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As mentioned by Tulio Alberto in comments, Amazon SageMaker Data Wrangler (the graphical data preparation feature inside Amazon SageMaker) is separate from AWS Data Wrangler (an open-source data prep utility published by AWS Labs): The two tools are based on different technologies and don't necessarily aim for full feature parity - they just happen to share similar names.
To my knowledge there's no committed timeline we can share at the moment for when these particular features will make it to SageMaker Data Wrangler, but I think as feature requests they make sense and the reasoning for both is pretty clear: I'm aware that both have been discussed to some extent internally already, and I'd personally like to see them launch too!
Thanks for sharing the feedback, and apologies for the naming confusion!
Hi Tulio, thanks for the clarification. But doesn't SageMaker Data Wrangler generate code that complies with/uses AWS Data Wrangler? Isn't there some (if tenuous) connection between the two?
Hi zzzz - Tulio is correct here: AWS DW and SageMaker DW aren't really related and are certainly not feature-matched... They just happen to share the 'data wrangler' name. Sorry for the confusion!
Hi,
SageMaker Data Wrangler in Studio just launched the JSON/ORC support and we support import files under a prefix already. Please see the following links
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- 已提問 6 個月前
AWS 官方已更新 6 個月前- AWS 官方已更新 1 年前
These two have no relation whatsoever. SageMaker Data Wrangler is a UI feature inside SageMaker Studio to accelerate your data cleaning/processing. AWS Data Wrangler is an open-source Python library to load different AWS sources, such S3, Athena or Redshift, directly into pandas.