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https://issues.apache.org/jira/browse/BEAM-991?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15711705#comment-15711705
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Joshua Fox commented on BEAM-991:
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Daniel Halperin, unfortunately I cannot participate too much in the development
and full testing, both for the usual reason of time commitments but also
because I am not close enough to the infrastructure to fully understand what is
happening, particularly in edge cases. However, I will be glad to serve as an
early user.
My situation: I wrote a Datastore backup in Dataflow, after Google's Backup and
Managed Backup tool failed on various bugs.
However, this new tool cannot copy any Kind with Item size >20 KB (max in
Datastore is 1 MB). So, I can only use it to backup Kinds with average Item
size 10 KB (since there may be variation.) I wrote a second a simple
multithreaded but nondistributed backup tool, using "select-insert" loops. It
works, but of course is less scalable and more expensive than the Dataflow
tool. I use a combination of the Dataflow and the nondistributed tool now, for
different Kinds, but can easily switch to using just Dataflow.
> DatastoreIO Write should flush early for large batches
> ------------------------------------------------------
>
> Key: BEAM-991
> URL: https://issues.apache.org/jira/browse/BEAM-991
> Project: Beam
> Issue Type: Bug
> Components: sdk-java-gcp
> Reporter: Vikas Kedigehalli
> Assignee: Vikas Kedigehalli
>
> If entities are large (avg size > 20KB) then the a single batched write (500
> entities) would exceed the Datastore size limit of a single request (10MB)
> from https://cloud.google.com/datastore/docs/concepts/limits.
> First reported in:
> http://stackoverflow.com/questions/40156400/why-does-dataflow-erratically-fail-in-datastore-access
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