Query performance issue

On 10/16/24 10:50 AM, yudhi s wrote:

Hi,

Below question got in one discussion.Appreciate any guidance on this.

Below is a query which is running for ~40 seconds. As it's a query which
is executed from UI , we were expecting it to finish in <~5 seconds. It
has a "IN" and a "NOT IN" subquery , from the execution path it seems
the total response time is mainly, to be sum of the "IN" and the "NOT
IN" subquery section. My thought was that both "IN" and "NOT IN" should
be executed/evaluated in parallel but not in serial fashion.

In the execution path below , the line number marked in *bold* are the
top lines for the IN and NOT IN subquery evaluation and they are showing
"Actual time" as  Approx ~9 seconds and ~8 seconds and they seems to be
summed up and the top lines showing it to be ~19 seconds. Then onwards
it keeps on increasing with other "nested loop" joins.

*Note*:- This query is running on a MYSQL 8.0 database. So I'm wondering
if there is any mysql list similar to Oracle list , in which i can share
this issue?

This is the Postgres list.

As to your question maybe one of the forums?:

https://forums.mysql.com/

In particular Performance:

https://forums.mysql.com/list.php?24

--
Adrian Klaver
adrian.klaver@aklaver.com

On 2024-10-16 23:20:36 +0530, yudhi s wrote:

Below is a query which is running for ~40 seconds.

[...]

In the execution path below , the line number marked in bold are the top lines
for the IN and NOT IN subquery evaluation and they are showing "Actual time" as
 Approx ~9 seconds and ~8 seconds and they seems to be summed up and the top
lines showing it to be ~19 seconds. Then onwards it keeps on increasing with
other "nested loop" joins.

Note:- This query is running on a MYSQL 8.0 database. So I'm wondering if there
is any mysql list similar to Oracle list , in which i can share this issue?

The execution plan looks like a postgresql execution plan, not a mysql
execution plan. Did you run this query on postgresql? That may be
interesting for comparison purposese, but ultimately it is useless: You
won't get mysql to work like postgresql, and any tips to speed up this
query on postgresql (which is all you can expect on a postgresql mailing
list) probably won't work on mysql.

hp

--
_ | Peter J. Holzer | Story must make more sense than reality.
|_|_) | |
| | | hjp@hjp.at | -- Charles Stross, "Creative writing
__/ | http://www.hjp.at/ | challenge!"

On Thu, Oct 17, 2024 at 3:06 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:

On 2024-10-16 23:20:36 +0530, yudhi s wrote:

Below is a query which is running for ~40 seconds.

[...]

In the execution path below , the line number marked in bold are the top

lines

for the IN and NOT IN subquery evaluation and they are showing "Actual

time" as

Approx ~9 seconds and ~8 seconds and they seems to be summed up and the

top

lines showing it to be ~19 seconds. Then onwards it keeps on increasing

with

other "nested loop" joins.

Note:- This query is running on a MYSQL 8.0 database. So I'm wondering

if there

is any mysql list similar to Oracle list , in which i can share this

issue?

The execution plan looks like a postgresql execution plan, not a mysql
execution plan. Did you run this query on postgresql? That may be
interesting for comparison purposese, but ultimately it is useless: You
won't get mysql to work like postgresql, and any tips to speed up this
query on postgresql (which is all you can expect on a postgresql mailing
list) probably won't work on mysql.

Agreed. Postgres and mysql may have differences in how the optimizer is
interpreting the stats and coming up with the execution oath. However, I
was looking if the query can be written efficiently by tweaking the current
logic. It's actually spending the majority of the time doing the "IN" and
"NOT IN" evaluation and in that it's using the same exact subquery for the
"UNION ALL" . And the overall execution time is summation of the IN and NOT
IN clause evaluation. So I was thinking of a better way of writing the
same logically.

On Thu, Oct 17, 2024 at 3:06 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:

The execution plan looks like a postgresql execution plan, not a mysql
execution plan. Did you run this query on postgresql? That may be
interesting for comparison purposese, but ultimately it is useless: You
won't get mysql to work like postgresql, and any tips to speed up this
query on postgresql (which is all you can expect on a postgresql mailing
list) probably won't work on mysql.

Tried running the same in postgres and below is the plan from bothe
postgres and mysql. Can you please guide me to understand , if anything
else can be done to make it better?

https://gist.github.com/databasetech0073/746353a9e76d5e29b2fc6abdc80cdef8

On 10/21/24 23:31, yudhi s wrote:

On Thu, Oct 17, 2024 at 3:06 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:

The execution plan looks like a postgresql execution plan, not a mysql
execution plan. Did you run this query on postgresql? That may be
interesting for comparison purposese, but ultimately it is
useless: You
won't get mysql to work like postgresql, and any tips to speed up this
query on postgresql (which is all you can expect on a postgresql
mailing
list) probably won't work on mysql.

