Thread

Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-01-31T13:30:03Z

Hello Experts,
 We have a "Select" query which is using three to five main transaction
tables (txn_tbl, txn_status, txn_decision, txn_sale, ath) holding ~2million
rows in each of them(which is going to increase to have ~50-100million in
future) and others(6-7) tables out of which some are master and some other
small tables.

When we are running this query , and it's taking ~2-3seconds , however when
we hit this query from 10-15 session at same time its causing CPU spike up
to ~50-60% for the DB instance and this is increasing and touching 90% when
we are increasing the hits further to 40-50 times concurrently.

This query is going to be called in the first page of an UI screen and is
supposed to show the latest 1000 rows based on a certain transaction date.
This query is supposed to allow thousands of users to hit this same query
at the first landing page at the same time.  Its postgres version 17.  The
instance has 2-VCPU and 16GB RAM.

I have the following questions.

1)Why is this query causing a high cpu spike ,if there is any way in
postgres to understand what part/line of the query is contributing to the
high cpu time?
2)How can we tune this query to further reduce response time and mainly CPU
consumption ? Is any additional index or anything will make this plan
better further?
3) Is there any guidance or best practices exists , to create/design top
N-queries for such UI scenarios where performance is an important factor?
4)And based on the CPU core and memory , is there any calculation by using
which , we can say that this machine can support a maximum N number of
concurrent queries of such type beyond which we need more cpu cores
machines?

Below is the query and its current plan:-
https://gist.github.com/databasetech0073/6688701431dc4bf4eaab8d345c1dc65f

Regards
Yudhi

Re: Top -N Query performance issue and high CPU usage

David Mullineux <dmullx@gmail.com> — 2026-01-31T14:41:18Z

On Sat, 31 Jan 2026, 13:30 yudhi s, <learnerdatabase99@gmail.com> wrote:

> Hello Experts,
>  We have a "Select" query which is using three to five main transaction
> tables (txn_tbl, txn_status, txn_decision, txn_sale, ath) holding ~2million
> rows in each of them(which is going to increase to have ~50-100million in
> future) and others(6-7) tables out of which some are master and some other
> small tables.
>
> When we are running this query , and it's taking ~2-3seconds , however
> when we hit this query from 10-15 session at same time its causing CPU
> spike up to ~50-60% for the DB instance and this is increasing and touching
> 90% when we are increasing the hits further to 40-50 times concurrently.
>
> This query is going to be called in the first page of an UI screen and is
> supposed to show the latest 1000 rows based on a certain transaction date.
> This query is supposed to allow thousands of users to hit this same query
> at the first landing page at the same time.  Its postgres version 17.  The
> instance has 2-VCPU and 16GB RAM.
>
> I have the following questions.
>
> 1)Why is this query causing a high cpu spike ,if there is any way in
> postgres to understand what part/line of the query is contributing to the
> high cpu time?
> 2)How can we tune this query to further reduce response time and mainly
> CPU consumption ? Is any additional index or anything will make this plan
> better further?
> 3) Is there any guidance or best practices exists , to create/design top
> N-queries for such UI scenarios where performance is an important factor?
> 4)And based on the CPU core and memory , is there any calculation by using
> which , we can say that this machine can support a maximum N number of
> concurrent queries of such type beyond which we need more cpu cores
> machines?
>
> Below is the query and its current plan:-
> https://gist.github.com/databasetech0073/6688701431dc4bf4eaab8d345c1dc65f
>
> Regards
> Yudhi
>

Plan says it's using temp files for sorting....I would suggest you increase
work_mem for this to avoid temp.fike creation...Although not the answer to
all your problems, it would be a good start .

Re: Top -N Query performance issue and high CPU usage

Adrian Klaver <adrian.klaver@aklaver.com> — 2026-01-31T16:14:48Z

On 1/31/26 05:30, yudhi s wrote:
> Hello Experts,

> This query is going to be called in the first page of an UI screen and 
> is supposed to show the latest 1000 rows based on a certain transaction 
> date. This query is supposed to allow thousands of users to hit this 
> same query at the first landing page at the same time. Its postgres 
> version 17.  The instance has 2-VCPU and 16GB RAM.

1) Without even looking at the plan I'm going to say 2-VCPU and 16GB RAM 
and is insufficient resources for what you want to do.

2) You will need to provide the schema definitions for the tables involved.

4)And based on the CPU core and memory , is there any calculation by 
using which , we can say that this machine can support a maximum N 
number of concurrent queries of such type beyond which we need more cpu 
cores machines?

You already have the beginnings of a chart:

1 session 2-3 secs

10-15 sessions 50-60% usage

40-50 sessions 90% usage

> 
> Regards
> Yudhi

-- 
Adrian Klaver
adrian.klaver@aklaver.com

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-01-31T19:39:47Z

>
>
>>
> Plan says it's using temp files for sorting....I would suggest you
> increase work_mem for this to avoid temp.fike creation...Although not the
> answer to all your problems, it would be a good start .
>
>
Even setting work_mem to 64MB remove all the "temp read" and showig all
memory reads, but still we are seeing similar cpu spike when executing this
query from multiple sessions and also the response time is staying same.

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-01-31T19:46:56Z

Thank you.

>
> 1) Without even looking at the plan I'm going to say 2-VCPU and 16GB RAM
> and is insufficient resources for what you want to do.
>
>
Can you please explain a bit in detail, how much minimum VCPU and RAM will
be enough resources to suffice this requirement? and you normally do that
calculation?


> 2) You will need to provide the schema definitions for the tables involved.
>
> Do you mean table DDL or just the index definitions on the tables should
help?

Also i was trying to understand , by just looking into the "explain
analyze" output, is there any way we can tie the specific step in the plan
, which is the major contributor of the cpu resources? Such that we can
then try to fix that part rather than looking throughout the query as its
big query?

And if any suggestion to improve the TOP-N queries where the base table may
have many rows in it.

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-01-31T21:05:17Z

On Sat, Jan 31, 2026 at 2:47 PM yudhi s <learnerdatabase99@gmail.com> wrote:

> Thank you.
>
>>
>> 1) Without even looking at the plan I'm going to say 2-VCPU and 16GB RAM
>> and is insufficient resources for what you want to do.
>>
>>
> Can you please explain a bit in detail, how much minimum VCPU and RAM will
> be enough resources to suffice this requirement? and you normally do that
> calculation?
>
>
>> 2) You will need to provide the schema definitions for the tables
>> involved.
>>
>> Do you mean table DDL or just the index definitions on the tables should
> help?
>
> Also i was trying to understand , by just looking into the "explain
> analyze" output, is there any way we can tie the specific step in the plan
> , which is the major contributor of the cpu resources? Such that we can
> then try to fix that part rather than looking throughout the query as its
> big query?
>

It looks like 71% (748ms of a total 1056ms) of elapsed time is taken by the
c_1.tran_date  external sort on line 150.

That, obviously, is what you should work on.

