > And I completely agree with your answer Kimoon, we should provide sensible > defaults and make it configurable, as Yinan’s PR does. > > The only remaining question would then be what a sensible default for > *spark.kubernetes.executor.cores > *would be. Seeing that I wanted more than 1 and Yinan wants less, leaving > it at 1 night be best. > > > > Thanks, > > David > > > > *From: *Kimoon Kim <kim...@pepperdata.com> > *Date: *Friday, March 30, 2018 at 4:28 PM > *To: *Yinan Li <liyinan...@gmail.com> > *Cc: *David Vogelbacher <dvogelbac...@palantir.com>, "dev@spark.apache.org" > <dev@spark.apache.org> > *Subject: *Re: [Kubernetes] Resource requests and limits for Driver and > Executor Pods > > > > I see. Good to learn the interaction between spark.task.cpus and > spark.executor.cores. But am I right to say that PR #20553 can be still > used as an additional knob on top of those two? Say a user wants 1.5 core > per executor from Kubernetes, not the rounded up integer value 2? > > > > > A relevant question is should Spark on Kubernetes really be opinionated > on how to set the cpu request and limit and even try to determine this > automatically? > > > > Personally, I don't see how this can be auto-determined at all. I think > the best we can do is to come up with sensible default values for the most > common case, and provide and well-document other knobs for edge cases. > > > Thanks, > > Kimoon > > > > On Fri, Mar 30, 2018 at 12:37 PM, Yinan Li <liyinan...@gmail.com> wrote: > > PR #20553 [github.com] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_spark_pull_20553&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=jqIG5lO5tnV3K3SDPPxw2bEHs0i6cltoaLh8K39JTTQ&e=> > is > more for allowing users to use a fractional value for cpu requests. The > existing spark.executor.cores is sufficient for specifying more than one > cpus. > > > > > One way to solve this could be to request more than 1 core from > Kubernetes per task. The exact amount we should request is unclear to me > (it largely depends on how many threads actually get spawned for a task). > > A good indication is spark.task.cpus, and on average how many tasks are > expected to run by a single executor at any point in time. If each executor > is only expected to run one task at most at any point in time, > spark.executor.cores can be set to be equal to spark.task.cpus. > > A relevant question is should Spark on Kubernetes really be opinionated on > how to set the cpu request and limit and even try to determine this > automatically? > > > > On Fri, Mar 30, 2018 at 11:40 AM, Kimoon Kim <kim...@pepperdata.com> > wrote: > > > Instead of requesting `[driver,executor].memory`, we should just request > `[driver,executor].memory + [driver,executor].memoryOverhead `. I think > this case is a bit clearer than the CPU case, so I went ahead and filed an > issue > [issues.apache.org] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__issues.apache.org_jira_browse_SPARK-2D23825&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=hA8h-KIeJ_6Khjx1JzFZF55ZH3GnSrB4HEkHc1I-yBc&e=> > with > more details and made a PR [github.com] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_spark_pull_20943&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=qZFhxef7FgsA9UfijbVtKAIDuchcTf9wQxYIKL87SsU&e=> > . > > I think this suggestion makes sense. > > > > > One way to solve this could be to request more than 1 core from > Kubernetes per task. The exact amount we should request is unclear to me > (it largely depends on how many threads actually get spawned for a task). > > > > I wonder if this is being addressed by PR #20553 [github.com] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_spark_pull_20553&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=jqIG5lO5tnV3K3SDPPxw2bEHs0i6cltoaLh8K39JTTQ&e=> > written > by Yinan. Yinan? > > > Thanks, > > Kimoon > > > > On Thu, Mar 29, 2018 at 5:14 PM, David Vogelbacher < > dvogelbac...@palantir.com> wrote: > > Hi, > > > > At the moment driver and executor pods are created using the following > requests and limits: > > > > *CPU* > > *Memory* > > *Request* > > [driver,executor].cores > > [driver,executor].memory > > *Limit* > > Unlimited (but can be specified using spark.[driver,executor].cores) > > [driver,executor].memory + [driver,executor].memoryOverhead > > > > Specifying the requests like this leads to problems if the pods only get > the requested amount of resources and nothing of the optional (limit) > resources, as it can happen in a fully utilized cluster. > > > > *For memory:* > > Let’s say we have a node with 100GiB memory and 5 pods with 20 GiB memory > and 5 GiB memoryOverhead. > > At the beginning all 5 pods use 20 GiB of memory and all is well. If a pod > then starts using its overhead memory it will get killed as there is no > more memory available, even though we told spark > > that it can use 25 GiB of memory. > > > > Instead of requesting `[driver,executor].memory`, we should just request > `[driver,executor].memory + [driver,executor].memoryOverhead `. > > I think this case is a bit clearer than the CPU case, so I went ahead and > filed an issue [issues.apache.org] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__issues.apache.org_jira_browse_SPARK-2D23825&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=hA8h-KIeJ_6Khjx1JzFZF55ZH3GnSrB4HEkHc1I-yBc&e=> > with more details and made a PR [github.com] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_spark_pull_20943&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=qZFhxef7FgsA9UfijbVtKAIDuchcTf9wQxYIKL87SsU&e=> > . > > > > *For CPU:* > > As it turns out, there can be performance problems if we only have > `executor.cores` available (which means we have one core per task). This > was raised here [github.com] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache-2Dspark-2Don-2Dk8s_spark_issues_352&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=BFXcJr3WTIvmlY-gtaiCO5QK4bLix2sgwDDpPfrZKoE&m=TrCA4oIVKyN3M_ExqpHr7bbhi14uvoEaspPwclIJI4M&s=uTMrl29jkJRlc_N1S_6lvwCjkovzrsan8zIczzxDZGM&e=> > and is the reason that the cpu limit was set to unlimited. > > This issue stems from the fact that in general there will be more than one > thread per task, resulting in performance impacts if there is only one core > available. > > However, I am not sure that just setting the limit to unlimited is the > best solution because it means that even if the Kubernetes cluster can > perfectly satisfy the resource requests, performance might be very bad. > > > > I think we should guarantee that an executor is able to do its work well > (without performance issues or getting killed - as could happen in the > memory case) with the resources it gets guaranteed from Kubernetes. > > > > One way to solve this could be to request more than 1 core from Kubernetes > per task. The exact amount we should request is unclear to me (it largely > depends on how many threads actually get spawned for a task). > > We would need to find a way to determine this somehow automatically or at > least come up with a better default value than 1 core per task. > > > > Does somebody have ideas or thoughts on how to solve this best? > > > > Best, > > David > > > > > > >
