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https://issues.apache.org/jira/browse/BEAM-12792?focusedWorklogId=729952&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-729952
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ASF GitHub Bot logged work on BEAM-12792:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 19/Feb/22 01:20
Start Date: 19/Feb/22 01:20
Worklog Time Spent: 10m
Work Description: tvalentyn commented on a change in pull request #16658:
URL: https://github.com/apache/beam/pull/16658#discussion_r810426468
##########
File path: sdks/python/container/boot.go
##########
@@ -145,7 +145,21 @@ func main() {
// Guard from concurrent artifact retrieval and installation,
// when called by child processes in a worker pool.
+ workerPoolId := os.Getenv(workerPoolIdEnv)
+ var venvDir string
+ if workerPoolId != "" {
+ venvDir = filepath.Join(*semiPersistDir, "beam-venv",
"beam-pool-" + workerPoolId)
+ } else {
+ venvDir = filepath.Join(*semiPersistDir, "beam-venv",
"beam-worker-" + *id)
Review comment:
> It's not clear why there wouldn't be a workerPoolId. Maybe add a
comment.
I think the difference here is how the boot.go code is executed in various
execution modes that were added for various runners, for example on
PortableRunner+Flink Cluster vs Dataflow.
The worker pool logic was initially added for for portable runner
(https://github.com/apache/beam/pull/9371), and a more recent change here (that
is not gained significant usage yet) is
https://github.com/apache/beam/pull/15642. Different environment variables /
params may be available in different execution mode and we will need to make
sure this works cleanly for all scenarios.
I am familiar with one of at least the 3 branches so caching up now.
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Issue Time Tracking
-------------------
Worklog Id: (was: 729952)
Time Spent: 4h (was: 3h 50m)
> Multiple jobs running on Flink session cluster reuse the persistent Python
> environment.
> ---------------------------------------------------------------------------------------
>
> Key: BEAM-12792
> URL: https://issues.apache.org/jira/browse/BEAM-12792
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-harness
> Affects Versions: 2.27.0, 2.28.0, 2.29.0, 2.30.0, 2.31.0
> Environment: Kubernetes 1.20 on Ubuntu 18.04.
> Reporter: Jens Wiren
> Priority: P1
> Labels: FlinkRunner, beam
> Time Spent: 4h
> Remaining Estimate: 0h
>
> I'm running TFX pipelines on a Flink cluster using Beam in k8s. However,
> extra python packages passed to the Flink runner (or rather beam worker
> side-car) are only installed once per deployment cycle. Example:
> # Flink is deployed and is up and running
> # A TFX pipeline starts, submits a job to Flink along with a python whl of
> custom code and beam ops.
> # The beam worker installs the package and the pipeline finishes succesfully.
> # A new TFX pipeline is build where a new beam fn is introduced, the pipline
> is started and the new whl is submitted as in step 2).
> # This time, the new package is not being installed in the beam worker
> causing the job to fail due to a reference which does not exist in the beam
> worker, since it didn't install the new package.
>
> I started using Flink from beam version 2.27 and it has been an issue all the
> time.
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