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Slow Performance of Faceted Query with Increased Fields

TLDR John experienced slowdown in faceted queries after increasing to 1000 fields. Upgrading from 0.24.0.rcn21 to 0.24.0 improved performance. The issue was attributed to John using an ARM build on an M1 Mac.

7mo

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Feb 23, 2023 (7 months ago)

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John

04:32 PM

Hey, we have a collection with thousands (!) of fields per document where we select only a few fields at query time depending on the user. It used to have O(100) fields and performance was fine, but faceting seems to be very slow now that we have O(1000) fields and I’m trying to wrap my head around it. Do you see any reason why this should be the case? I figured that only indexing would be slow with many fields and runtime performance unaffected.

Before: ~100 fields, faceting by 8 fields with max_facet_values=100 => ~0.3 seconds
After: ~1000 fields, faceting by 8 fields with max_facet_values=100 => ~1.5 seconds (without faceting ~0.08 seconds)

04:34

John

04:34 PM

Maybe it’s fetching the entire documents somewhere and the documents are huge so it’s slow? 🤔

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Jason

05:29 PM

CC: Kishore Nallan ^

Feb 24, 2023 (7 months ago)

John

10:29 AM

Hmm, I upgraded from 0.24.0.rcn21 to 0.24.0 and got a dramatic speed-up, from 1300 ms to 140 ms, almost suspiciously fast 😄 I’ll have to look into it a bit more, but maybe there was some major change to facet computation since rcn21

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Kishore Nallan

10:32 AM

👋 Check if the default search cutoff is happening (look for the search cutoff boolean field in the response).

John

10:33 AM

I get "search_cutoff": false so doesn’t seem like it

Kishore Nallan

10:33 AM

Oh 🤔 😄

10:34

Kishore Nallan

10:34 AM

Then it's possible that some performance improvement has landed. We are always working on a stream of perf work so that's possible.

John

10:38 AM

Let’s hope that’s the case 😄

12:24

John

12:24 PM

It’s slow on 0.24.0.rcn62, which is the latest nightly build before 0.24.0, and fast on 0.24.0. Very strange. Is there something different about the nightly builds that could cause it?

Kishore Nallan

12:27 PM

Hmm no and in fact that last rcn62 build exactly became the GA build.

John

12:32 PM

It’s again slow on later builds like 0.24.1.rc4 so there’s something special about the 0.24.0 I’m running 😄

Kishore Nallan

12:34 PM

Are the counts matching?

John

12:37 PM

The facet counts are not matching but in the same ballpark, and
Fast (search_time_ms=130): found=1102, out_of=5800
Slow (search_time_ms=1361): found=945, out_of=2053

12:37

John

12:37 PM

search_cutoff=false for both

12:39

John

12:39 PM

My 0.24.0 image is larger than all the rest for some reason, it’s 926MB while all others (both before and after) are 789-798MB

Kishore Nallan

12:40 PM

This is very strange. All images are built in the same way and there has not been any changes in the build process until we cut the 0.24.0 release.

12:41

Kishore Nallan

12:41 PM

Is it possible for you to reproduce on another machine or with the Linux binary for the 0.24 release?

John

12:51 PM

Ahhhh it turns out it’s because 0.24.0 has an ARM build and I’m on a M1 Mac, whereas the others are just AMD64

Kishore Nallan

12:51 PM

Ah yes, virtualizaation at play

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