I’m pretty sure this was just upvoted because of the title.
Geosharded Recommendations with Hilbert Curve at Tinder
11–20 of 47 posts
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#12I’m pretty sure this was just upvoted because of the title.
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Re: Geosharded Recommendations with Hilbert Curve at Tinder
#13I’m pretty sure this was just upvoted because of the title.
My observation is that most upvotes are because of the title, and then a minority of people will read and critique the article in the top-voted comments.
Doesn't sound like a perfect system, but actually does a wonderful job at debunking very appealing-sounding articles.
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#14Very interesting. Used to do something similar for a project I work on. Used geohash based sharding, instead of complex curves like that. Worked great, but with recent advances in ES its no longer needed. They don't seem to mention which version of ES they are on, and would be curious how it has changed over time in their experience.
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#15a bit off-topic, it's funny you use all this fancy technology behind the scenes and your iOS app is buggy, slow and always problems with login and notifications which do not update. TLDR; Awful
"a bit"
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#16I’m pretty sure this was just upvoted because of the title.
My observation is that most upvotes are because of the title, and then a minority of people will read and critique the article in the top-voted comments. Doesn't sound like a perfect system, but actually does a wonderful job at debunking very appealing-sounding articles.
The upvote isn't for the article per see it's for the subject matter. I'm hoping to hear war stories and crtiques of Hilbert Curves vs S2 vs H3 or KD-Trees for spatial indexing.
The fun of Hacker News is hearing pros talk shop about stuff too distant from what you're working on.
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#17Sometimes it feels like Groundhog Day, behold:
https://medium.com/@buckhx/unwinding-uber-s-most-efficient-s...
tl;dr - S2 is a good library.
There's also a joke in here somewhere about bikeshedding and yak shaving.
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#18a bit off-topic, it's funny you use all this fancy technology behind the scenes and your iOS app is buggy, slow and always problems with login and notifications which do not update. TLDR; Awful
I came here to write the same thing, so have an upvote. Tinder’s iOS app is such a gigantic travesty of engineering that I’m honestly surprised to hear they have an actual engineering team.
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#19I’m pretty sure this was just upvoted because of the title.
My observation is that most upvotes are because of the title, and then a minority of people will read and critique the article in the top-voted comments. Doesn't sound like a perfect system, but actually does a wonderful job at debunking very appealing-sounding articles.
The bigger problem is when people comment and even discuss the title without reading the article. It's extremely common on Reddit but luckily less prevalent on Hacker News .
Re: Geosharded Recommendations with Hilbert Curve at Tinder
#20How big of a problem is the fact that shards constructed this way don't like crossing the "big" boundaries in the S2 curve? Especially if a high-usage location happens to straddle one of those boundaries (like, IIRC, Toronto)?
You can compute which shard to use and if you’re in a border region you just use all shards that overlap with your 100km radius.
Yeah it seems like the real bottleneck is that in these super dense areas, there might be a ton of shards in a mid-size radius. This is inevitable since in the middle of Manhattan, there are just a lot of people in a small area.
One solution would be to scale their recommendation radius with density; no need to look farther than 5 miles for true love in Manhattan, but in Wyoming you may have to drive a bit.