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Support dependent distrubution in FATE cluster deployed by FATE #730

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lvying0019 opened this issue Aug 23, 2022 · 5 comments
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Support dependent distrubution in FATE cluster deployed by FATE #730

lvying0019 opened this issue Aug 23, 2022 · 5 comments
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kind/requirement New feature requirement.
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@lvying0019
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使用kubefate部署FATE on Spark
fate on spark 状态下,service_conf.yaml中
dependent_distribution: true时,
出现出错no such file or directory: '/opt/app-root/pyvenv.cfg'

FederatedAI/FATE#4255 (comment)

@JingChen23
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We don't have bandwidth to do this in verison 1.9.0, we can support this in the next release, 1.10.0

@JingChen23
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We can prioritize this task to let you use this feature early, on the feature branch.

@stuforfun stuforfun added this to the v1.10.0 milestone Aug 30, 2022
@JingChen23 JingChen23 moved this to Todo in KubeFATE Sep 7, 2022
@JingChen23
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JingChen23 commented Sep 7, 2022

Hi @lvying0019 , could you elaborate why you want the dependent_distribution to be true?

In specific, which dependencies you want to distribute to spark workers?

Actually in the image docker file, we have a base image, in which we have done pip install for almost all the fate dependencies.
https://github.com/FederatedAI/FATE-Builder/blob/main/docker-build/base/basic/Dockerfile

The fateflow image is built from the base image with pyspark installed.
https://github.com/FederatedAI/FATE-Builder/blob/main/docker-build/modules/fateflow-spark/Dockerfile

The spark images (master and worker) are also built from the base image, so it inherits all the python dependencies.
https://github.com/FederatedAI/FATE-Builder/blob/main/docker-build/modules/spark-base/Dockerfile

My current understanding is, dependent_destribution need not to be set to ture when you are using Kubefate to deploy the FATE cluster, so why do you want to set it to ture, we want to know the reason, thanks.

@JingChen23 JingChen23 self-assigned this Sep 7, 2022
@JingChen23 JingChen23 added the kind/task A task represents work that needs to be done. label Sep 13, 2022
@JingChen23 JingChen23 changed the title no such file or directory: '/opt/app-root/pyvenv.cfg' Support dependent distrubution in FATE cluster deployed by FATE Oct 24, 2022
@JingChen23 JingChen23 added kind/requirement New feature requirement. and removed bug Something isn't working labels Oct 24, 2022
@JingChen23 JingChen23 assigned n063h and unassigned JingChen23 Nov 1, 2022
@stuforfun stuforfun moved this from Todo to In Progress in KubeFATE Nov 1, 2022
@lvying0019
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Hi @lvying0019 , could you elaborate why you want the dependent_distribution to be true?

In specific, which dependencies you want to distribute to spark workers?

Actually in the image docker file, we have a base image, in which we have done pip install for almost all the fate dependencies. https://github.com/FederatedAI/FATE-Builder/blob/main/docker-build/base/basic/Dockerfile

The fateflow image is built from the base image with pyspark installed. https://github.com/FederatedAI/FATE-Builder/blob/main/docker-build/modules/fateflow-spark/Dockerfile

The spark images (master and worker) are also built from the base image, so it inherits all the python dependencies. https://github.com/FederatedAI/FATE-Builder/blob/main/docker-build/modules/spark-base/Dockerfile

My current understanding is, dependent_destribution need not to be set to ture when you are using Kubefate to deploy the FATE cluster, so why do you want to set it to ture, we want to know the reason, thanks.

您好,将dependent_distribution = true主要是因为在实际生产中,我们对接的spark集群是已经存在的,而不是我们自己去创建的集群,而且生产上spark集群环境一般都以yarn cluster的形式,所以需要设置成true,我看到在FATE 1.10版本中已经在准备支持该使用场景,相信KubeFATE在后续中也会有支持。

@JingChen23
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This issue has been fixed by 3 submission in 3 repos:
#806
FederatedAI/FATE-Flow#352
FederatedAI/FATE-Builder#19

And will be released with v1.10.0 at the end of December, 2022.

Repository owner moved this from In Progress to Done in KubeFATE Nov 21, 2022
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