Regarding the caching, we would need to agree between apps and web about the url and smaxage parameter as Adam noted so that the urls are exactly the same to not bloat varnish and reuse the same cached objects across platforms.

It is an extremely adhoc and brittle solution but seems like it would be the greatest win.

20% of the traffic from searches by being only in android and web beta seems a lot to me, and we should work on reducing it, otherwise when it hits web stable we're going to crush the servers, so caching seems the highest priority.

Let's chime in https://phabricator.wikimedia.org/T124216 and continue the cache discussion there.

Regarding the validity of results with opening text only, how should we proceed? Adam?

On Wed, Jan 20, 2016 at 9:34 PM, David Causse <dcausse@wikimedia.org> wrote:

Hi,

Yes we can combine many factors, from templates (quality but also disambiguation/stubs), size and others.
Today cirrus uses mostly the number of incoming links which (imho) is not very good for morelike.
On enwiki results will also be scored according the weights defined in https://en.wikipedia.org/wiki/MediaWiki:Cirrussearch-boost-templates.

I wrote a small bash to compare results : https://gist.github.com/nomoa/93c5097e3c3cb3b6ebad
Here is some random results from the list (Semetimes better, sometimes worse) :

$ sh morelike.sh Revolution_Muslim
Defaults
        "title": "Chess",
        "title": "Suicide attack",
        "title": "Zachary Adam Chesser",
=======
Opening text no boost links
        "title": "Hungarian Revolution of 1956",
        "title": "Muslims for America",
        "title": "Salafist Front",

$ sh morelike.sh Chesser
Defaults
        "title": "Chess",
        "title": "Edinburgh",
        "title": "Edinburgh Corn Exchange",
=======
Opening text no boost links
        "title": "Dreghorn Barracks",
        "title": "Edinburgh Chess Club",
        "title": "Threipmuir Reservoir",

$ sh morelike.sh Time_%28disambiguation%29
Defaults
        "title": "Atlantis: The Lost Empire",
        "title": "Stargate",
        "title": "Stargate SG-1",
=======
Opening text no boost links
        "title": "Father Time (disambiguation)",
        "title": "The Last Time",
        "title": "Time After Time",

Le 20/01/2016 19:34, Jon Robson a écrit :

I'm actually  interested to see whether this yields better results in
certain examples where the algorithm is lacking [1]. If it's done as
an A/B test we could even measure things such as click throughs in the
related article feature (whether they go up or not)

Out of interest is it also possible to take article size and type into
account and not returning any morelike results for things like
disambiguation pages and stubs?

[1] https://www.mediawiki.org/wiki/Topic:Swsjajvdll3pf8ya


On Wed, Jan 20, 2016 at 9:47 AM, Adam Baso <abaso@wikimedia.org> wrote:

One thing we could do regarding the quality of the output is check results
against a random sample of popular articles (example approach to find some
articles) on mdot Wikipedia. Presuming that improves the quality of the
recommendations or at least does not degrade them, we should consider adding
the enhancement task to a future sprint, with further instrumentation and
A/B testing / timeboxed beta test, etc.

Joaquin, smaxage (e.g., 24 hour cached responses) does seem a good fix for
now for further reduction of client perceived wait, at least for non-cold
cache requests, even if we stop beating up the backend. Does anyone know of
a compelling reason to not do that for the time being? The main thing that
comes to mind as always is growing the Varnish cache object pool - probably
not a huge deal while the thing is only in beta, but on the stable channel
maybe noteworthy because it would run on probably most pages (but that's
what edge caches are for, after all).

Erik, from your perspective does use of smaxage relieve the backend
sufficiently?

If we do smaxage, then Web, Android, iOS should standardize their URLs so we
get more cache hits at the edge across all clients. Here's the URL I see
being used on the web today from mobile web beta:

https://en.m.wikipedia.org/w/api.php?action=query&format=json&formatversion=2&prop=pageimages%7Cpageterms&piprop=thumbnail&pithumbsize=80&wbptterms=description&pilimit=3&generator=search&gsrsearch=morelike%3ACome_Share_My_Love&gsrnamespace=0&gsrlimit=3


-Adam

On Wed, Jan 20, 2016 at 7:45 AM, Joaquin Oltra Hernandez
<jhernandez@wikimedia.org> wrote:

I'd be up to it if we manage to cram it up in a following sprint and it is
worth it.

We could run a controlled test against production with a long batch of
articles and check median/percentiles response time with repeated runs and
highlight the different results for human inspection regarding quality.

It's been noted previously that the results are far from ideal (which they
are because it is just morelike), and I think it would be a great idea to
change the endpoint to a specific one that is smarter and has some cache (we
could do much more to get relevant results besides text similarity, take
into account links, or see also links if there are, etc...).

As a note, in mobile web the related articles extension allows editors to
specify articles to show in the section, which would avoid queries to
cirrussearch if it was more used (once rolled into stable I guess).

I remember that the performance related task was closed as resolved
(https://phabricator.wikimedia.org/T121254#1907192), should we reopen it or
create a new one?

I'm not sure if we ended up adding the smaxage parameter (I think we
didn't), should we? To me it seems a no-brainer that we should be caching
this results in varnish since they don't need to be completely up to date
for this use case.

On Tue, Jan 19, 2016 at 11:54 PM, Erik Bernhardson
<ebernhardson@wikimedia.org> wrote:

Both mobile apps and web are using CirrusSearch's morelike: feature which
is showing some performance issues on our end. We would like to make a
performance optimization to it, but before we would prefer to run an A/B
test to see if the results are still "about as good" as they are currently.

The optimization is basically: Currently more like this takes the entire
article into account, we would like to change this to take only the opening
text of an article into account. This should reduce the amount of work we
have to do on the backend saving both server load and latency the user sees
running the query.

This can be triggered by adding these two query parameters to the search
api request that is being performed:

cirrusMltUseFields=yes&cirrusMltFields=opening_text


The API will give a warning that these parameters do not exist, but they
are safe to ignore. Would any of you be willing to run this test? We would
basically want to look at user perceived latency along with click through
rates for the current default setup along with the restricted setup using
only opening_text.

Erik B.

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