1. You say you increased work_mem.  From what, to what?
2. But that it did not reduce execution time.  Please post the EXPLAIN from
after increasing work_mem.
3. Did you remember to run SELECT pg_reload_conf(); after increasing
work_mem?
4. Is there an index on APP_schema.txn_tbl.tran_date?

And if any suggestion to improve the TOP-N queries where the base table may
> have many rows in it.
>

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

Re: Top -N Query performance issue and high CPU usage

Luigi Nardi <luigi@dbtune.com> — 2026-02-01T12:54:54Z

On Sat, Jan 31, 2026 at 10:05 PM Ron Johnson <ronljohnsonjr@gmail.com>
wrote:

> On Sat, Jan 31, 2026 at 2:47 PM yudhi s <learnerdatabase99@gmail.com>
> wrote:
>
>> Thank you.
>>
>>>
>>> 1) Without even looking at the plan I'm going to say 2-VCPU and 16GB RAM
>>> and is insufficient resources for what you want to do.
>>>
>>>
>> Can you please explain a bit in detail, how much minimum VCPU and RAM
>> will be enough resources to suffice this requirement? and you normally do
>> that calculation?
>>
>>
>>> 2) You will need to provide the schema definitions for the tables
>>> involved.
>>>
>>> Do you mean table DDL or just the index definitions on the tables should
>> help?
>>
>> Also i was trying to understand , by just looking into the "explain
>> analyze" output, is there any way we can tie the specific step in the plan
>> , which is the major contributor of the cpu resources? Such that we can
>> then try to fix that part rather than looking throughout the query as its
>> big query?
>>
>
> It looks like 71% (748ms of a total 1056ms) of elapsed time is taken by
> the c_1.tran_date  external sort on line 150.
>
> That, obviously, is what you should work on.
>
> 1. You say you increased work_mem.  From what, to what?
> 2. But that it did not reduce execution time.  Please post the EXPLAIN
> from after increasing work_mem.
> 3. Did you remember to run SELECT pg_reload_conf(); after increasing
> work_mem?
> 4. Is there an index on APP_schema.txn_tbl.tran_date?
>
> And if any suggestion to improve the TOP-N queries where the base table
>> may have many rows in it.
>>
>
>
The DBtune Free Edition <http://app.dbtune.com> can help you find the
correct adjustments for work_mem and other server parameters
<https://dbtune.com/blog/dbtunes-multi-dimensional-performance-tuning-space>.
It's designed to help optimize your PostgreSQL runtime for your current
hardware setup.



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

Re: Top -N Query performance issue and high CPU usage

Peter J. Holzer <hjp-pgsql@hjp.at> — 2026-02-01T21:47:11Z

On 2026-02-01 01:16:56 +0530, yudhi s wrote:
> Thank you. 
> 
> 
>     1) Without even looking at the plan I'm going to say 2-VCPU and 16GB RAM
>     and is insufficient resources for what you want to do.
> 
> 
> 
> Can you please explain a bit in detail, how much minimum VCPU and RAM will be
> enough resources to suffice this requirement? and you normally do that
> calculation?

You wrote:

| This query is supposed to allow thousands of users to hit this same
| query at the first landing page at the same time.

If you meant that literally, you would need thousands of cores to handle
those thousands of simultaneous queries and enough RAM for thousands of
sessions, each performing a rather complex query. So possibly hundreds
of maybe even thousands of gigabytes, not 16.

However, maybe you didn't mean that. There are relatively few
applications where thousands of users log in within a second. Maybe you
just meant that there would be thousands of users logged in in total. If
so, how many simultaneus queries do you really expect?

If you do have that many simultaneous accesses to the landing page, and
you can't speed up the query significantly (I take it you've seen the
suggestion to check whether there's an index on
APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
for every user? I don't know what the query is supposed to do, but
unless the "ent_id" is really a user id, it doesn't seem to be specific
to the user. So maybe you can cache the result for a minute or an hour
and show the same result to everybody who logs in during that time.

        hjp

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

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-01T21:56:20Z

On Sun, Feb 1, 2026 at 4:47 PM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:
[snip]

> If you do have that many simultaneous accesses to the landing page, and
> you can't speed up the query significantly (I take it you've seen the
> suggestion to check whether there's an index on
> APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
> for every user? I don't know what the query is supposed to do, but
> unless the "ent_id" is really a user id, it doesn't seem to be specific
> to the user. So maybe you can cache the result for a minute or an hour
> and show the same result to everybody who logs in during that time.
>

That's what I was thinking, too: app server background process continually
runs that query in a loop, feeding the results to a shared cache; the end
user connections then read the latest version of the cached results.

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

Re: Top -N Query performance issue and high CPU usage

Adrian Klaver <adrian.klaver@aklaver.com> — 2026-02-02T01:06:17Z

On 1/31/26 11:46, yudhi s wrote:
> Thank you.
> 
> 
>     1) Without even looking at the plan I'm going to say 2-VCPU and 16GB
>     RAM
>     and is insufficient resources for what you want to do.
> 
> 
> Can you please explain a bit in detail, how much minimum VCPU and RAM 
> will be enough resources to suffice this requirement? and you normally 
> do that calculation?

Don't know what the minimum requirements are. It would depend on many 
variables 1) The plan being chosen, which in turn depends on the schema 
information as well as the data turnover. 2) What the VCPU is actually 
emulating. 3) The efficiency of of the virtual machines/containers with 
regard to accessing memory and storage. 4) The service limits of the 
virtualization. 5) What the storage system and how performant it is.

In other words this is something you will need to test and derive your 
own formula for.

> 
>     2) You will need to provide the schema definitions for the tables
>     involved.
> 
> Do you mean table DDL or just the index definitions on the tables should 
> help?

Basically what you get in psql when you do \d some_table.

> 
> Also i was trying to understand , by just looking into the "explain 
> analyze" output, is there any way we can tie the specific step in the 
> plan , which is the major contributor of the cpu resources? Such that we 
> can then try to fix that part rather than looking throughout the query 
> as its big query?
> 
> And if any suggestion to improve the TOP-N queries where the base table 
> may have many rows in it.

-- 
Adrian Klaver
adrian.klaver@aklaver.com

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-02T04:17:06Z

On Mon, Feb 2, 2026 at 3:17 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:

>
> However, maybe you didn't mean that. There are relatively few
> applications where thousands of users log in within a second. Maybe you
> just meant that there would be thousands of users logged in in total. If
> so, how many simultaneus queries do you really expect?
>
> If you do have that many simultaneous accesses to the landing page, and
> you can't speed up the query significantly (I take it you've seen the
> suggestion to check whether there's an index on
> APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
> for every user? I don't know what the query is supposed to do, but
> unless the "ent_id" is really a user id, it doesn't seem to be specific
> to the user. So maybe you can cache the result for a minute or an hour
> and show the same result to everybody who logs in during that time.
>
>
Thank you so much. I need to get back on the exact number of such queries
which can hit the database. However, as 1000 of users will be there, so the
possibility of all logging into the system on the same page at same time
needs to be found out. Will double check on this.

