Earlier quoted context omitted.
"Checksum-all-the-things is a basic feature of a lot of file systems" "A lot"? Does anything but ZFS and maybe btrfs do this? Ext4 anf XFS — two very common filesystems — still don't have data checksums.
Bcachefs, and LVM also has a way to do it. Unfortunately I’m not aware of any filesystem that does it while maintaining the full bandwidth of a modern NVMe. Not even with the extra reads factored in; on ZFS I get 800 MB/s max.
S3 is files, but not a filesystem
401–410 of 456 posts
Re: S3 is files, but not a filesystem
#402Earlier quoted context omitted.
For AWS, we're comparing against filesystems in the datacenter - so EBS, EFS and FSx Lustre. Compared to these, you can see in the graphs where S3 is much faster for workloads with big files and small files: https://cuno.io/technology/ and in even more detail of different types of EBS/EFS/FSx Lustre here: https://cuno.io/blog/making-the-right-choice-comparing-the-c...
EFS is ridiculously slow though. Almost to the point where I fail to see how it’s actually useful for any of the traditional use cases for NFS.
Re: S3 is files, but not a filesystem
#403Earlier quoted context omitted.
What is it about S3 that enables this speed, and why can’t traditional Unix file systems do the same?
S3 doesn’t have directories, it could be thought of a flat + sorted list of keys. UNIX (and all operating systems) differentiate between a file and a directory. To list the contents of a directory, you need to make an explicit call. That call might return files or directories. So to list all files recursively, you need to list, sort, check if an entry is a directory, recurse”. This isn’t great.
Anyway, I guess this is beyond the point of the original commenter above. I would disagree that listing files efficiently is the most useful part of S3. The main value prop is the fact that you can easily upload and download files from a distributed store. Most use cases involve uploading and downloading known files, not efficiently listing millions of files.
[1] https://jvns.ca/blog/2015/03/05/how-the-locate-command-works...
Re: S3 is files, but not a filesystem
#404> And listing files is slow. While the joy of Amazon S3 is that you can read and write at extremely, extremely, high bandwidths, listing out what is there is much much slower. Slower than a slow local filesystem This misses something critical. Yes, s3 has fast reading and writing, but that’s not really what makes it useful . What makes it useful is listing. In an unversioned bucket (or one with no delete markers), li…
And if for some reason you need a complete listing along with object sizes and other attributes you can get one every 24 hours with S3 inventory report. That has always been good enough for me.
Re: S3 is files, but not a filesystem
#405Re: S3 is files, but not a filesystem
#406Earlier quoted context omitted.
We liked B2 but not enough to pay for IPv4 addresses, insane they advertise as a multi-cloud solution but basically kill any chance at adoption when NAT gateways and IPv4 charges are everywhere. We would literally save money paying B2 bandwidth fees (high read low write) but not when being pushed through a NAT64 gateway, or paying an hourly charge just to be able to access B2.
How could they launch a cloud service like this and not have IPv6 in 2015? What other basic things did they cheap out on?
Re: S3 is files, but not a filesystem
#407Earlier quoted context omitted.
"Even though the file API handles all those concerns, but it doesn't expose them to you. A narrow interface handling a large number of concerns - that makes the unix file API a "deep" module." Both sentences here are incomplete, incoherent. I did not read past this point.
Thanks. I take your point on the first one and have corrected it (maybe you need to shift+F5 to bust your cache in order to see it). For the second one, what's your objection? That it's fragmentary?
Re: S3 is files, but not a filesystem
#408Earlier quoted context omitted.
When I worked at Google in storage, we had our own figures of merit that showed that we were the best and Amazon's durability was trash in comparison to us. As far as I can tell, every cloud provider's object store is too durable to actually measure ("14 9's"), and it's not a problem.
9's are overblown. When cloud providers report that, they're really saying "Assuming random hard drive failure at the rates we've historically measured and how we quickly we detect and fix those failures, what's the mean time to data loss". But that's burying the lede. By far the greatest risks to a file's durability are: 1. Bugs (which aren't captured by a durability model). This is mitigated by deploying slowly and…
-1. government, the historical cause of most data loss
1½. google canceling the product and deleting all the data, as they did with google+
Re: S3 is files, but not a filesystem
#409Earlier quoted context omitted.
S3 is better for large datasets. It's cheaper and handles large file sizes with ease. It has become a de-facto standard for distributed, data-intensive workloads like those common with spark. A key benefit is decoupling the data from the compute so that they can scale independently. EBS is tightly coupled to iops and you pay extra for that. (Source: a long time working in data engineering)
Yes and I also believe: Experienced Spark / Data Engineering teams would not assume S3 is readily useable as a filesystem. This [1] seems like a good guide on how to configure spark for working with Cloud object stores, while recognizing the limitations and pitfalls. [1]: https://spark.apache.org/docs/latest/cloud-integration.html --- Amazon EMR offers a managed way to run hadoop or spark clusters and it implements a…
The problem that emrfs is trying to solve doesn't cover the rdbms scenarios like row-level updates and deletes.