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https://issues.apache.org/jira/browse/BEAM-7390?focusedWorklogId=361035&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-361035
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ASF GitHub Bot logged work on BEAM-7390:
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Author: ASF GitHub Bot
Created on: 17/Dec/19 18:23
Start Date: 17/Dec/19 18:23
Worklog Time Spent: 10m
Work Description: davidcavazos commented on issue #10165: [BEAM-7390] Add
code snippet for GroupIntoBatches
URL: https://github.com/apache/beam/pull/10165#issuecomment-566687297
@aaltay, from your
[comment](https://github.com/apache/beam/pull/8914#issuecomment-504609011) and
the rest of the discussion I'm gathering the following:
`BatchElements`
- Does **not** use state and timer APIs (more portable across runners that
don't support them)
- Does **not** support streaming (is this correct?)
- Can use keyed or un-keyed elements
- Supports batch auto-sizing
- Does **not** match any Java transform
`GroupIntoBatches`
- Uses state and timer APIs (can't be used in some runners)
- Supports streaming
- Must use keyed elements
- Fixed-sized batches only
- Matches the Java transform
Are these observations correct? Am I missing anything?
If so, it might be worthwhile to have samples for both transforms and have a
note on these differences in the docs, as well as a link to
[BEAM-6696](https://issues.apache.org/jira/browse/BEAM-6696) for more details.
I noticed that `GroupIntoBatches` *requires* keyed inputs, but I couldn't
figure out what the keys are used for. I used `None` keys in the sample, but it
seems cumbersome to have to add keys to use this transform.
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Issue Time Tracking
-------------------
Worklog Id: (was: 361035)
Time Spent: 8h (was: 7h 50m)
> Colab examples for aggregation transforms (Python)
> --------------------------------------------------
>
> Key: BEAM-7390
> URL: https://issues.apache.org/jira/browse/BEAM-7390
> Project: Beam
> Issue Type: Improvement
> Components: website
> Reporter: Rose Nguyen
> Assignee: David Cavazos
> Priority: Minor
> Time Spent: 8h
> Remaining Estimate: 0h
>
> Merge aggregation Colabs into the transform catalog
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