However,  when you said caching :- The results on the base tables are going
to be ~30-50 million. This landing page has filters on it so it may be of
30+ different combinations based on the user's choice. So do you suggest ,
we will populate the base data in a materialized view(named like "landing
page data") which we can refresh (maybe once in ~5 minutes behind the
scenes) and then that can be queried in the landing page directly. And we
can have suitable indexes created on the materialized view based on the
dynamic filter criteria?

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-02T06:33:08Z

On Mon, 2 Feb, 2026, 11:21 am Rob Sargent, <robjsargent@gmail.com> wrote:

>
> > Thank you so much. I need to get back on the exact number of such
> queries which can hit the database. However, as 1000 of users will be
> there, so the possibility of all logging into the system on the same page
> at same time needs to be found out. Will double check on this.
> >
> > However,  when you said caching :- The results on the base tables are
> going to be ~30-50 million. This landing page has filters on it so it may
> be of 30+ different
>
> I know I read OP’s earlier descriptions to suggest that each login saw the
> same data. I was wrong and I suspect the suggestion to cache goes out the
> window.
>
> The need for more resources now comes centre stage, right beside query
> tuning. You won’t get much help here on the latter problem without more DDL
> on the tables involved. Help on the hardware is just money - though most
> desktops these days are more powerful than that vert described up-thread


Won't , the materialized view having a minimum Delta refresh frequency(5-10
> minutes?) help in such scenarios? As the overhead of the query complexity
> will lie within the materialized view and it can be indexed as per the
> dynamic incoming filter conditions.

Re: Top -N Query performance issue and high CPU usage

Thiemo Kellner <thiemo@gelassene-pferde.biz> — 2026-02-02T07:45:31Z

Hi

Would it do any good to restrict the transaction date for the limit to something like "current timestamp - 1 day/hour/month". How about partitioning?

My two dimes

Thiemo

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-02T11:39:21Z

On Mon, Feb 2, 2026 at 3:17 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:

>
> If you do have that many simultaneous accesses to the landing page, and
> you can't speed up the query significantly (I take it you've seen the
> suggestion to check whether there's an index on
> APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
> for every user? I don't know what the query is supposed to do, but
> unless the "ent_id" is really a user id, it doesn't seem to be specific
> to the user. So maybe you can cache the result for a minute or an hour
> and show the same result to everybody who logs in during that time.
>
>
>

There was no index on column  tran_date  , I created one and it's making
the query finish in  ~200ms, a lot faster than in the past. Below is the
portion of the query and its plan which actually consumes most of the
resource and time post the new index creation.

https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492

1) Now the part  which takes time is the "nested loop" join on the
"ent_id"  column. Can we do anything to make it much better/faster?

2) Also another question I had was,  with this new index the table scan of
txn_tbl is now fully eliminated by the "Index Scan Backward" even i have
other columns from that table projected in the query, so how its getting
all those column values without visiting table but just that index scan
backward operation?

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-02T13:34:31Z

On Mon, Feb 2, 2026 at 6:39 AM yudhi s <learnerdatabase99@gmail.com> wrote:

>
>
> On Mon, Feb 2, 2026 at 3:17 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:
>
>>
>> If you do have that many simultaneous accesses to the landing page, and
>> you can't speed up the query significantly (I take it you've seen the
>> suggestion to check whether there's an index on
>> APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
>> for every user? I don't know what the query is supposed to do, but
>> unless the "ent_id" is really a user id, it doesn't seem to be specific
>> to the user. So maybe you can cache the result for a minute or an hour
>> and show the same result to everybody who logs in during that time.
>>
>>
>>
>
> There was no index on column  tran_date  , I created one and it's making
> the query finish in  ~200ms, a lot faster than in the past. Below is the
> portion of the query and its plan which actually consumes most of the
> resource and time post the new index creation.
>
> https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492
>
> 1) Now the part  which takes time is the "nested loop" join on the
> "ent_id"  column. Can we do anything to make it much better/faster?
>
> 2) Also another question I had was,  with this new index the table scan of
> txn_tbl is now fully eliminated by the "Index Scan Backward" even i have
> other columns from that table projected in the query, so how its getting
> all those column values without visiting table but just that index scan
> backward operation?
>

Reading through EXPLAIN output isn't always a mystery.

Search for "actual time" and you'll find row 53, which is the "deepest"
(most nested) row with the highest actual time.

That tells you where the time is now spent, and what it's doing.

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

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-02T13:53:00Z

On Mon, Feb 2, 2026 at 7:04 PM Ron Johnson <ronljohnsonjr@gmail.com> wrote:

> On Mon, Feb 2, 2026 at 6:39 AM yudhi s <learnerdatabase99@gmail.com>
> wrote:
>
>>
>>
>> On Mon, Feb 2, 2026 at 3:17 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:
>>
>>>
>>> If you do have that many simultaneous accesses to the landing page, and
>>> you can't speed up the query significantly (I take it you've seen the
>>> suggestion to check whether there's an index on
>>> APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
>>> for every user? I don't know what the query is supposed to do, but
>>> unless the "ent_id" is really a user id, it doesn't seem to be specific
>>> to the user. So maybe you can cache the result for a minute or an hour
>>> and show the same result to everybody who logs in during that time.
>>>
>>>
>>>
>>
>> There was no index on column  tran_date  , I created one and it's making
>> the query finish in  ~200ms, a lot faster than in the past. Below is the
>> portion of the query and its plan which actually consumes most of the
>> resource and time post the new index creation.
>>
>> https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492
>>
>> 1) Now the part  which takes time is the "nested loop" join on the
>> "ent_id"  column. Can we do anything to make it much better/faster?
>>
>> 2) Also another question I had was,  with this new index the table scan
>> of txn_tbl is now fully eliminated by the "Index Scan Backward" even i have
>> other columns from that table projected in the query, so how its getting
>> all those column values without visiting table but just that index scan
>> backward operation?
>>
>
> Reading through EXPLAIN output isn't always a mystery.
>
> Search for "actual time" and you'll find row 53, which is the "deepest"
> (most nested) row with the highest actual time.
>
> That tells you where the time is now spent, and what it's doing.
>
>
>
My apologies if i misunderstand the plan, But If I see,   it's spending
~140ms(140ms-6ms) i.e. almost all the time now, in performing the below
nested loop join. So my question was , is there any possibility to reduce
the resource consumption or response time further here?  Hope my
understanding is correct here.

-> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual time=
*6.009..147.695* rows=1049 loops=1)
Join Filter: ((df.ent_id)::numeric = m.ent_id)
Rows Removed by Join Filter: 513436
Buffers: shared hit=1939

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-02T15:00:47Z

On Mon, Feb 2, 2026 at 8:53 AM yudhi s <learnerdatabase99@gmail.com> wrote:

>
>
> On Mon, Feb 2, 2026 at 7:04 PM Ron Johnson <ronljohnsonjr@gmail.com>
> wrote:
>
>> On Mon, Feb 2, 2026 at 6:39 AM yudhi s <learnerdatabase99@gmail.com>
>> wrote:
>>
>>>
>>>
>>> On Mon, Feb 2, 2026 at 3:17 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:
>>>
>>>>
>>>> If you do have that many simultaneous accesses to the landing page, and
>>>> you can't speed up the query significantly (I take it you've seen the
>>>> suggestion to check whether there's an index on
>>>> APP_schema.txn_tbl.tran_date), then maybe you don't need to perform it
>>>> for every user? I don't know what the query is supposed to do, but
>>>> unless the "ent_id" is really a user id, it doesn't seem to be specific
>>>> to the user. So maybe you can cache the result for a minute or an hour
>>>> and show the same result to everybody who logs in during that time.
>>>>
>>>>
>>>>
>>>
>>> There was no index on column  tran_date  , I created one and it's
>>> making the query finish in  ~200ms, a lot faster than in the past. Below is
>>> the portion of the query and its plan which actually consumes most of the
>>> resource and time post the new index creation.
>>>
>>> https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492
>>>
>>> 1) Now the part  which takes time is the "nested loop" join on the
>>> "ent_id"  column. Can we do anything to make it much better/faster?
>>>
>>> 2) Also another question I had was,  with this new index the table scan
>>> of txn_tbl is now fully eliminated by the "Index Scan Backward" even i have
>>> other columns from that table projected in the query, so how its getting
>>> all those column values without visiting table but just that index scan
>>> backward operation?
>>>
>>
>> Reading through EXPLAIN output isn't always a mystery.
>>
>> Search for "actual time" and you'll find row 53, which is the "deepest"
>> (most nested) row with the highest actual time.
>>
>> That tells you where the time is now spent, and what it's doing.
>>
>>
>>
> My apologies if i misunderstand the plan, But If I see,   it's spending
> ~140ms(140ms-6ms) i.e. almost all the time now, in performing the below
> nested loop join. So my question was , is there any possibility to reduce
> the resource consumption or response time further here?  Hope my
> understanding is correct here.
>
> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual time=
> *6.009..147.695* rows=1049 loops=1)
> Join Filter: ((df.ent_id)::numeric = m.ent_id)
> Rows Removed by Join Filter: 513436
> Buffers: shared hit=1939
>

I don't see m.ent_id in the actual query.  Did you only paste a portion of
the query?

Also, casting in a JOIN typically brutalizes the ability to use an index.

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

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-02T18:39:24Z

On Mon, Feb 2, 2026 at 8:57 PM Ron Johnson <ronljohnsonjr@gmail.com> wrote:

>
>> My apologies if i misunderstand the plan, But If I see,   it's spending
>> ~140ms(140ms-6ms) i.e. almost all the time now, in performing the below
>> nested loop join. So my question was , is there any possibility to reduce
>> the resource consumption or response time further here?  Hope my
>> understanding is correct here.
>>
>> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual
>> time=*6.009..147.695* rows=1049 loops=1)
>> Join Filter: ((df.ent_id)::numeric = m.ent_id)
>> Rows Removed by Join Filter: 513436
>> Buffers: shared hit=1939
>>
>
> I don't see m.ent_id in the actual query.  Did you only paste a portion
> of the query?
>
> Also, casting in a JOIN typically brutalizes the ability to use an index.
>
>
> Thank you.
Actually i tried executing the first two CTE where the query was spending
most of the time  and teh alias has changed. Also here i have changed the
real table names before putting it here, hope that is fine.
However , i verified the data type of the ent_id column in "ent" its "int8"
and in table "txn_tbl" is "numeric 12", so do you mean to say this
difference in the data type is causing this high response time during the
nested loop join? My understanding was it will be internally castable
without additional burden. Also, even i tried creating an index on the
"(df.ent_id)::numeric"
its still reulting into same plan and response time.

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-02T19:31:06Z

On Mon, Feb 2, 2026 at 1:39 PM yudhi s <learnerdatabase99@gmail.com> wrote:

> On Mon, Feb 2, 2026 at 8:57 PM Ron Johnson <ronljohnsonjr@gmail.com>
> wrote:
>
>>
>>> My apologies if i misunderstand the plan, But If I see,   it's spending
>>> ~140ms(140ms-6ms) i.e. almost all the time now, in performing the below
>>> nested loop join. So my question was , is there any possibility to reduce
>>> the resource consumption or response time further here?  Hope my
>>> understanding is correct here.
>>>
>>> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual
>>> time=*6.009..147.695* rows=1049 loops=1)
>>> Join Filter: ((df.ent_id)::numeric = m.ent_id)
>>> Rows Removed by Join Filter: 513436
>>> Buffers: shared hit=1939
>>>
>>
>> I don't see m.ent_id in the actual query.  Did you only paste a portion
>> of the query?
>>
>> Also, casting in a JOIN typically brutalizes the ability to use an index.
>>
>>
>> Thank you.
> Actually i tried executing the first two CTE where the query was spending
> most of the time  and teh alias has changed.
>

We need to see everything, not just what you think is relevant.


> Also here i have changed the real table names before putting it here, hope
> that is fine.
> However , i verified the data type of the ent_id column in "ent" its
> "int8" and in table "txn_tbl" is "numeric 12", so do you mean to say this
> difference in the data type is causing this high response time during the
> nested loop join? My understanding was it will be internally castable
> without additional burden. Also, even i tried creating an index on the "(df.ent_id)::numeric"
> its still reulting into same plan and response time.
>

If you'd shown the "\d" table definitions like Adrian asked two days ago,
we'd know what indexes are on each table, and not have to beg you to
dispense dribs and drabs of information.

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

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-02T20:43:01Z

On Tue, Feb 3, 2026 at 1:01 AM Ron Johnson <ronljohnsonjr@gmail.com> wrote:

> On Mon, Feb 2, 2026 at 1:39 PM yudhi s <learnerdatabase99@gmail.com>
> wrote:
>
>> On Mon, Feb 2, 2026 at 8:57 PM Ron Johnson <ronljohnsonjr@gmail.com>
>> wrote:
>>
>>>
>>>> My apologies if i misunderstand the plan, But If I see,   it's spending
>>>> ~140ms(140ms-6ms) i.e. almost all the time now, in performing the below
>>>> nested loop join. So my question was , is there any possibility to reduce
>>>> the resource consumption or response time further here?  Hope my
>>>> understanding is correct here.
>>>>
>>>> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual
>>>> time=*6.009..147.695* rows=1049 loops=1)
>>>> Join Filter: ((df.ent_id)::numeric = m.ent_id)
>>>> Rows Removed by Join Filter: 513436
>>>> Buffers: shared hit=1939
>>>>
>>>
>>> I don't see m.ent_id in the actual query.  Did you only paste a portion
>>> of the query?
>>>
>>> Also, casting in a JOIN typically brutalizes the ability to use an index.
>>>
>>>
>>> Thank you.
>> Actually i tried executing the first two CTE where the query was spending
>> most of the time  and teh alias has changed.
>>
>
> We need to see everything, not just what you think is relevant.
>
>
>> Also here i have changed the real table names before putting it here,
>> hope that is fine.
>> However , i verified the data type of the ent_id column in "ent" its
>> "int8" and in table "txn_tbl" is "numeric 12", so do you mean to say this
>> difference in the data type is causing this high response time during the
>> nested loop join? My understanding was it will be internally castable
>> without additional burden. Also, even i tried creating an index on the "(df.ent_id)::numeric"
>> its still reulting into same plan and response time.
>>
>
> If you'd shown the "\d" table definitions like Adrian asked two days ago,
> we'd know what indexes are on each table, and not have to beg you to
> dispense dribs and drabs of information.
>
>
I am unable to run "\d" from the dbeaver sql worksheet. However,  I have
fetched the DDL for the three tables and their selected columns, used in
the smaller version of the query and its plan , which I recently updated.

