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https://issues.apache.org/jira/browse/HADOOP-17402?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17241935#comment-17241935
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Rafal Wojdyla commented on HADOOP-17402:
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[[email protected]] thanks for the links. I'm with you on the long term
vision. In the meantime tho, is there something we can do to bring GCS
connector on par with S3 (specifically the {{core-default}} config). I'm mostly
thinking of pyspark users, for whom java ecosystem may be a puzzle.
Spark/pyspark loads {{core-default}} from {{hadoop-common}}. Afaiu in pyspark
context the auto service doesn't actually register the {{gs}} scheme, so Spark
users are forced to add the config manually.
One might argue that adding the config to {{core-default}} would still result
in missing class error, but at least it would look the same as S3, and it would
save on extra config. What do you think?
> Add GCS FS impl reference to core-default.xml
> ---------------------------------------------
>
> Key: HADOOP-17402
> URL: https://issues.apache.org/jira/browse/HADOOP-17402
> Project: Hadoop Common
> Issue Type: Improvement
> Components: fs
> Reporter: Rafal Wojdyla
> Priority: Major
>
> Akin to current S3 default configuration add GCS configuration, specifically
> to declare the GCS implementation. [GCS
> connector|https://cloud.google.com/dataproc/docs/concepts/connectors/cloud-storage].
> Has this not been done since the GCS connector is not part of the hadoop/ASF
> codebase, or is there any other blocker?
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