Hi there, I have a process that downloads thousands of files from s3 bucket, removes a set of columns from it, and upload it to s3.
S3 is currently not the bottleneck, having a Single Master Node Spark instance is the bottleneck. One approach is to distribute the files on multiple Spark Master Node workers, that will make it faster. Question: 1. Is there a way to utilize master / slave node on Spark to distribute this downloading and processing of files – so it can say do 10 files at a time? 2. Is there a way to scale workers with Spark downloading and processing files, even if they are all Single Master Node? Thanks, Bardia ________________________________________________________ The information contained in this e-mail is confidential and/or proprietary to Capital One and/or its affiliates and may only be used solely in performance of work or services for Capital One. The information transmitted herewith is intended only for use by the individual or entity to which it is addressed. If the reader of this message is not the intended recipient, you are hereby notified that any review, retransmission, dissemination, distribution, copying or other use of, or taking of any action in reliance upon this information is strictly prohibited. If you have received this communication in error, please contact the sender and delete the material from your computer.