https://gist.github.com/databasetech0073/e4290b085f8f974e315fb41bdc47a1f3

https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492

Regards
Yudhi

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-02T23:19:50Z

On Mon, Feb 2, 2026 at 3:43 PM yudhi s <learnerdatabase99@gmail.com> wrote:

>
> On Tue, Feb 3, 2026 at 1:01 AM Ron Johnson <ronljohnsonjr@gmail.com>
> wrote:
>
>> On Mon, Feb 2, 2026 at 1:39 PM yudhi s <learnerdatabase99@gmail.com>
>> wrote:
>>
>>> On Mon, Feb 2, 2026 at 8:57 PM Ron Johnson <ronljohnsonjr@gmail.com>
>>> wrote:
>>>
>>>>
>>>>> My apologies if i misunderstand the plan, But If I see,   it's
>>>>> spending ~140ms(140ms-6ms) i.e. almost all the time now, in performing the
>>>>> below nested loop join. So my question was , is there any possibility to
>>>>> reduce the resource consumption or response time further here?  Hope my
>>>>> understanding is correct here.
>>>>>
>>>>> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual
>>>>> time=*6.009..147.695* rows=1049 loops=1)
>>>>> Join Filter: ((df.ent_id)::numeric = m.ent_id)
>>>>> Rows Removed by Join Filter: 513436
>>>>> Buffers: shared hit=1939
>>>>>
>>>>
>>>> I don't see m.ent_id in the actual query.  Did you only paste a
>>>> portion of the query?
>>>>
>>>> Also, casting in a JOIN typically brutalizes the ability to use an
>>>> index.
>>>>
>>>>
>>>> Thank you.
>>> Actually i tried executing the first two CTE where the query was
>>> spending most of the time  and teh alias has changed.
>>>
>>
>> We need to see everything, not just what you think is relevant.
>>
>>
>>> Also here i have changed the real table names before putting it here,
>>> hope that is fine.
>>> However , i verified the data type of the ent_id column in "ent" its
>>> "int8" and in table "txn_tbl" is "numeric 12", so do you mean to say this
>>> difference in the data type is causing this high response time during the
>>> nested loop join? My understanding was it will be internally castable
>>> without additional burden. Also, even i tried creating an index on the "(df.ent_id)::numeric"
>>> its still reulting into same plan and response time.
>>>
>>
>> If you'd shown the "\d" table definitions like Adrian asked two days ago,
>> we'd know what indexes are on each table, and not have to beg you to
>> dispense dribs and drabs of information.
>>
>>
> I am unable to run "\d" from the dbeaver sql worksheet. However,  I have
> fetched the DDL for the three tables and their selected columns, used in
> the smaller version of the query and its plan , which I recently updated.
>
> https://gist.github.com/databasetech0073/e4290b085f8f974e315fb41bdc47a1f3
>
> https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492
>

Lines 30-32 are where most of the time and effort are taken.

I can't be certain, but changing APP_schema.ent.ent_id from NUMERIC to int8
(with a CHECK constraint to, well, constrain it to 12 digits, if really
necessary) is something I'd test.

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

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-03T09:26:14Z

On Tue, Feb 3, 2026 at 4:50 AM Ron Johnson <ronljohnsonjr@gmail.com> wrote:

> On Mon, Feb 2, 2026 at 3:43 PM yudhi s <learnerdatabase99@gmail.com>
> wrote:
>
>>
>> On Tue, Feb 3, 2026 at 1:01 AM Ron Johnson <ronljohnsonjr@gmail.com>
>> wrote:
>>
>>> On Mon, Feb 2, 2026 at 1:39 PM yudhi s <learnerdatabase99@gmail.com>
>>> wrote:
>>>
>>>> On Mon, Feb 2, 2026 at 8:57 PM Ron Johnson <ronljohnsonjr@gmail.com>
>>>> wrote:
>>>>
>>>>>
>>>>>> My apologies if i misunderstand the plan, But If I see,   it's
>>>>>> spending ~140ms(140ms-6ms) i.e. almost all the time now, in performing the
>>>>>> below nested loop join. So my question was , is there any possibility to
>>>>>> reduce the resource consumption or response time further here?  Hope my
>>>>>> understanding is correct here.
>>>>>>
>>>>>> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20) (actual
>>>>>> time=*6.009..147.695* rows=1049 loops=1)
>>>>>> Join Filter: ((df.ent_id)::numeric = m.ent_id)
>>>>>> Rows Removed by Join Filter: 513436
>>>>>> Buffers: shared hit=1939
>>>>>>
>>>>>
>>>>> I don't see m.ent_id in the actual query.  Did you only paste a
>>>>> portion of the query?
>>>>>
>>>>> Also, casting in a JOIN typically brutalizes the ability to use an
>>>>> index.
>>>>>
>>>>>
>>>>> Thank you.
>>>> Actually i tried executing the first two CTE where the query was
>>>> spending most of the time  and teh alias has changed.
>>>>
>>>
>>> We need to see everything, not just what you think is relevant.
>>>
>>>
>>>> Also here i have changed the real table names before putting it here,
>>>> hope that is fine.
>>>> However , i verified the data type of the ent_id column in "ent" its
>>>> "int8" and in table "txn_tbl" is "numeric 12", so do you mean to say this
>>>> difference in the data type is causing this high response time during the
>>>> nested loop join? My understanding was it will be internally castable
>>>> without additional burden. Also, even i tried creating an index on the "(df.ent_id)::numeric"
>>>> its still reulting into same plan and response time.
>>>>
>>>
>>> If you'd shown the "\d" table definitions like Adrian asked two days
>>> ago, we'd know what indexes are on each table, and not have to beg you to
>>> dispense dribs and drabs of information.
>>>
>>>
>> I am unable to run "\d" from the dbeaver sql worksheet. However,  I have
>> fetched the DDL for the three tables and their selected columns, used in
>> the smaller version of the query and its plan , which I recently updated.
>>
>> https://gist.github.com/databasetech0073/e4290b085f8f974e315fb41bdc47a1f3
>>
>> https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492
>>
>
> Lines 30-32 are where most of the time and effort are taken.
>
> I can't be certain, but changing APP_schema.ent.ent_id from NUMERIC to
> int8 (with a CHECK constraint to, well, constrain it to 12 digits, if
> really necessary) is something I'd test.
>
> --
>


Thank you so much.