Tried running the same in postgres and below is the plan from bothe
postgres and mysql. Can you please guide me to understand ,  if
anything else can be done to make it better?

https://gist.github.com/databasetech0073/746353a9e76d5e29b2fc6abdc80cdef8

Here's your postgres query as analyzed and made more readable by the
most excellent explain.depesz.com.

https://explain.depesz.com/s/VyeM#html

Under the hints tab are suggestions to bump your work_mem to avoid
writing sorts out to disk.

Jeff

To be frank, there is so much wrong with this query that it is hard to know
where to start. But a few top items:

* Make sure all of the tables involved have been analyzed. You might want
to bump default_statistics_target up and see if that helps.

* As mentioned already, increase work_mem, as you have things spilling to
disk (e.g. external merge Disk: 36280kB)

* Don't use the "FROM table1, table2, table3" syntax but use "FROM table1
JOIN table2 ON (...) JOIN table3 ON (...)

* Try not to use subselects. Things like WHERE x IN (SELECT ...) are
expensive and hard to optimize.

* You have useless GROUP BY clauses in there. Remove to simplify the query

* There is no LIMIT. Does the client really need all 135,214 rows?

Cheers,
Greg

On Tue, Oct 22, 2024 at 3:02 PM Greg Sabino Mullane <htamfids@gmail.com>
wrote:
[snip]

* Don't use the "FROM table1, table2, table3" syntax but use "FROM table1
JOIN table2 ON (...) JOIN table3 ON (...)

Why?

--
Death to <Redacted>, and butter sauce.
Don't boil me, I'm still alive.
<Redacted> crustacean!

On Tue, Oct 22, 2024 at 1:01 PM Ron Johnson <ronljohnsonjr@gmail.com> wrote:

On Tue, Oct 22, 2024 at 3:02 PM Greg Sabino Mullane <htamfids@gmail.com>
wrote:
[snip]

* Don't use the "FROM table1, table2, table3" syntax but use "FROM table1
JOIN table2 ON (...) JOIN table3 ON (...)

Why?

Readability is improved when done correctly; and you need to know it for
outer joins anyway, so consistency.

David J.

On Wed, Oct 23, 2024 at 12:32 AM Greg Sabino Mullane <htamfids@gmail.com>
wrote:

To be frank, there is so much wrong with this query that it is hard to
know where to start. But a few top items:

* Make sure all of the tables involved have been analyzed. You might want
to bump default_statistics_target up and see if that helps.

* As mentioned already, increase work_mem, as you have things spilling to
disk (e.g. external merge Disk: 36280kB)

* Don't use the "FROM table1, table2, table3" syntax but use "FROM table1
JOIN table2 ON (...) JOIN table3 ON (...)

* Try not to use subselects. Things like WHERE x IN (SELECT ...) are
expensive and hard to optimize.

* You have useless GROUP BY clauses in there. Remove to simplify the query

* There is no LIMIT. Does the client really need all 135,214 rows?

I tried running the query by removing both the "group by" from the inner
subqueries (I think the initial thought was that they will give distinct
records to the outer query and will thus help), and added limit 500 at the
last and also set the work_mem to 2GB for that session before running the
query. But seeing the response increased to ~5 seconds (from ~3.1 seconds
earlier). Below I have updated the execution plan for the same at the last
section.

https://gist.github.com/databasetech0073/746353a9e76d5e29b2fc6abdc80cdef8

Again , not able to clearly understand the third point you said below. Can
you please clarify a bit more. Do you mean we should write it as exists
/not exists rather IN and NOT IN and that will improve the performance? I
hope the third point doesn't matter much as we have all equijoin used here.
Correct me if I'm wrong.

*"Try not to use subselects. Things like WHERE x IN (SELECT ...) are
expensive and hard to optimize*."

Additionally in the plan which mysql makes and showing the highest response
time, is it suffering because of differences of the speed of the underlying
IO/storage or is it just because of the optimization features which are
available in postgres and not there in mysql ? Trying to understand if it
can be identified from the execution plan itself.

On Tue, 2024-10-22 at 13:06 -0700, David G. Johnston wrote:

On Tue, Oct 22, 2024 at 1:01 PM Ron Johnson <ronljohnsonjr@gmail.com> wrote:

On Tue, Oct 22, 2024 at 3:02 PM Greg Sabino Mullane <htamfids@gmail.com> wrote:

* Don't use the "FROM table1, table2, table3" syntax but use "FROM table1 JOIN table2 ON (...) JOIN table3 ON (...)

