On Jul 31, 2019, at 2:02 PM, Paul Emmerich <paul.emmerich@croit.io> wrote:

we are seeing a trend towards rather large RGW S3 buckets lately.
we've worked on
several clusters with 100 - 500 million objects in a single bucket, and we've
been asked about the possibilities of buckets with several billion objects more
than once.

From our experience: buckets with tens of million objects work just fine with
no big problems usually. Buckets with hundreds of million objects require some
attention. Buckets with billions of objects? "How about indexless buckets?" -
"No, we need to list them".

A few stories and some questions:

1. The recommended number of objects per shard is 100k. Why? How was this
default configuration derived?

It doesn't really match my experiences. We know a few clusters running with
larger shards because resharding isn't possible for various reasons at the
moment. They sometimes work better than buckets with lots of shards.

So we've been considering to at least double that 100k target shard size
for large buckets, that would make the following point far less annoying.

I believe the 100,000 objects per shard was done with a little bit of experience and some back-of-the-envelope calculations. Please keep us updated as to what you find for 200,000 objects per shard.

2. Many shards + ordered object listing = lots of IO

Unfortunately telling people to not use ordered listings when they don't really
need them doesn't really work as their software usually just doesn't support
that :(

We are exploring sharding schemes that maintain ordering, and that would really help here.

A listing request for X objects will retrieve up to X objects from each shard
for ordering them. That will lead to quite a lot of traffic between the OSDs
and the radosgw instances, even for relatively innocent simple queries as X
defaults to 1000 usually.

What you say is correct. And it gets worse, because we have to go through all the returned lists and select the, say, 1000 earliest to return. And then we throw the rest away.

Simple example: just getting the first page of a bucket listing with 4096
shards fetches around 1 GB of data from the OSD to return ~300kb or so to the
S3 client.

Correct.

I've got two clusters here that are only used for some relatively low-bandwidth
backup use case here. However, there are a few buckets with hundreds of millions
of objects that are sometimes being listed by the backup system.

The result is that this cluster has an average read IO of 1-2 GB/s, all going
to the index pool. Not a big deal since that's coming from SSDs and goes over
80 Gbit/s LACP bonds. But it does pose the question about scalability
as the user-
visible load created by the S3 clients is quite low.

3. Deleting large buckets

Someone accidentaly put 450 million small objects into a bucket and only noticed
when the cluster ran full. The bucket isn't needed, so just delete it and case
closed?

Deleting is unfortunately far slower than adding objects, also
radosgw-admin leaks
memory during deletion: https://tracker.ceph.com/issues/40700

Increasing --max-concurrent-ios helps with deletion speed (option does effect
deletion concurrency, documentation says it's only for other specific commands).

Since the deletion is going faster than new data is being added to that cluster
the "solution" was to run the deletion command in a memory-limited cgroup and
restart it automatically after it gets killed due to leaking.

That tracker is being investigated.

How could the bucket deletion of the future look like? Would it be possible
to put all objects in buckets into RADOS namespaces and implement some kind
of efficient namespace deletion on the OSD level similar to how pool deletions
are handled at a lower level?

I’ll raise that with other RGW developers. I’m unfamiliar with how RADOS namespaces are handled.

4. Common prefixes could filtered in the rgw class on the OSD instead
of in radosgw

Consider a bucket with 100 folders with 1000 objects in each and only one shard

/p1/1, /p1/2, ..., /p1/1000, /p2/1, /p2/2, ..., /p2/1000, ... /p100/1000

Now a user wants to list / with aggregating common prefixes on the
delimiter / and
wants up to 1000 results.
So there'll be 100 results returned to the client: the common prefixes
p1 to p100.

How much data will be transfered between the OSDs and radosgw for this request?
How many omap entries does the OSD scan?

radosgw will ask the (single) index object to list the first 1000 objects. It'll
return 1000 objects in a quite unhelpful way: /p1/1, /p1/2, ...., /p1/1000

radosgw will discard 999 of these and detect one common prefix and continue the
iteration at /p1/\xFF to skip the remaining entries in /p1/ if there are any.
The OSD will then return everything in /p2/ in that next request and so on.

So it'll internally list every single object in that bucket. That will
be a problem
for large buckets and having lots of shards doesn't help either.

This shouldn't be too hard to fix: add an option "aggregate prefixes" to the RGW
class method and duplicate the fast-forward logic from radosgw in
cls_rgw. It doesn't
even need to change the response type or anything, it just needs to
limit entries in
common prefixes to one result.
Is this a good idea or am I missing something?

On the face it looks good. I’ll raise this with other RGW developers. I do know that there was a related bug that was recently addressed with this pr:

https://github.com/ceph/ceph/pull/28192

But your suggestion seems to go farther.

IO would be reduced by a factor of 100 for that particular
pathological case. I've
unfortunately seen a real-world setup that I think hits a case like that.

Thank you for sharing your experiences and your ideas.