After making the data types equal on both tables for the column ent_id the
plan now looks as below. The costing function sinow removed. So it must be
helping reduce CPU cycle consumption to some extent, But,  I still see
~100ms is spent in this step. Is there anything we can do to further drop
the response time here? Or it's the best time we can get here.

  ->  Nested Loop  (cost=262.77..1342550.91 rows=579149 width=20) (*actual
time=6.406..107.946* rows=1049 loops=1)
              Join Filter: (*df.ent_id = m.ent_id*)
              Rows Removed by Join Filter: 514648
              Buffers: shared hit=1972


Also I do see in some other steps in the plan , the casting function is
getting used. For example in the below filter. Here txn_tbl_type_nm is
defined as Varchar(25) and still it's trying to cast it to Text. Can we do
anything to avoid these force casts as these must consume the CPU cycles?

    AND txn_tbl_dcsn.txn_tbl_txn_sts_tx NOT IN ('STATUS_A','STATUS_B')
    WHERE txn_tbl.txn_tbl_type_nm IN ('TYPE1','TYPE2','TYPE3')

  ->  Index Scan Backward using txn_tbl_due_dt_idx on txn_tbl df
 (cost=0.43..115879.87 rows=1419195 width=20) (actual time=0.019..20.377
rows=43727 loops=1)
Filter: *((txn_tbl_type_nm)::text = ANY ('{TYPE1,TYPE2,TYPE3}'::text[])*)
Rows Removed by Filter: 17
Buffers: shared hit=1839

The plan is as below.

https://gist.github.com/databasetech0073/558377c1939a9291e7b72b1cbac7c9f9

Regards
Yudhi

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-03T15:59:51Z

On Tue, Feb 3, 2026 at 4:26 AM yudhi s <learnerdatabase99@gmail.com> wrote:

> On Tue, Feb 3, 2026 at 4:50 AM Ron Johnson <ronljohnsonjr@gmail.com>
> wrote:
>
>> On Mon, Feb 2, 2026 at 3:43 PM yudhi s <learnerdatabase99@gmail.com>
>> wrote:
>>
>>>
>>> On Tue, Feb 3, 2026 at 1:01 AM Ron Johnson <ronljohnsonjr@gmail.com>
>>> wrote:
>>>
>>>> On Mon, Feb 2, 2026 at 1:39 PM yudhi s <learnerdatabase99@gmail.com>
>>>> wrote:
>>>>
>>>>> On Mon, Feb 2, 2026 at 8:57 PM Ron Johnson <ronljohnsonjr@gmail.com>
>>>>> wrote:
>>>>>
>>>>>>
>>>>>>> My apologies if i misunderstand the plan, But If I see,   it's
>>>>>>> spending ~140ms(140ms-6ms) i.e. almost all the time now, in performing the
>>>>>>> below nested loop join. So my question was , is there any possibility to
>>>>>>> reduce the resource consumption or response time further here?  Hope my
>>>>>>> understanding is correct here.
>>>>>>>
>>>>>>> -> Nested Loop (cost=266.53..1548099.38 rows=411215 width=20)
>>>>>>> (actual time=*6.009..147.695* rows=1049 loops=1)
>>>>>>> Join Filter: ((df.ent_id)::numeric = m.ent_id)
>>>>>>> Rows Removed by Join Filter: 513436
>>>>>>> Buffers: shared hit=1939
>>>>>>>
>>>>>>
>>>>>> I don't see m.ent_id in the actual query.  Did you only paste a
>>>>>> portion of the query?
>>>>>>
>>>>>> Also, casting in a JOIN typically brutalizes the ability to use an
>>>>>> index.
>>>>>>
>>>>>>
>>>>>> Thank you.
>>>>> Actually i tried executing the first two CTE where the query was
>>>>> spending most of the time  and teh alias has changed.
>>>>>
>>>>
>>>> We need to see everything, not just what you think is relevant.
>>>>
>>>>
>>>>> Also here i have changed the real table names before putting it here,
>>>>> hope that is fine.
>>>>> However , i verified the data type of the ent_id column in "ent" its
>>>>> "int8" and in table "txn_tbl" is "numeric 12", so do you mean to say this
>>>>> difference in the data type is causing this high response time during the
>>>>> nested loop join? My understanding was it will be internally castable
>>>>> without additional burden. Also, even i tried creating an index on the "(df.ent_id)::numeric"
>>>>> its still reulting into same plan and response time.
>>>>>
>>>>
>>>> If you'd shown the "\d" table definitions like Adrian asked two days
>>>> ago, we'd know what indexes are on each table, and not have to beg you to
>>>> dispense dribs and drabs of information.
>>>>
>>>>
>>> I am unable to run "\d" from the dbeaver sql worksheet. However,  I have
>>> fetched the DDL for the three tables and their selected columns, used in
>>> the smaller version of the query and its plan , which I recently updated.
>>>
>>> https://gist.github.com/databasetech0073/e4290b085f8f974e315fb41bdc47a1f3
>>>
>>> https://gist.github.com/databasetech0073/344df46c328e02b98961fab0cd221492
>>>
>>
>> Lines 30-32 are where most of the time and effort are taken.
>>
>> I can't be certain, but changing APP_schema.ent.ent_id from NUMERIC to
>> int8 (with a CHECK constraint to, well, constrain it to 12 digits, if
>> really necessary) is something I'd test.
>>
>> --
>>
>
>
> Thank you so much.
>
> After making the data types equal on both tables for the column ent_id the
> plan now looks as below. The costing function sinow removed. So it must be
> helping reduce CPU cycle consumption to some extent, But,  I still see
> ~100ms is spent in this step. Is there anything we can do to further drop
> the response time here? Or it's the best time we can get here.
>
>   ->  Nested Loop  (cost=262.77..1342550.91 rows=579149 width=20) (*actual
> time=6.406..107.946* rows=1049 loops=1)
>               Join Filter: (*df.ent_id = m.ent_id*)
>               Rows Removed by Join Filter: 514648
>               Buffers: shared hit=1972
>

Hmm.  What does pg_stat_user_tables say about when you last analyzed and
vacuumed APP_schema.txn_tbl and APP_schema.ent?

Beyond "aggressively keep those two tables analyzed, via reducing
autovacuum_analyze_scale_factor to something like 0.05, and adding
'vacuumdb -d mumble -j2 --analyze-only -t APP_schema.txn_tbl -t
APP_schema.ent' to crontab", I'm out of ideas.  An 85% speed improvement is
nothing to sneeze at, though.


> Also I do see in some other steps in the plan , the casting function is
> getting used. For example in the below filter. Here txn_tbl_type_nm is
> defined as Varchar(25) and still it's trying to cast it to Text. Can we do
> anything to avoid these force casts as these must consume the CPU cycles?
>
>     AND txn_tbl_dcsn.txn_tbl_txn_sts_tx NOT IN ('STATUS_A','STATUS_B')
>     WHERE txn_tbl.txn_tbl_type_nm IN ('TYPE1','TYPE2','TYPE3')
>
>   ->  Index Scan Backward using txn_tbl_due_dt_idx on txn_tbl df
>  (cost=0.43..115879.87 rows=1419195 width=20) (actual time=0.019..20.377
> rows=43727 loops=1)
> Filter: *((txn_tbl_type_nm)::text = ANY ('{TYPE1,TYPE2,TYPE3}'::text[])*)
> Rows Removed by Filter: 17
> Buffers: shared hit=1839
>

There is no VARCHAR or CHAR; there is only TEXT.  Thus, this is 100%
expected and normal.

