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This repository has been archived by the owner on Jul 19, 2024. It is now read-only.
Which service(blob, file, queue, table) does this issue concern?
blob
Which version of the SDK was used?
Please note that if your issue is with v11, we are recommending customers either move back to v11 or move to v12 (currently in preview) if at all possible. Hopefully this resolves your issue, but if there is some reason why moving away from v11 is not possible at this time, please do continue to ask your question and we will do our best to support you. The README for this SDK has been updated to point to more information on why we have made this decision.
Storage SDK v8 for Java:
com.microsoft.azure
azure-storage
8.6.6
What problem was encountered?
I tried to use this SDK in our spark based code. Any task that is executed on top of a Dataframe/RDD will be serialized and sent to spark executors. As StorageCredentials and other blob related classes are not serializable, spark couldn't use them to upload/download files to azure file storage in parallel.
Have you found a mitigation/solution?
No
The text was updated successfully, but these errors were encountered:
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Which service(blob, file, queue, table) does this issue concern?
blob
Which version of the SDK was used?
Please note that if your issue is with v11, we are recommending customers either move back to v11 or move to v12 (currently in preview) if at all possible. Hopefully this resolves your issue, but if there is some reason why moving away from v11 is not possible at this time, please do continue to ask your question and we will do our best to support you. The README for this SDK has been updated to point to more information on why we have made this decision.
Storage SDK v8 for Java:
com.microsoft.azure
azure-storage
8.6.6
What problem was encountered?
I tried to use this SDK in our spark based code. Any task that is executed on top of a Dataframe/RDD will be serialized and sent to spark executors. As StorageCredentials and other blob related classes are not serializable, spark couldn't use them to upload/download files to azure file storage in parallel.
Have you found a mitigation/solution?
No
The text was updated successfully, but these errors were encountered: