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https://issues.apache.org/jira/browse/BEAM-9247?focusedWorklogId=392543&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-392543
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ASF GitHub Bot logged work on BEAM-9247:
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Author: ASF GitHub Bot
Created on: 25/Feb/20 13:22
Start Date: 25/Feb/20 13:22
Worklog Time Spent: 10m
Work Description: EDjur commented on issue #10959: [BEAM-9247] Integrate
GCP Vision API functionality
URL: https://github.com/apache/beam/pull/10959#issuecomment-590859920
> I wonder whether it makes sense to support async (offline) annotation from
Beam's perspective. Let's suppose that we don't return anything and
`AsyncBatchAnnotateImage` essentially become a sink. In that case, Beam, as a
data processing framework, doesn't provide much value. If all the transform
does is just sending a request, there is no point in executing it on multiple
Dataflow or Flink workers. We'd rather use a task orchestration tool, like
Apache Airflow.
>
> On the other hand, the main advantage of sync (online) annotation is that
it returns results relatively fast for further processing.
I agree that those sort of tasks are more suited for e.g. Airflow, and that
was something that crossed my mind too.
If you think that batches of <=5 items are useful, then perhaps we should
go with sync (online) batch annotation rather than async. But I guess the
question then is how much use (or more efficient) a batch of 5 image
annotations is compared to 5 separate annotations.
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Issue Time Tracking
-------------------
Worklog Id: (was: 392543)
Time Spent: 2.5h (was: 2h 20m)
> [Python] PTransform that integrates Cloud Vision functionality
> --------------------------------------------------------------
>
> Key: BEAM-9247
> URL: https://issues.apache.org/jira/browse/BEAM-9247
> Project: Beam
> Issue Type: Sub-task
> Components: io-py-gcp
> Reporter: Kamil Wasilewski
> Assignee: Elias Djurfeldt
> Priority: Major
> Time Spent: 2.5h
> Remaining Estimate: 0h
>
> The goal is to create a PTransform that integrates Google Cloud Vision API
> functionality [1].
> [1] https://cloud.google.com/vision/docs/
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