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it would be more performance efficient if redshift_to_pandas first writes to S3 and then reads it from there.
redshift_to_pandas
redshift_to_pandas reads over wire directly connecting to redshift
If there is large dataset ( >100 million rows) being downloaded, redshift's one thread is occupied in serving this user.
The text was updated successfully, but these errors were encountered:
It sounds like a separate concern. If you are using Python >= 3.6 you can try https://github.com/yaojiach/red-panda/blob/master/red_panda/red_panda.py#L664
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the syntax from the redshift side shouldn't be too hard to integrate. https://docs.aws.amazon.com/redshift/latest/dg/t_Unloading_tables.html
Will look into this.
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Expected Behaviour
it would be more performance efficient if
redshift_to_pandas
first writes to S3 and then reads it from there.Actual Behaviour
redshift_to_pandas
reads over wire directly connecting to redshiftImplications
If there is large dataset ( >100 million rows) being downloaded, redshift's one thread is occupied in serving this user.
The text was updated successfully, but these errors were encountered: