How to download and upload multiple files from Amazon AWS S3 buckets

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This process can take several minutes. Upload the file in multiple parts using low-level aws s3api commands Important: This aws s3api procedure should be used only when aws s3 commands don't support a specific upload need, such as when the multipart upload involves multiple servers, a multipart upload is being manually stopped and resumed, or when the aws s3 command doesn't support a required request parameter. In this post, I will give a on uploading large files to Amazon S3 with the aws command line tool. The -L option will follow the redirect for you.

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AWS S3 File

Hi everyone, I have a bucket that has a large number of small files that I need to rename from a flat file structure aws s3 cp multiple files a nested one based on the original file names. Each file is about ~200 kb. Is this a terrible approach. Assuming that this is a one-time thing and I can spend a bit of money to make this happen faster, is there a better way to go about this. Edit: to be clear, aws cannot have the new filename depend on a pattern. You can select which files to include in a move statement with a pattern, of course, but I'm really more concerned with renaming things. Are you wanting to do this with a single regex. Just listing all of the items in my bucket takes hours. Submitting one request for each of the ~10 7 items is going to take a very long time with latency of a second per call. To be specific I need to move tens of millions of files that are in one flat folder and move them to folders based on the values of the string after their last underscore. This will be suboptimal on the client side. After a while Amazon starts rate-limiting your aws requests. The way I got around it was to code a user-defined parameter, where the user can specify how many seconds to pause after a certain amount of requests. Additionally, I created a temporary farm, where I downloaded the list of files, use the linux 'split' command to evenly divide the resulting list amongst X amount of servers, ship them out and kick off the process on each farm node with rate-limit awareness. Complex I know, but my situation was different: the task was to transcode audio files using ffmpeg and reupload whilst saving metadata for each file. Any kind of sync will be burning money on unneeded transfers. Until you have numbers to tell you otherwise, think of this as a multithreaded relatively simple task. One thread should paginate through list-objects, building a simple work list of files that still need moving. One or more threads should now consume this list and rename files as required, updating the work list to mark objects as complete. The stats from how quickly you can list and how quickly you can consume will tell you if adding more threads to either side will help. Your code can cope with this and adjust threads on demand. To be honest, a self scaling bit of parallel python code should soon give you a good feel as to what your scaling or time limiting factors are. If it comes back as less than a few minutes, add a zero to the end of the number of files in the test batch. Divide by the number of files in your test aws s3 cp multiple files and multiply by the total number of files you have - this new time is roughly the time the whole thing will take. Divide by the number of instances you are willing to use in order get roughly how long it will take you. Remember that instances take time to start up and be assigned a batch.

When you use this option, S3 Browser calculates the hash of downloaded file and compares it with the hash provided by Amazon S3, if they do not match, returns an error. I'm not sure if the resolved bandwidth issue could help this one. Have a question about this project? It would be great if s3 cp command accepts multiple sources just like bash cp command. GitHub will remain the channel for reporting bugs. Any kind of sync will be burning money on unneeded transfers.