Re: [PoC] Improve dead tuple storage for lazy vacuum - Mailing list pgsql-hackers

From Masahiko Sawada
Subject Re: [PoC] Improve dead tuple storage for lazy vacuum
Date
Msg-id CAD21AoD3w76wERs_Lq7_uA6+gTaoOERPji+Yz8Ac6aui4JwvTg@mail.gmail.com
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In response to Re: [PoC] Improve dead tuple storage for lazy vacuum  (John Naylor <john.naylor@enterprisedb.com>)
Responses Re: [PoC] Improve dead tuple storage for lazy vacuum
Re: [PoC] Improve dead tuple storage for lazy vacuum
Re: [PoC] Improve dead tuple storage for lazy vacuum
List pgsql-hackers
On Mon, Aug 15, 2022 at 10:39 PM John Naylor
<john.naylor@enterprisedb.com> wrote:
>
> On Mon, Aug 15, 2022 at 12:39 PM Masahiko Sawada <sawada.mshk@gmail.com> wrote:
> >
> > On Fri, Jul 22, 2022 at 10:43 AM Masahiko Sawada <sawada.mshk@gmail.com> wrote:
> > >
> > > On Tue, Jul 19, 2022 at 1:30 PM John Naylor
> > > <john.naylor@enterprisedb.com> wrote:
> > > >
> > > >
> > > >
> > > > On Tue, Jul 19, 2022 at 9:11 AM Masahiko Sawada <sawada.mshk@gmail.com> wrote:
> > > >
> > > > > I’d like to keep the first version simple. We can improve it and add
> > > > > more optimizations later. Using radix tree for vacuum TID storage
> > > > > would still be a big win comparing to using a flat array, even without
> > > > > all these optimizations. In terms of single-value leaves method, I'm
> > > > > also concerned about an extra pointer traversal and extra memory
> > > > > allocation. It's most flexible but multi-value leaves method is also
> > > > > flexible enough for many use cases. Using the single-value method
> > > > > seems to be too much as the first step for me.
> > > > >
> > > > > Overall, using 64-bit keys and 64-bit values would be a reasonable
> > > > > choice for me as the first step . It can cover wider use cases
> > > > > including vacuum TID use cases. And possibly it can cover use cases by
> > > > > combining a hash table or using tree of tree, for example.
> > > >
> > > > These two aspects would also bring it closer to Andres' prototype, which 1) makes review easier and 2) easier
topreserve optimization work already done, so +1 from me. 
> > >
> > > Thanks.
> > >
> > > I've updated the patch. It now implements 64-bit keys, 64-bit values,
> > > and the multi-value leaves method. I've tried to remove duplicated
> > > codes but we might find a better way to do that.
> > >
> >
> > With the recent changes related to simd, I'm going to split the patch
> > into at least two parts: introduce other simd optimized functions used
> > by the radix tree and the radix tree implementation. Particularly we
> > need two functions for radix tree: a function like pg_lfind32 but for
> > 8 bits integers and return the index, and a function that returns the
> > index of the first element that is >= key.
>
> I recommend looking at
>
> https://www.postgresql.org/message-id/CAFBsxsESLUyJ5spfOSyPrOvKUEYYNqsBosue9SV1j8ecgNXSKA%40mail.gmail.com
>
> since I did the work just now for searching bytes and returning a
> bool, buth = and <=. Should be pretty close. Also, i believe if you
> left this for last as a possible refactoring, it might save some work.
> In any case, I'll take a look at the latest patch next month.

I've updated the radix tree patch. It's now separated into two patches.

0001 patch introduces pg_lsearch8() and pg_lsearch8_ge() (we may find
better names) that are similar to the pg_lfind8() family but they
return the index of the key in the vector instead of true/false. The
patch includes regression tests.

0002 patch is the main radix tree implementation. I've removed some
duplicated codes of node manipulation. For instance, since node-4,
node-16, and node-32 have a similar structure with different fanouts,
I introduced the common function for them.

In addition to two patches, I've attached the third patch. It's not
part of radix tree implementation but introduces a contrib module
bench_radix_tree, a tool for radix tree performance benchmarking. It
measures loading and lookup performance of both the radix tree and a
flat array.

Regards,

--
Masahiko Sawada
PostgreSQL Contributors Team
RDS Open Source Databases
Amazon Web Services: https://aws.amazon.com

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