[postgis-devel] Issues about the GSoC project

[Han Wang]

Hi Giuseppe and Hi Regina,

After checking the paper of GiST and implementation in Postgres. I think
the query performance should be considered besides the building process. In
the larger data test scenario, the building time of different indexes are
similar because Postgres just hashes the tuples and sorts them and packs
them into pages, building the tree index from bottom to up. With a bad hash
order definition, the building process cannot detect the poor index query
performance. So it is necessary to test the index query performance. I have
tested the query performance with the `EXPLAIN` operator, using the sql
scripts like other indexes in the `/regress`. But I am not familiar with
PL/pgSQL, so I handle the log with some python scripts.

In this test, I focus on the buffer hits and execution time of different
tasks of different index types including `No Index`, `Simple GiST index`,
`X hash function`, `morton hash function` and `hilbert hash function`.
And there are some results:
Shared buffer hits:
 IndexCreate Time(ms)<<&<&&&>>>~=~@&<|<<||>>|&>
0 No Index 0 18 18 18 18 18 18 18 18 18 18 18 18
1 GiST Index 25.249 40237 46085 3009 40297 46025 3009 3009 3009 41994 45295
41934 45355
2 X PreSort Index 8.829 443620 441235 3009 444501 440354 3009 3009 3009
441568 442503 440687 443384
3 Morton PreSort Index 16.885 447779 447446 4079 448669 446556 4079 4079
4079 445362 449428 444472 450318
4 Hilbert PreSort Index 16.824 446714 444058 3558 447600 443172 3558 3558
3558 446072 445394 445186 446280
Execution time:

IndexCreate Time(ms)<<&<&&&>>>~=~@&<|<<||>>|&>
0 No Index 0 567.251 565.720 481.618 561.877 563.452 480.128 478.275 478.518
567.144 572.191 563.255 556.281
1 GiST Index 25.249 289.255 293.143 28.838 289.002 291.296 28.336 28.597
26.947 295.394 297.556 293.988 299.760
2 X PreSort Index 8.829 440.861 445.630 37.960 439.564 440.535 37.594 37.979
37.741 386.662 384.635 385.166 388.832
3 Morton PreSort Index 16.885 421.999 413.427 77.002 422.939 412.130 77.415
75.102 76.056 416.205 446.599 410.614 434.613
4 Hilbert PreSort Index 16.824 417.539 415.962 56.583 421.226 414.553 56.320
55.600 55.338 416.639 421.243 418.550 417.094
The number of shared buffer hits are far bigger than the original one. But
what confuses me is that the execution times are worse. I am trying to
figure out why this happened.
What's more, I am not very clear about the relationship between query
performance and the number of shared buffer hits.

If you have any questions or suggestions, please let me know.

Best regards,
Han

On Thu, Jul 8, 2021 at 1:32 AM Giuseppe Broccolo <g.broccolo.7 at gmail.com>
wrote:

> Hi Han,
>
> Il giorno mer 7 lug 2021 alle ore 18:05 Han Wang <hanwgeek at gmail.com> ha
> scritto:
>
>> Hi Regina and hi Giuseppe,
>>
>> Thanks for your reply!
>>
>> I am now checking the original paper and postgres's implement of gist.
>> And now I think the query performance test after building gist index is
>> necessary. Because as Darafei mentioned, the fast sorting building method
>> may just pack the sorted tuples into pages regardless of which hash
>> function it use. The correctness of index may be checked in the runtime
>> query. At present, I am working on confirm the io access of hash functions.
>>
>> Feel free to give suggestions or questions.
>>
>
> The correctness of the index should be covered by some of the regression
> tests in action for the GiST support in PostGIS - for instance, kNN
> searches etc. - for the moment I am really curious about the I/O access of
> the hash functions. This is something maybe it has not been checked even in
> PostgreSQL, and maybe it would be good to share the results with them as
> well.
>
> Keep us updated, and thank you for your help!
>
> Giuseppe.
>
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