I love the idea. Generally it is quite easy now to add new executors and there is no harm in having more options. I don't think we need to justify it as a replacement of anything honestly.
The biggest decision is whether this is a community managed executor or if we can find stakeholders to create this outside of Airflow (those stakeholders could be some of us from the community). Cheers, Niko ________________________________ From: Vikram Koka <vik...@astronomer.io.INVALID> Sent: Wednesday, October 16, 2024 4:13:27 PM To: dev@airflow.apache.org Subject: RE: [EXT] [DISCUSS] Create community "Apache YuniKorn" executor ? CAUTION: This email originated from outside of the organization. Do not click links or open attachments unless you can confirm the sender and know the content is safe. AVERTISSEMENT: Ce courrier électronique provient d’un expéditeur externe. Ne cliquez sur aucun lien et n’ouvrez aucune pièce jointe si vous ne pouvez pas confirmer l’identité de l’expéditeur et si vous n’êtes pas certain que le contenu ne présente aucun risque. I am supportive of this in the long term (i.e. post-3.0) as an additional Executor similar to the Kubernetes Executor. As Jens said "K8sExecutor++". Just to be precise, I don't believe that this can be a replacement for Celery Executor (at least at first glance). I also believe that for this to be effective, this will need some dedicated work including additional information about the task. I am very curious for Amogh to chime in on this :) On Tue, Oct 15, 2024 at 1:58 PM Jarek Potiuk <ja...@potiuk.com> wrote: > Yeah - it was a bit of dramatisation when I recalled the Celery > "replacement" ;) . And yes it's not really "alternative" to Celery, Celery > is there to stay for short tasks. > > Almost by definition it is meant to run more heavy tasks (for example batch > inference) where multiple tasks running in parallel share the same GPU for > example - because that's what we want to optimize. > > And yes - it provides features that K8S executor does not - gang > scheduling, and sophisticated preemption logic. > > J. > > On Tue, Oct 15, 2024 at 8:40 PM Jens Scheffler <j_scheff...@gmx.de.invalid > > > wrote: > > > Hi Jarek, > > > > scanning but not reading the full docs I understand that YuniKorn is a > > specialized, more advanced K8sExecutor - all workload also runs in PODs? > > > > If this is the right understanding then it might be a K8sExecutor++ or > > could replace this... but Celery is playing very good usually if you > > have very small and high-frequency tasks. Don't know if I mis-interpret > > the docs... but would it be scaling down to very small > > PythonOperator/@task decorated tasks with a few lines of code as well? > > > > Jens > > > > On 15.10.24 12:55, Jarek Potiuk wrote: > > > Hello here, > > > > > > *Tl;DR; I would love to start discussion about creating (for Airflow > 3.x > > - > > > it does not have to be Airflow 3.0) a new community executor based on > > > YuniKorn* > > > > > > You might remember my point "replacing Celery Executor" when I raised > the > > > Airflow 3 question. I never actually "meant" to replace (and remove) > > Celery > > > Executor, but I was more in a quest to see if we have a viable > > alternative. > > > > > > And I think we have one with Apache Yunicorn. > > https://yunikorn.apache.org/ > > > > > > While it is not a direct replacement (so I'd say it should be an > > additional > > > executor), I think Yunikorn can provide us with a number of features > that > > > we currently cannot give to our users and from the discussions I had > and > > > talk I saw at the Community Over Code in Denver, I believe it might be > > > something that might make Airflow also more capable especially in the > > > "optimization wars" context that I wrote about in > > > https://lists.apache.org/thread/1mp6jcfvx67zd3jjt9w2hlj0c5ysbh8r > > > > > > It seems like quite a good fit for the "Inference" use case that we > want > > to > > > support for Airflow 3. > > > > > > At the Community Over Code I attended a talk (and had quite nice > > follow-up > > > discussion) from Apple engineers - named: "Maximizing GPU Utilization: > > > Apache YuniKorn Preemption" and had a very long discussion with > Cloudera > > > people who are using YuniKorn for years to optimize their workloads. > > > > > > The presentation is not recorded, but I will try to get slides and send > > it > > > your way. > > > > > > I think we should take a close look at it - because it seems to save a > > ton > > > of implementation effort for the Apple team running Batch inference for > > > their multi-tenant internal environment - which I think is precisely > what > > > you want to do. > > > > > > YuniKorn (https://yunikorn.apache.org/) is an "app-aware" scheduler > that > > > has a number of queue / capacity management models, policies that allow > > > controlling various applications - competing for GPUs from a common > pool. > > > > > > They mention things like: > > > > > > * Gang Scheduling / with gang scheduling preemption where there are > > > workloads requiring minimum number of workers > > > * Supports Latency sensitive workloads > > > * Resource quota management - things like priorities of execution > > > * YuniKorn preemption - with guaranteed capacity and preemption when > > needed > > > - which improves the utilisation > > > * Preemption that minimizes preemption cost (Pod level preemption > rather > > > than application level preemption) - very customizable preemption with > > > opt-in/opt-out, queues, resource weights, fencing, supporting fifo/lifo > > > sorting etc. > > > * Runs in Cloud and on-premise > > > > > > The talk described quite a few scenarios of preemption/utilization/ > > > guaranteed resources etc. They also outlined on what YuniKorn works on > > new > > > features (intra-queue preemption etc.) and what future things can be > > done. > > > > > > > > > Coincidentally - Amogh Desai with a friend submitted a talk for Airflow > > > Summit: > > > > > > "A Step Towards Multi-Tenant Airflow Using Apache YuniKorn" > > > > > > Which did not make it to the Summit (other talk of Amogh did) - but I > > think > > > back then we have not realized about the potential of utilising > YuniKorn > > to > > > optimize workflows managed by Airflow. > > > > > > But we seem to have people in the community who know more about > YuniKorn > > <> > > > Airflow relation (Amogh :) ) and could probably comment and add some > > "from > > > the trenches" experience to the discussion. > > > > > > Here is the description of the talk that Amoghs submitted: > > > > > > Multi-tenant Airflow is hard and there have been novel approaches in > the > > > recent past to converge this gap. A key obstacle in multi-tenant > Airflow > > is > > > the management of cluster resources. This is crucial to avoid one > > malformed > > > workload from hijacking an entire cluster. It is also vital to restrict > > > users and groups from monopolizing resources in a shared cluster using > > > their workloads. > > > > > > To tackle these challenges, we turn to Apache YuniKorn, a K8s scheduler > > > catering all kinds of workloads. We leverage YuniKorn’s hierarchical > > queues > > > in conjunction with resource quotas to establish multi-tenancy at both > > the > > > shared namespace level and within individual namespaces where Airflow > is > > > deployed. > > > > > > YuniKorn also introduces Airflow to a new dimension of preemption. Now, > > > Airflow workers can preempt resources from lower-priority jobs, > ensuring > > > critical schedules in our data pipelines are met without compromise. > > > > > > Join us for a discussion on integrating Airflow with YuniKorn, > unraveling > > > solutions to these multi-tenancy challenges. We will also share our > past > > > experiences while scaling Airflow and the steps we have taken to handle > > > real world production challenges in equitable multi-tenant K8s > clusters. > > > > > > I would love to hear what you think about it. I know we are deep into > > > Airflow 3.0 implementation - but that one can be discussed/implemented > > > independently and maybe it's a good idea to start doing it earlier than > > > later if we see that it has good potential. > > > > > > J. > > > > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: dev-unsubscr...@airflow.apache.org > > For additional commands, e-mail: dev-h...@airflow.apache.org > > > > >
