Probably good to take a quick step back and note that FoundationDB’s
versionstamps are an elegant and scalable solution to atomically maintaining
the index of documents in the order in which they were most recently updated. I
think that’s what you mean by the first part of the problem, but I want to make
sure that on the ML here we collectively understand that FoundationDB actually
nails this hard part of the problem *really* well.
When you say “notify CouchDB about new updates”, are you referring to the
feed=longpoll or feed=continuous options to the _changes API? I guess I see
three different routes that can be taken here.
One route is to use the same kind machinery that we have in place today in
CouchDB 2.x. As a reminder, the way this works is
- a client waiting for changes on a DB spawns one local process and also a
rexi RPC process on each node hosting one of the DB shards of interest (see
fabric_db_update_listener).
- those RPC processes register as local couch_event listeners, where they
receive {db_updated, ShardName} messages forwarded to them from the
couch_db_updater processes.
Of course, in the FoundationDB design we don’t need to serialize updates in
couch_db_updater processes, but individual writers could just as easily fire
off those db_updated messages. This design is already heavily optimized for
large numbers of listeners on large numbers of databases. The downside that I
can see is it means the *CouchDB layer nodes would need to form a distributed
Erlang cluster* in order for them to learn about the changes being committed
from other nodes in the cluster.
So let’s say we *didn’t* want to do that and we rather are trying to design for
completely independent layer nodes that have no knowledge of or communication
with one another save through FoundationDB. There’s definitely something to be
said for that constraint. One very simple approach might be to just poll
FoundationDB. If the database is under a heavy write load there’s no overhead
to this approach; every time we finish sending the output of one range query
against the versionstamp space and we re-acquire a new read version there will
be new updates to consume. Where it gets inefficient is if we have a lot of
listeners on the feed and a very low-throughput database. But one fiddle with
polling intervals, or else have a layer of indirection so only one process on
each layer node is doing the polling and then sending events to couch_event. I
think this could scale quite far.
The other option (which I think is the one you’re homing in on) is to leverage
FoundationDB’s watchers to get a push notification about updates to a
particular key. I would be cautious about creating a specific key or set of
keys specifically for this purpose, but, if we find that there’s some other bit
of metadata that we are needing to maintain anyway then this could work nicely.
I think same indirection that I described above (where each layer node has a
maximum of one watcher per database, and it re-broadcasts messages to all
interested clients via couch_event) would help us not be too constrained by the
limit on watches.
So to recap, the three approaches
1. Writers publish db_updated events to couch_event, listeners use distributed
Erlang to subscribe to all nodes
2. Poll the _changes subspace, scale by nominating a specific process per node
to do the polling
3. Same as #2 but using a watch on DB metadata that changes with every update
instead of polling
Adam
> On Feb 4, 2019, at 2:18 PM, Ilya Khlopotov <iil...@apache.org> wrote:
>
> One of the features of CouchDB, which doesn't map cleanly into FoudationDB is
> changes feed. The essence of the feature is:
> - Subscriber of the feed wants to receive notifications when database is
> updated.
> - The notification includes update_seq for the database and list of changes
> which happen at that time.
> - The change itself includes docid and rev.
> Hi,
>
> There are multiple ways to easily solve this problem. Designing a scalable
> way to do it is way harder.
>
> There are at least two parts to this problem:
> - how to structure secondary indexes so we can provide what we need in
> notification event
> - how to notify CouchDB about new updates
>
> For the second part of the problem we could setup a watcher on one of the
> keys we have to update on every transaction. For example the key which tracks
> the database_size or key which tracks the number of documents or we can add
> our own key. The problem is at some point we would hit a capacity limit for
> atomic updates of a single key (FoundationDB doesn't redistribute the load
> among servers on per key basis). In such case we would have to distribute the
> counter among multiple keys to allow FoundationDB to split the hot range.
> Therefore, we would have to setup multiple watches. FoundationDB has a limit
> on the number of watches the client can setup (100000 watches). So we need to
> keep in mind this number when designing the feature.
>
> The single key update rate problem is very theoretical and we might ignore it
> for the PoC version. Then we can measure the impact and change design
> accordingly. The reason I decided to bring it up is to see maybe someone has
> a simple solution to avoid the bottleneck.
>
> best regards,
> iilyak
