Hi all,
apologies in advance, this is going to be a long email.
I’ve been holding this back intentionally in order to be able to focus on
shipping 2.0, but now that that’s out, I feel we should talk about what’s next.
This email is separated into areas of work that I think CouchDB could improve on, some with
very concrete plans, some with rather vague ideas. I’ve been collecting these over the past
year or <strike>two</strike>five, so it’s fairly wide, but I’m sure I’m missing
things that other people find important, so please add to this list.
After the initial discussion here, I’ll move all of the individual issues to
JIRA, so we can go down our usual process.
This is basically my wish list, and I’d like this to become everyone’s wish
list, so please add what I’ve been missing. :) — Note, this isn’t a
free-for-all, only suggest things that you are prepared to see through being
shipped, from design, implementation to docs.
I don’t have a specific order for these in mind, although I have a rough idea
of what we should be doing first. Putting all of this on a roadmap is going to
be a fun future exercise for us, though :)
One last note: this doesn’t include anything on documentation or testing. I
fully expect to step our game from here on out. This list is for the technical
aspects of the project.
* * *
These are the areas of work I’ve roughly come up with that my suggestions fit
into:
- API
- Storage
- Query
- Replication
- Cluster
- Fauxton
- Releases
- Performance
- Internals
- Builds
- Features
(I’m not claiming these are any good, but it’s what I’ve got)
Let’s go.
* * *
# API
## HTTP2
I think this is an obvious first next step. Our HTTP Layer needs work, our
existing HTTP server library is not getting HTTP2 support, it’s time to attack
this head-first. I’m imagining a Cowboy[1]-based HTTP layer that calls into a
unified internals layer and everything will be rose-golden. HTTP2 support for
Cowboy is still in progress. Maybe we can help them along, or we focus on the
internals refactor first and drop Cowboy in later (not sure how feasible this
approach is, but we’ll figure this out.
In my head, we focus on this and call the result 3.0 in 6-12 months. That
doesn’t mean we *only* do this, but this will be the focus (more on this later).
There are a few fun considerations, mainly of the “avoid Python
2/3-chasm”-type. Do we re-implement the 2.0 API with all its idiosyncrasies, or
do we take the opportunity to clean things up while we are at it? If yes, how
and how long do we support the then old API? Do we manage this via different
ports? If yes, how can this me made to work for hosting services like Cloudant?
Etc. etc.
[1] https://github.com/ninenines/cowboy
## Sub-Document Operations
Currently a doc update needs the whole doc body sent to the server. There are
some obvious performance improvements possible. For the longest time, I wanted
to see if we can model sub-document operations via JSON Pointers[2]. These
would roughly allow pointing to a JSON value via a URL.
For example in this doc:
{
"_id": "123abc",
"_rev": "zyx987",
"contact": {
"name": "",
"address": {
"street": "Long Street",
"nr": 123
"zip": "12345"
}
}
An update to the zip code could look like this:
curl -X POST $SERVER/db/123abc/_jsonpointer/contact/address/zip?rev=zyx987 -d
'54321'
GET/DELETE accordingly. We could shortcut the `_jsonpointer` to just `_` if we
like the short magic.
JSONPointer can deal with nested objects and lists and works fairly well for
this type of stuff, and it is rather simple to implement (even I could do it:
https://github.com/janl/erl-jsonpointer/blob/master/src/jsonpointer.erl — This
idea is literally 5 years old, it looks like, no need to use my code if there
is anything better).
This is just a raw idea, and I’m happy to solve this any other way, if somebody
has a good approach.
[2] https://tools.ietf.org/html/rfc6901
## HTTP PATCH / JSON Diff
Another stab at a similar problem are HTTP PATCH with JSON Diff, but with the
inherent problems of JSON normalisation, I’m leaning towards the JSONPointer
variant as simpler, but I’d be open for this as well, if someone comes up with
a good approach.
## GraphQL[3]
It’s rather new, but getting good traction[4]. This would be a nice addition to
our API. Somebody might already be hacking on this ;)
[3]: http://graphql.org
[4]: http://githubengineering.com/the-github-graphql-api/
## Mango for Document Validation
The only place where we absolutely require writing JS is validate_doc_update
functions. Some security behaviour can only be enforced there. With their
inherent performance problems, I’d like to get doc validations out of the path
of the query server and would love to find a way to validate document updates
through Mango.
## Redesign Security System
Our security system is slowly grown and not coherently designed. We should
start over. I have many ideas and opinions, but they are out of scope for this.
I think everybody here agrees that we can do better. This *very likely* will
*not* include per-document ACLs as per the often stated issues with that
approach in our data model.
* * *
# Replication
This is our flagship feature of course, and there are a few things we can do
better.