Why?

Readability is improved when done correctly; and you need to know it for outer joins anyway, so consistency.

Also, you cannot accidentally forget a join condition.

Yours,
Laurenz Albe

On Wed, Oct 23, 2024 at 2:06 AM yudhi s <learnerdatabase99@gmail.com> wrote:

On Wed, Oct 23, 2024 at 12:32 AM Greg Sabino Mullane <htamfids@gmail.com>
wrote:

To be frank, there is so much wrong with this query that it is hard to
know where to start. But a few top items:

* Make sure all of the tables involved have been analyzed. You might want
to bump default_statistics_target up and see if that helps.

* As mentioned already, increase work_mem, as you have things spilling to
disk (e.g. external merge Disk: 36280kB)

* Don't use the "FROM table1, table2, table3" syntax but use "FROM table1
JOIN table2 ON (...) JOIN table3 ON (...)

* Try not to use subselects. Things like WHERE x IN (SELECT ...) are
expensive and hard to optimize.

* You have useless GROUP BY clauses in there. Remove to simplify the query

* There is no LIMIT. Does the client really need all 135,214 rows?

I tried running the query by removing both the "group by" from the inner
subqueries (I think the initial thought was that they will give distinct
records to the outer query and will thus help), and added limit 500 at the
last and also set the work_mem to 2GB for that session before running the
query. But seeing the response increased to ~5 seconds (from ~3.1 seconds
earlier). Below I have updated the execution plan for the same at the last
section.

https://gist.github.com/databasetech0073/746353a9e76d5e29b2fc6abdc80cdef8

Again , not able to clearly understand the third point you said below. Can
you please clarify a bit more. Do you mean we should write it as exists
/not exists rather IN and NOT IN and that will improve the performance? I
hope the third point doesn't matter much as we have all equijoin used here.
Correct me if I'm wrong.

*"Try not to use subselects. Things like WHERE x IN (SELECT ...) are
expensive and hard to optimize*."

Additionally in the plan which mysql makes and showing the highest
response time, is it suffering because of differences of the speed of the
underlying IO/storage or is it just because of the optimization features
which are available in postgres and not there in mysql ? Trying to
understand if it can be identified from the execution plan itself.

Additionally, I see below differences, when I compare two specific lines of
the plan which fetches data using the same index in both posgres and mysql,
so does it point that the speed in mysql is slower as compared to postgres.
And thus is it possible that the underlying infrastructure is playing a
role here in the mysql slowness too and that might be the key one here to
first address for mysql
OR its any optimization feature which helps postgres to give it an edge in
performance here over mysql?

In mysql plan:-
-> Index lookup on EX_STS using EX_STS_INDEX (AID=b3.AID, RC_ID=b3.RC_ID,
RC_VNB=b3.RC_VNB) (cost=0.43 rows=2) (actual time=0.014..0.021 rows=2
loops=70904)
VS
In postgres plan:-
-> Index Scan using EX_STS_INDEX on RCE_STS EX_STS (cost=0.42..0.82 rows=1
width=424) (actual time=0.006..0.007 rows=2 loops=70904)

**************

In mysql plan
-> Covering index lookup on mns using M_INF_AID_index
(AID='XXXXXXXXXXXXXXXXXXX') (cost=9187.54 rows=72748) (actual
time=0.058..19.637 rows=35980 loops=1)
-> Filter:
(RNS.ASID = 'XXXXXXXXXXXXXXXXXXX') (cost=43.50 rows=42) (actual
time=0.042..0.218 rows=97 loops=1)
VS
In postgres plan
-> Bitmap Index Scan on M_INF_AID_index (cost=0.00..406.98 rows=36074
width=0) (actual time=0.790..0.790 rows=35980 loops=1)
Index Cond: ((AID)::text =
'XXXXXXXXXXXXXXXXXXX'::text)

Additionally in the plan which mysql makes and showing the highest
response time, is it suffering because of differences of the speed of the
underlying IO/storage or is it just because of the optimization features
which are available in postgres and not there in mysql ? Trying to
understand if it can be identified from the execution plan itself.

I think trying to compare postgres and mysql plans against each other is
not a very useful endeavor. There are fundamental design decisions between
the two. Focus on making your Postgres query the best it can be, full stop.
Optimize your queries, make sure the database is analyzed, and tweak some
configs as needed.

Also, you cannot accidentally forget a join condition.

Yes, this is the primary reason. Cartesian joins hurt.

Again , not able to clearly understand the third point you said below. Can

you please clarify a bit more. Do you mean we should write it as exists
/not exists rather IN and NOT IN and that will improve the performance?

It gives Postgres more options on how to do things, so yes, it can be
better.

Cheers,
Greg