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

Re: Top -N Query performance issue and high CPU usage

Adrian Klaver <adrian.klaver@aklaver.com> — 2026-02-03T16:07:39Z

On 2/3/26 07:59, Ron Johnson wrote:

> 
> 
> There is no VARCHAR or CHAR; there is only TEXT.  Thus, this is 100% 
> expected and normal.

What Ron is saying is that there are varchar and char types, but they 
boil down to text per:

https://www.postgresql.org/docs/current/datatype-character.html

"text is PostgreSQL's native string data type, in that most built-in 
functions operating on strings are declared to take or return text not 
character varying. For many purposes, character varying acts as though 
it were a domain over text."

As to performance see:

"
Tip

There is no performance difference among these three types, apart from 
increased storage space when using the blank-padded type, and a few 
extra CPU cycles to check the length when storing into a 
length-constrained column. While character(n) has performance advantages 
in some other database systems, there is no such advantage in 
PostgreSQL; in fact character(n) is usually the slowest of the three 
because of its additional storage costs. In most situations text or 
character varying should be used instead.
"

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

-- 
Adrian Klaver
adrian.klaver@aklaver.com

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-03T18:50:20Z

On Tue, 3 Feb, 2026, 9:37 pm Adrian Klaver, <adrian.klaver@aklaver.com>
wrote:

> On 2/3/26 07:59, Ron Johnson wrote:
>
> >
> >
> > There is no VARCHAR or CHAR; there is only TEXT.  Thus, this is 100%
> > expected and normal.
>
> What Ron is saying is that there are varchar and char types, but they
> boil down to text per:
>
> https://www.postgresql.org/docs/current/datatype-character.html
>
> "text is PostgreSQL's native string data type, in that most built-in
> functions operating on strings are declared to take or return text not
> character varying. For many purposes, character varying acts as though
> it were a domain over text."
>
> As to performance see:
>
> "
> Tip
>
> There is no performance difference among these three types, apart from
> increased storage space when using the blank-padded type, and a few
> extra CPU cycles to check the length when storing into a
> length-constrained column. While character(n) has performance advantages
> in some other database systems, there is no such advantage in
> PostgreSQL; in fact character(n) is usually the slowest of the three
> because of its additional storage costs. In most situations text or
> character varying should be used instead.
> "
>

Thank you. I was looking into those casting(::text) in the explain plan
output in similar way (as it was happening for int8 to numeric join
scenario) and was thinking, may be it's spending some cpu cycles on doing
these ::text casting behind the scenes for that column and if there is
someway(data type change) to stop those. But from your explanation, it
looks like those representation in the query plan is normal and have no
performance overhead as such. Thanks again.

In regards to the below, "nested loop" having response time of 100ms. I
understand, here the casting function us now removed after changing the
data type of columns to match in both side of the join.

So, is this expected to do a nested loop on 500k rows to take 100ms?

->  Nested Loop  (cost=262.77..1342550.91 rows=579149 width=20) (*actual
time=6.406..107.946* rows=1049 loops=1)
              Join Filter: (*df.ent_id = m.ent_id*)
              Rows Removed by Join Filter: 514648
              Buffers: shared hit=1972

Regards
Yudhi

Re: Top -N Query performance issue and high CPU usage

Ron Johnson <ronljohnsonjr@gmail.com> — 2026-02-03T20:51:44Z

On Tue, Feb 3, 2026 at 1:50 PM yudhi s <learnerdatabase99@gmail.com> wrote:

>
>
> On Tue, 3 Feb, 2026, 9:37 pm Adrian Klaver, <adrian.klaver@aklaver.com>
> wrote:
>
>> On 2/3/26 07:59, Ron Johnson wrote:
>>
>> >
>> >
>> > There is no VARCHAR or CHAR; there is only TEXT.  Thus, this is 100%
>> > expected and normal.
>>
>> What Ron is saying is that there are varchar and char types, but they
>> boil down to text per:
>>
>> https://www.postgresql.org/docs/current/datatype-character.html
>>
>> "text is PostgreSQL's native string data type, in that most built-in
>> functions operating on strings are declared to take or return text not
>> character varying. For many purposes, character varying acts as though
>> it were a domain over text."
>>
>> As to performance see:
>>
>> "
>> Tip
>>
>> There is no performance difference among these three types, apart from
>> increased storage space when using the blank-padded type, and a few
>> extra CPU cycles to check the length when storing into a
>> length-constrained column. While character(n) has performance advantages
>> in some other database systems, there is no such advantage in
>> PostgreSQL; in fact character(n) is usually the slowest of the three
>> because of its additional storage costs. In most situations text or
>> character varying should be used instead.
>> "
>>
>
> Thank you. I was looking into those casting(::text) in the explain plan
> output in similar way (as it was happening for int8 to numeric join
> scenario) and was thinking, may be it's spending some cpu cycles on doing
> these ::text casting behind the scenes for that column and if there is
> someway(data type change) to stop those. But from your explanation, it
> looks like those representation in the query plan is normal and have no
> performance overhead as such. Thanks again.
>
> In regards to the below, "nested loop" having response time of 100ms. I
> understand, here the casting function us now removed after changing the
> data type of columns to match in both side of the join.
>
> So, is this expected to do a nested loop on 500k rows to take 100ms?
>

HAVE YOU ANALYZED THE TABLES?


>
> ->  Nested Loop  (cost=262.77..1342550.91 rows=579149 width=20) (*actual
> time=6.406..107.946* rows=1049 loops=1)
>               Join Filter: (*df.ent_id = m.ent_id*)
>               Rows Removed by Join Filter: 514648
>               Buffers: shared hit=1972
>

Decompose complex problems into a small problem, then start adding stuff.

https://gist.github.com/databasetech0073/6688701431dc4bf4eaab8d345c1dc65f

In this case, I would run SELECT * FROM limited_txns, to get a base
EXPLAIN, then strip out all WHERE clauses, the ORDER BY and the LIMIT then
run it again for another EXPLAIN.

Then add back lines 33-34 and EXPLAIN.  Then line 7, etc, etc saving each
EXPLAIN.  See what makes it break.