## Mobile-optimised extension or new version of the protocol
The original protocol design didn’t take mobile devices into account and
through PouchDB et.al. we are now learning that there are number of downsides
to our protocol. We’ve helped a lot with introducing _bulk_get/_revs, but
that’s more a bandaid than a considered strategy ;)
That new version could also be HTTP2-only, to take advantage of the new
connection semantics there.
## Easy way to skip deletes on sync
This one is self-explanatory, mobile clients usually don’t need to sync deletes
from a year ago first. Mango filters might already get us there, maybe we can
do better.
## Sync a rolling subset
Say you always want to keep the last 90 days of email on a mobile device with
optionally back-loading older documents on user-request. It is something I
could see getting a lot of traction.
Today, this can be built on 1.x with clever use of _purge, but that’s hardly a
good experience. I don’t know if it can be done in a cluster.
## Selective Sync
There might be other criteria than “last 90 days”, so the more general solution
to this problem class would be arbitrary (e.g. client-directed) selective sync,
but this might be really hard as opposed to just very hard of the “last 90
days” one, so happy to punt on this first. But filters are generally not the
answer, especially with large data sets. Maybe proper sync from views _changes
is the answer.
## A _db_updates powered _replicator DB
Running thousands+ of replications on a server is not really resource friendly
today, we should teach the replicator to only run replication on active
databases via _db_updates. Somebody might already be looking into this one.
* * *
# Storage
## Pluggable Storage Engines
Paul Davis already showed some work on allowing multiple different storage
backends. I’d like to see this land.
## Different Storage Backends
These don’t all have to be supported by the main project, but I’d really like
to see some experimentation with different backends like LevelDB[5]/RocksDB[6],
InnoDB[7], SQLite[8] a native-erlang one that is optimised for space usage and
not performance (I don’t want to budge on safety). Similarly, it’d be fun to
see if there is a compression format that we can use as a storage backend
directly, so we get full-DB compression as opposed to just per-doc compression.
[5]: http://leveldb.org
[6]: http://rocksdb.org
[7]: https://en.wikipedia.org/wiki/InnoDB
[8]: https://www.sqlite.org
* * *
# Query
## Teach Mango JOINs and result sorting
It’s the natural path for query languages. We should make these happen. Once we
have the basics, we might even be able to find a way to compile basic SQL into
Mango, it’s going to be glorious :)
## “No-JavaScript”-mode
I’ve hinted at this above, but I’d really like a way for users to use CouchDB
productively without having to write a line of JavaScript. My main motivation
is the poor performance characteristics of the Query Server (hello CGI[9]?).
But even with one that is improved, it will always faster to do any, say
filtering or validation operations in native Erlang. I don’t know if we can
expand Mango to cover all this, and I’m not really concerned about the
specifics, as long as we get there.
Of course, for pro-users, the JS-variant will still be around.
[9]: https://en.wikipedia.org/wiki/Common_Gateway_Interface
## Query Server V2
We need to revamp the Query Server. It is hardcoded to an out-of-date version
of SpiderMonkey and we are stuck with C-bindings that barely anyone dares to
look at, let alone iterate on.
I believe the way forward is re-vamping the query server protocol to use
streaming IO instead of blocking batches like we do now, and use JS-native
implementation of the JS-side instead of C-bindings.
I’m partial to doing this straight in Node, because there is a ton of support
for things we need already, and I believe we’ve solved the isolation issues
required for secure MapReduce, but I’m happy to use any other thing as well, if
it helps.
Other benefits would be support for emerging JS features that devs will want to
use.
And we can have two modes: standalone QS like now, and embedded QS where, say,
V8 is compiled into the Erlang VM. Not everybody will want to run this, but
it’ll be neat for those who do.
* * *
# Cluster
## Rebalancing
With this we will be able to grow clusters one by one instead of hitting a wall
when eventually each shard lives on a single machine. E.g. when you add a node
to the cluster, all other nodes share 1/Nth of their data with the new node,
and everything can keep going. Same for removing a node and shrinking the
cluster.
Couchbase has this and it is really nice.
## Setup
Even without rebalancing, we need a nice Fauxton UI to manage the cluster, so
far we only have a simple setup procedure (which is great don’t get me wrong),
but users will want to do more elaborate cluster management and we should make
that easy with a slick UI.
## Cluster-Aware Clients
This might end up being not a good idea, but I’d like some experimentation
here. Say you’d have a CouchDB client that could be hooked into the cluster
topology so it’d know which nodes to query for which data, then we can save a
proxy-hop, and build clients that have lower-latency access to CouchDB. Again,
this is something that Couchbase does and I think is worth exploring.
