tvalentyn opened a new pull request #13475:
URL: https://github.com/apache/beam/pull/13475
When Dataflow runs portable python pipelines, such as all Python streaming
pipelines and all pipelines on Runner V2, Dataflow service currently starts as
many SDK containers as there are CPU cores on the VMs.
This behavior was originally initiated by the SDK setting an experiment
use_multiple_sdk_containers, and it was possible to disable this behavior by
supplying `--experiment=no_use_multiple_sdk_containers`.
Dataflow service no longer needs SDK to supply these experiments, so we
clean up this logic.
Dataflow service may still recognize
`--experiment=no_use_multiple_sdk_containers` for some time but it is NOT
RECOMMENDED to use this knob: in the future Dataflow may have better algorithms
for deciding how many SDK containers to start, and specifying this knob may
interfere with these algorithms.
Users can control the number of cores on the VMs by setting an appropriate
`--machine_type`. Note that there are custom machine types, where users can
select number of cores and number of memory GBs, such as
`--machine_type=custom-1-13312-ext` which will have 1 core and 13GB memory.
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