The very short form is that from Solr 6.6.1 to Solr 8.3.1, the throughput for 
date boosting in my tests dropped by 40+%

I’ve been hearing about slowdowns in successive Solr releases with boost 
functions, so I dug into it a bit. The test setup is just a boost-by-date with 
an additional big OR clause of 100 random words so I’d be sure to hit a bunch 
of docs. I figured that if there were few hits, the signal would be lost in the 
noise, but I didn’t look at the actual hit counts.

I saw several Solr JIRAs about this subject, but they were slightly different, 
although quite possibly the same underlying issue. So I tried to get this down 
to a very specific form of a query.

I’ve also seen some cases in the wild where the response was proportional to 
the number of segments, thus my optimize experiments.

Here are the results, explanation below. O stands for optimized to one segment. 
I spot checked pdate against 7x and 8x and they weren’t significantly different 
performance wise from tdate. All have docValues enabled. I ran these against a 
multiValued=“false” field. All the tests pegged all my CPUs. Jmeter is being 
run on a different machine than Solr. Only one Solr was running for any test.

Solr version   queries/min   
6.6.1              3,400          
6.6.1 O           4,800          

7.1                 2,800           
7.1 O             4,200           

7.7.1              2,400           
7.7.1 O          3,500            

8.3.1             2,000            
8.3.1 O          2,600            


The tests I’ve been running just index 20M docs into a single core, then run 
the exact same 10,000 queries against them from jmeter with 24 threads. Spot 
checks showed no hits on the queryResultCache.

A query looks like this: 
rows=0&{!boost b=recip(ms(NOW, 
INSERT_FIELD_HERE),3.16e-11,1,1)}text_txt:(campaigners OR adjourned OR 
anyplace…97 more random words)

There is no faceting. No grouping. No sorting.

I fill in INSERT_FIELD_HERE through jmeter magic. I’m running the exact same 
queries for every test.

One wildcard is that I did regenerate the index for each major revision, and 
the chose random words from the same list of words, as well as random times 
(bounded in the same range though) so the docs are not completely identical. 
The index was in the native format for that major version even if slightly 
different between versions. I ran the test once, then ran it again after 
optimizing the index.

I haven’t dug any farther, if anyone’s interested I can throw a profiler at, 
say, 8.3 and see what I can see, although I’m not going to have time to dive 
into this any time soon. I’d be glad to run some tests though. I saved the 
queries and the indexes so running a test would  only take a few minutes.

While I concentrated on date fields, the docs have date, int, and long fields, 
both docValues=true and docValues=false, each variant with multiValued=true and 
multiValued=false and both Trie and Point (where possible) variants as well as 
a pretty simple text field.

Erick



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