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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2019/10/15 00:58:00 UTC
[jira] [Work logged] (BEAM-8367) Python BigQuery sink should use
unique IDs for mode STREAMING_INSERTS
[ https://issues.apache.org/jira/browse/BEAM-8367?focusedWorklogId=328238&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-328238 ]
ASF GitHub Bot logged work on BEAM-8367:
----------------------------------------
Author: ASF GitHub Bot
Created on: 15/Oct/19 00:57
Start Date: 15/Oct/19 00:57
Worklog Time Spent: 10m
Work Description: pabloem commented on pull request #9797: [BEAM-8367] Using insertId for BQ streaming inserts
URL: https://github.com/apache/beam/pull/9797
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Issue Time Tracking
-------------------
Worklog Id: (was: 328238)
Remaining Estimate: 0h
Time Spent: 10m
> Python BigQuery sink should use unique IDs for mode STREAMING_INSERTS
> ---------------------------------------------------------------------
>
> Key: BEAM-8367
> URL: https://issues.apache.org/jira/browse/BEAM-8367
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Chamikara Madhusanka Jayalath
> Assignee: Pablo Estrada
> Priority: Major
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Unique IDs ensure (best effort) that writes to BigQuery are idempotent, for example, we don't write the same record twice in a VM failure.
>
> Currently Python BQ sink insert BQ IDs here but they'll be re-generated in a VM failure resulting in data duplication.
> [https://github.com/apache/beam/blob/master/sdks/python/apache_beam/io/gcp/bigquery.py#L766]
>
> Correct fix is to do a Reshuffle to checkpoint unique IDs once they are generated, similar to how Java BQ sink operates.
> [https://github.com/apache/beam/blob/dcf6ad301069e4d2cfaec5db6b178acb7bb67f49/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/StreamingWriteTables.java#L225]
>
> Pablo, can you do an initial assessment here ?
> I think this is a relatively small fix but I might be wrong.
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