S3st: Stream data from multiple S3 objects directly into your terminal | Hacker News Reader

S3st: Stream data from multiple S3 objects directly into your terminal

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61 pointsloige19 comments

You can also acomplish this with shell:

export BUCKET=____; aws s3 ls "$BUCKET" | tail -n+2 | awk '{print $4}' | while read k; do aws s3 cp "s3://$BUCKET/$k" -; done

I especially like the "done" (!) at end :) Thanks for this one-liner!

Cool. I had a similar use case and created a tool to stream colorized logs from CloudWatch to your terminal that is a little more ergonomic to use than this:

https://github.com/TylerBrock/saw

I didn't know saw! It looks very very cool, and it's written in go! Thanks for (making and) sharing this!

One thing to be careful of with this is the Data Transfer (egress) cost you will incur streaming data out from S3.

If you're just wanting to do a 'grep' style action on an S3 prefix, might be worth looking into "S3 Select"for your use case instead

Very good point, this is probably worth mentioning in the README. I'll add a note there for sure!

Pretty neat. I'm working on a product that relies heavily on S3 buckets and tagged files.

Does s3st support tags or other ways of identifying which files to stream other than filtering by the content of the files? Asking because I didn't see this feature in the demo.

It doesn't. It only supports a prefix to filter out objects. I am happy to get PRs for this kind of features if you have a use case!

Copy that. I’ll take a look.

What are the advantages of this over a shell pipeline with aws-cli?

Or, what is the advantage over mounting the s3 bucket as a local filesystem with s3fs[1] or rclone mount[2] ?

[1] https://github.com/s3fs-fuse/s3fs-fuse

[2] https://rclone.org/commands/rclone_mount/

If your s3 bucket is huge, that's probably not a good idea. Most likely, the use case here is streaming and search for tagged data within a very large s3 dataset.

...or MinIO's mc (which is a single executable)?

We have a large s3 bucket 2 billions objects and we start thinking about cleaning it a bit. Is anyone had done such things or any tools on :

- categorising what's inside

- checking what's used or not

Thanks!

The first step would be figuring out what's in there, so maybe look at Glue[1] and see if it can determine your existing schema.

But usually you need to run run arbitrary code against the contents of a large S3 bucket, and that gets tricky. The main problem is tracking what you've done vs. what you need to do, because if you haven't categorized your data yet, you can expect that code processing it will break.

One technique is queues in SQS:

1. Keys to process

2. Keys that succeeded

3. Keys that failed

(Regular queues, FIFO queues probably won't be useful. A queue can have an unlimited backlog, but the maximum message timeout is two weeks. That's probably more than enough time to iterate over some code in Lambda.)

Your initial lambda should be triggered by KeysToProcess, which you can initiate off a developer machine and just run ListBucket and create a pile of messages.

When the lambda is done, it passes its information to KeysThatSucceeded. (Or possibly another S3 bucket, or Dynamo, or a database, or just drop its key if you determine you don't need it.)

Point your dead letter queue to KeysThatFailed. Let the messages pile up in there until you've figured out the errors and are ready to try again.

And then you can trigger off KeysThatFailed, point the dead letter queue at a new KeysThatFailed2, rinse, repeat until you're satisfied it's correct.

[1]: https://aws.amazon.com/glue/

https://docs.aws.amazon.com/AmazonS3/latest/dev/storage-inve...

S3 Inventory is basically designed for your use case. It effectively writes a full-bucket index every day.

Relatedly, I'm curious how people are handling local backups with large S3 buckets?

I've been using AWS CLI sync, but it's getting increasingly slow. To the point that it seems untenable.

What are the potential use cases?

There's one in the example (streaming from multiple cloudtrail files and grepping on the resulting stream)

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