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DataHub

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Hi team,
I have manual execution in pending status for a long time
How &amp; from which pod I can I kill it?

Check your datahub-actions logs. Probably the default-executor which is supposed to handle ingest actions is failing.

<@U040V3TUD5J> I don’t have any logs for it
That’s why I’ve asked if I can kill it from a pod

‘Pending’ is just a UI state.. there is nothing happening in the background as far I know. Only way to get rid off is to delete the ingestion source configuration from UI.

No other workaround for it????? Just killing the source?
No logs? Pods configuration?

Not that I know of.. but logs and pod configuration is something obvious from your DataHub deployment 

Hi again! WHere is the backend GMS and datahub-actions running for your frontend UI?

Hi <@U04D6HREJE9> often when it has status Pending, it just means you need to hit “Run”

Hi… I was OOO
Yes I’ve tried it. It added another execution with same pending status

<@U042KCFV9GX> <@U040V3TUD5J> <@U02DZ51RCK0> guys issue still relevant. It looks like a bug from your side… how can I get rid of it?

Hi! I don’t represent AcrylData. But I see your point that it could be a bug. How do you want to solve this problem since you said you don’t have access to the pods or logs and you don’t want to delete pending ingestion tasks. 

<@U040V3TUD5J> hi hi :grin: I do have all the access &amp; I did remove &amp; recreate the ingestion. Same issue

Hi <@U04D6HREJE9>, we’re talking internally to get this prioritized, thanks! In the meantime, do you mind filing a bug report on github? CC: <@U01GCJKA8P9>

<@U042KCFV9GX> <@U01GCJKA8P9>
<https://github.com/acryldata/datahub-helm/issues/266https://github.com/acryldata/datahub-helm/issues/266>

<@U042KCFV9GX> <@U01GCJKA8P9>
The issue is still relevant
<https://github.com/acryldata/datahub-helm/issues/266|This> is the correct URL

Aviv, is your datahub-actions container up and healthy? it seems like you're kicking off a request but our ingestion system is never picking it up

<@U03BEML16LB> <@U042KCFV9GX> hi. yes, It is. The issue was caused by adding `profiling` to the ingest yaml(Redshift resource). Omitting it resolves the issue

hmm interesting.. it may be that profiling was causing your pod to run out of memory. do you know if you saw any errors like that when you were running ingestion and you never received any updates in the UI?

<@U03BEML16LB> not sure I’m getting you. What updates in the UI
I’ve executed my ingestion, for redshift resource, with the following `profiling` configuration:
```profiling:
            enabled: true
            max_workers: 3
            profile_table_level_only: false
            include_field_sample_values: false```
I’m sending  you, in private, the logs