* * *
# Fauxton
Fauxton is great, but it could be better too, I think. I’m mostly concerned
about number of clicks/taps required for more specialised actions (like setting
the group_level of a reduce query, it’s like 15 or so). More cluster info would
also be nice, and maybe a specialised dashboard for db-per-user setups.
* * *
# Releases
## Six-Week Release Trains
We need to get back to frequent releases and I propose to go back to our
six-week-release train plans from three years ago. Whatever lands within a
release train time frame goes out. The nature of the change dictates the
version number increment as per semver, and we just ship a new version every
six weeks, even if it only includes a single bug fix. We should automate most
of this infrastructure, so actual releases are cheap. We are reasonably close
with this, but we need some more folks to step up on using and maintaining our
CI systems.
## One major feature per major version
I also propose to keep the scope of future major versions small, so we don’t
have to wait another 3-5 years for 3.0. In particular, I think we should focus
on a single major feature per major version and get that shipped within 6-12
months tops. If anything needs more time, it needs to be broken up. Of course
we continue to add features and fix things while this happens, but as a
project, there is *one* major feature we push. For example, for 3.0 I see our
push be behind HTTP2 support. There is a lot of subsequent work required to
make that happen, so it’ll be a worthwhile 3.0, but we can ship it in 6-12
months (hopefully).
Best case scenario, we have CouchDB 4.0 coming out 12 months from now with two
new major features. That would be amazing.
* * *
# Performance
## Perf Team
We need a team to comprehensive look at CouchDB performance. There is a lot of
low-hanging fruit like Robert Kowalski showed a while back, we should get back
into this. I’m mostly inspired by SQLite who’ve done a release a while back
that only focussed on 1-2% performance improvements, but got like 20-30 of
those and made the thing a lot faster across the board. I can’t remember where
I read about this, but I’ll update this once I find the link.
## Benchmark Suite
We need a benchmark suite that tests a variety of different work loads. The
goal here is to run different versions of CouchDB against the same suite on the
same hardware, to see where are going. I’m imagining a http://arewefastyet.com
style dashboard where we can track this, and even run this on Pull Requests and
not allow them if they significantly impact performance.
## Synthetic Load Suite
This one is for end users. I’d like to be able to say: My app produces mostly
10-20kb-sized docs, but millions of those in a single database, or across 1000s
of databases, with these views etc. and then run this on target hardware so I’d
know, e.g. how many nodes I need for a cluster with my estimated workload. I
know this can only be done in approximation, but I think this could make a big
difference in CouchDB adoption and feed back into Perf Team mentioned above.
* * *
# Internals
## Consolidate Repositories
With 2.0 we started to experiment with radically small modules for our
components and I think we’ve come to the conclusion that some consolidation is
better for us going forward. Obvious candidates for separate repos are docs,
Fauxton etc. but also some of the Erlang modules that other projects reasonably
would use.
## Elixir
I’d like it very much if we elevate Elixir as a prime target language for
writing CouchDB internals. I believe this would get us an influx of new
developers that we badly need to get all the things I’m listing here done.
Somebody might be looking into the technical aspects of this already, but we
need to decide as a project if we are okay with that.
## GitHub Issues
I hope we can transition to GitHub Issues soon.
* * *
# Builds
I’d like automated builds for source, Docker et.al., rpm, deb, brew, ports, Mac
Binary, etc with proper release channels for people to subscribe to, all
powered by CI for nightly builds, so people can test in-development versions
easily.
I’d also like builds that include popular community plugins like Geo or
Fulltext Search.
* * *
# Features
## Better Support for db-per-user
I don’t know what this will look like, but this is a pattern, and we need to
support it better.
One approach could be “virtual dbs” that are backed by a single database, but
that’s usually at odds with views, so we could make this an XOR and disable
views on these dbs. Since this usually powers client-heavy apps, querying
usually happens there anyway.
Another approach would be better / easier cross-db aggregation or querying.
There are a few approaches, but nothing really slick.
## Schema Extraction
I have half an (old) patch that extracts top level fields from a document and
stores them with a hash in an “attachment” to the database header. So we only
end up storing doc values and the schema hash. First of all this trades storage
for CPU time (I haven’t measured anything yet), but more interestingly, we
could use that schema data to do smart things like auto-generating a validation
function / mango expression based on the data that is already in the database.
And other fun things like easier schema migration operations that are native in
CouchDB and thus a lot faster than external ones. For the curious ones, I’ve
got the idea from V8’s property access optimisation strategy[10].
[10]: https://github.com/v8/v8/wiki/Design%20Elements#fast-property-access
* * *
Alright, that’s it for now. Can’t wait for your feedback!
Best
Jan
