Most obviously, you don’t need to move all components of the sstable to s3, you could keep index + compression offsets locally.
On Mar 4, 2025, at 1:46 PM, Štefan Miklošovič <smikloso...@apache.org> wrote:
I don't say that using remote object storage is useless.
I am just saying that I don't see the difference. I have not measured that but I can imagine that s3 mounted would use, under the hood, the same calls to s3 api. How else would it be done? You need to talk to remote s3 storage eventually anyway. So why does it matter if we call s3 api from Java or by other means from some "s3 driver"? It is eventually using same thing, no? Mounting an s3 bucket as a directory is an easy but poor implementation of object backed storage for databases
Object storage is durable (most data loss is due to bugs not concurrent hardware failures), cheap (can 5-10x cheaper) and ubiquitous. A huge number of modern systems are object-storage-only because the approximately infinite scale / cost / throughput tradeoffs often make up for the latency.
Outright dismissing object storage for Cassandra is short sighted - it needs to be done in a way that makes sense, not just blindly copying over the block access patterns to object.
I do not think we need this CEP, honestly. I don't want to diss this unnecessarily but if you mount a remote storage locally (e.g. mounting s3 bucket as if it was any other directory on node's machine), then what is this CEP good for?
Not talking about the necessity to put all dependencies to be able to talk to respective remote storage to Cassandra's class path, introducing potential problems with dependencies and their possible incompatibilities / different versions etc ... I’d love to see this implemented — where “this” is a proxy for some notion of support for remote object storage, perhaps usable by compaction strategies like TWCS to migrate data older than a threshold from a local filesystem to remote object.
It’s not an area where I can currently dedicate engineering effort. But if others are interested in contributing a feature like this, I’d see it as valuable for the project and would be happy to collaborate on design/architecture/goals.
– Scott Is anyone else interested in continuing to discuss this topic? I discussed this offline with Claude, he is no longer working on this.
It's a pity. I think this is a very valuable thing. Commitlog's archiving and restore may be able to use the relevant code if it is completed.
Thanks for reviving this one!
Is there any update on this topic? It seems that things can make a big progress if Jake Luciani can find someone who can make the FileSystemProvider code accessible. At a high level I really like the idea of being able to better leverage cheaper storage especially object stores like S3.
One important thing though - I feel pretty strongly that there's a big, deal breaking downside. Backups, disk failure policies, snapshots and possibly repairs would get more complicated which haven't been particularly great in the past, and of course there's the issue of failure recovery being only partially possible if you're looking at a durable block store paired with an ephemeral one with some of your data not replicated to the cold side. That introduces a failure case that's unacceptable for most teams, which results in needing to implement potentially 2 different backup solutions. This is operationally complex with a lot of surface area for headaches. I think a lot of teams would probably have an issue with the big question mark around durability and I probably would avoid it myself.
On the other hand, I'm +1 if we approach it something slightly differently - where _all_ the data is located on the cold storage, with the local hot storage used as a cache. This means we can use the cold directories for the complete dataset, simplifying backups and node replacements.
For a little background, we had a ticket several years ago where I pointed out it was possible to do this *today* at the operating system level as long as you're using block devices (vs an object store) and LVM [1]. For example, this works well with GP3 EBS w/ low IOPS provisioning + local NVMe to get a nice balance of great read performance without going nuts on the cost for IOPS. I also wrote about this in a little more detail in my blog [2]. There's also the new mount point tech in AWS which pretty much does exactly what I've suggested above [3] that's probably worth evaluating just to get a feel for it.
I'm not insisting we require LVM or the AWS S3 fs, since that would rule out other cloud providers, but I am pretty confident that the entire dataset should reside in the "cold" side of things for the practical and technical reasons I listed above. I don't think it massively changes the proposal, and should simplify things for everyone.
Jon
Is there still interest in this? Can we get some points down on electrons so that we all understand the issues?
While it is fairly simple to redirect the read/write to something other than the local system for a single node this will not solve the problem for tiered storage.
Tiered storage will require that on read/write the primary key be assessed and determine if the read/write should be redirected. My reasoning for this statement is that in a cluster with a replication factor greater than 1 the node will store data for the keys that would be allocated to it in a cluster with a replication factor = 1, as well as some keys from nodes earlier in the ring.
Even if we can get the primary keys for all the data we want to write to "cold storage" to map to a single node a replication factor > 1 means that data will also be placed in "normal storage" on subsequent nodes.
To overcome this, we have to explore ways to route data to different storage based on the keys and that different storage may have to be available on _all_ the nodes.
Have any of the partial solutions mentioned in this email chain (or others) solved this problem?
Claude
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