Re: GiST kNN search queue (Re: KNN-GiST with recheck)

From: Michael Paquier <michael(dot)paquier(at)gmail(dot)com>
To: Heikki Linnakangas <hlinnakangas(at)vmware(dot)com>
Cc: Alexander Korotkov <aekorotkov(at)gmail(dot)com>, pgsql-hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: GiST kNN search queue (Re: KNN-GiST with recheck)
Date: 2014-12-15 01:49:04
Message-ID: CAB7nPqT9n--PHbHuR_jOU_ez8dyu7ophdhrc4RD_E0g18_iCmw@mail.gmail.com
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On Thu, Dec 11, 2014 at 12:50 AM, Heikki Linnakangas
<hlinnakangas(at)vmware(dot)com> wrote:
> On 01/28/2014 04:12 PM, Alexander Korotkov wrote:
>>>
>>> >3. A binary heap would be a better data structure to buffer the
>>> > rechecked
>>> >values. A Red-Black tree allows random insertions and deletions, but in
>>> >this case you need to insert arbitrary values but only remove the
>>> > minimum
>>> >item. That's exactly what a binary heap excels at. We have a nice binary
>>> >heap implementation in the backend that you can use, see
>>> >src/backend/lib/binaryheap.c.
>>> >
>>
>> Hmm. For me binary heap would be a better data structure for KNN-GiST at
>> all :-)
>
>
> I decided to give this a shot, replacing the red-black tree in GiST with the
> binary heap we have in lib/binaryheap.c. It made the GiST code somewhat
> simpler, as the binaryheap interface is simpler than the red-black tree one.
> Unfortunately, performance was somewhat worse. That was quite surprising, as
> insertions and deletions are both O(log N) in both data structures, but the
> red-black tree implementation is more complicated.
>
> I implemented another data structure called a Pairing Heap. It's also a
> fairly simple data structure, but insertions are O(1) instead of O(log N).
> It also performs fairly well in practice.
>
> With that, I got a small but measurable improvement. To test, I created a
> table like this:
>
> create table gisttest (id integer, p point);
> insert into gisttest select id, point(random(), random()) from
> generate_series(1, 1000000) id;
> create index i_gisttest on gisttest using gist (p);
>
> And I ran this query with pgbench:
>
> select id from gisttest order by p <-> '(0,0)' limit 1000;
>
> With unpatched master, I got about 650 TPS, and with the patch 720 TPS.
> That's a nice little improvement, but perhaps more importantly, the pairing
> heap implementation consumes less memory. To measure that, I put a
> MemoryContextStats(so->queueCtx) call into gistendscan. With the above
> query, but without the "limit" clause, on master I got:
>
> GiST scan context: 2109752 total in 10 blocks; 2088456 free (24998 chunks);
> 21296 used
>
> And with the patch:
>
> GiST scan context: 1061160 total in 9 blocks; 1040088 free (12502 chunks);
> 21072 used
>
> That's 2MB vs 1MB. While that's not much in absolute terms, it'd be nice to
> reduce that memory consumption, as there is no hard upper bound on how much
> might be needed. If the GiST tree is really disorganized for some reason, a
> query might need a lot more.
>
>
> So all in all, I quite like this patch, even though it doesn't do anything
> too phenomenal. It adds a some code, in the form of the new pairing heap
> implementation, but it makes the GiST code a little bit simpler. And it
> gives a small performance gain, and reduces memory usage a bit.
Hum. It looks that this patch using binary heap is intended to be a
replacement red-black tree method. Any reason why it isn't added to
the CF to track it?
--
Michael

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