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

Re: Top -N Query performance issue and high CPU usage

Peter J. Holzer <hjp-pgsql@hjp.at> — 2026-02-03T21:02:19Z

On 2026-02-04 00:20:20 +0530, yudhi s wrote:
> 
> 
> On Tue, 3 Feb, 2026, 9:37 pm Adrian Klaver, <adrian.klaver@aklaver.com> wrote:
> 
>     On 2/3/26 07:59, Ron Johnson wrote:
> 
>     >
>     >
>     > There is no VARCHAR or CHAR; there is only TEXT.  Thus, this is 100%
>     > expected and normal.
> 
>     What Ron is saying is that there are varchar and char types, but they
>     boil down to text per:
> 
>     https://www.postgresql.org/docs/current/datatype-character.html
> 
>     "text is PostgreSQL's native string data type, in that most built-in
>     functions operating on strings are declared to take or return text not
>     character varying. For many purposes, character varying acts as though
>     it were a domain over text."
> 
>     As to performance see:
> 
>     "
>     Tip
> 
>     There is no performance difference among these three types, apart from
>     increased storage space when using the blank-padded type, and a few
>     extra CPU cycles to check the length when storing into a
>     length-constrained column. While character(n) has performance advantages
>     in some other database systems, there is no such advantage in
>     PostgreSQL; in fact character(n) is usually the slowest of the three
>     because of its additional storage costs. In most situations text or
>     character varying should be used instead.
>     "
> 
> 
> Thank you. I was looking into those casting(::text) in the explain plan output
> in similar way (as it was happening for int8 to numeric join scenario) and was
> thinking, may be it's spending some cpu cycles on doing these ::text casting
> behind the scenes for that column and if there is someway(data type change) to
> stop those. But from your explanation, it looks like those representation in
> the query plan is normal and have no performance overhead as such. Thanks
> again. 
> 
> In regards to the below, "nested loop" having response time of 100ms. I
> understand, here the casting function us now removed after changing the data
> type of columns to match in both side of the join.
> 
> So, is this expected to do a nested loop on 500k rows to take 100ms?
> 
> ->  Nested Loop  (cost=262.77..1342550.91 rows=579149 width=20) (actual time=
> 6.406..107.946 rows=1049 loops=1)
>               Join Filter: (df.ent_id = m.ent_id)
>               Rows Removed by Join Filter: 514648
>               Buffers: shared hit=1972
> 

Take a closer look at what that nested loop does:

        ->  Nested Loop  (cost=266.53..1548099.38 rows=411215 width=20) (actual time=6.009..147.695 rows=1049 loops=1)
              Join Filter: ((df.ent_id)::numeric = m.ent_id)
              Rows Removed by Join Filter: 513436
              Buffers: shared hit=1939
              ->  Index Scan Backward using txn_tbl_due_dt_idx on txn_tbl df  (cost=0.43..115471.09 rows=1417983 width=20) (actual time=0.047..20.155 rows=43626 loops=1)
                    Filter: ((txn_tbl_type_nm)::text = ANY ('{.......}'::text[]))
                    Rows Removed by Filter: 17
                    Buffers: shared hit=1816
              ->  Materialize  (cost=266.10..328.09 rows=58 width=16) (actual time=0.000..0.001 rows=12 loops=43626)
                  [lots of stuff]

It scans backwards through txn_tbl_due_dt_idx which returns 43626 rows
and takes 20 milliseconds.

For each of these rows it performs the "Materialize" node, which in turn
does lots of stuff, but whatever it is, it's fast and probably not worth
optimizing. The problem is that it's done 43626 times, which takes
another 120ms.

So the most promising way to proceed it to try to reduce those 43626
rows. Since the query is already scanning txn_tbl_due_dt_idx from newest
to oldest, is there a cutoff date where it is safe to ignore everything
older? If you can get it to scan only 2000 rows that would be 20 times
faster ...

(I'm a bit confused by your naming. I'm guessing that the "Index Scan
Backward using txn_tbl_due_dt_idx" is there because of the "order by
df.tran_date desc", but the name of the index and the column don't
match.)

        hjp

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

Re: Top -N Query performance issue and high CPU usage

felix.quintgz@yahoo.com — 2026-02-04T15:48:13Z

Have you tried adding an index to txn_tbl.txn_type?
And a vacuum on all tables? It seems the visibility map is outdated.

I'm using https://explain.dalibo.com to view the plan visually; it's more convenient.

You could use the option to periodically save the results of queries with common filters to another table, and then retrieve the results from that table when a user performs a query with their own filters.
You should also store the user's query results somewhere for a while to prevent excessive database access.

I imagine this is some kind of dashboard that each user is taken to after authenticating. It looks nice in presentations, but after a while in production, it can make the system unusable. I had to remove similar charts from the homepage of a system because after a year of work, they were taking a minute to load.

On Saturday, January 31, 2026 at 08:30:33 AM GMT-5, yudhi s <learnerdatabase99@gmail.com> wrote:
Hello Experts,
We have a "Select" query which is using three to five main transaction tables (txn_tbl, txn_status, txn_decision, txn_sale, ath) holding ~2million rows in each of them(which is going to increase to have ~50-100million in future) and others(6-7) tables out of which some are master and some other small tables.

When we are running this query , and it's taking ~2-3seconds , however when we hit this query from 10-15 session at same time its causing CPU spike up to ~50-60% for the DB instance and this is increasing and touching 90% when we are increasing the hits further to 40-50 times concurrently.

This query is going to be called in the first page of an UI screen and is supposed to show the latest 1000 rows based on a certain transaction date. This query is supposed to allow thousands of users to hit this same query at the first landing page at the same time.

Its postgres version 17. The instance has 2-VCPU and 16GB RAM.

I have the following questions.

1)Why is this query causing a high cpu spike ,if there is any way in postgres to understand what part/line of the query is contributing to the high cpu time?
2)How can we tune this query to further reduce response time and mainly CPU consumption ? Is any additional index or anything will make this plan better further?
3) Is there any guidance or best practices exists , to create/design top N-queries for such UI scenarios where performance is an important factor?
4)And based on the CPU core and memory , is there any calculation by using which , we can say that this machine can support a maximum N number of concurrent queries of such type beyond which we need more cpu cores machines?
Below is the query and its current plan:-https://gist.github.com/databasetech0073/6688701431dc4bf4eaab8d345c1dc65f
RegardsYudhi

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-05T08:20:26Z

On Wed, Feb 4, 2026 at 2:32 AM Peter J. Holzer <hjp-pgsql@hjp.at> wrote:

> On 2026-02-04 00:20:20 +0530, yudhi s wrote:
> >
> >
> > On Tue, 3 Feb, 2026, 9:37 pm Adrian Klaver, <adrian.klaver@aklaver.com>
> wrote:
> >
> >     On 2/3/26 07:59, Ron Johnson wrote:
> >
> >     >
> >     >
> >     > There is no VARCHAR or CHAR; there is only TEXT.  Thus, this is
> 100%
> >     > expected and normal.
> >
> >     What Ron is saying is that there are varchar and char types, but they
> >     boil down to text per:
> >
> >     https://www.postgresql.org/docs/current/datatype-character.html
> >
> >     "text is PostgreSQL's native string data type, in that most built-in
> >     functions operating on strings are declared to take or return text
> not
> >     character varying. For many purposes, character varying acts as
> though
> >     it were a domain over text."
> >
> >     As to performance see:
> >
> >     "
> >     Tip
> >
> >     There is no performance difference among these three types, apart
> from
> >     increased storage space when using the blank-padded type, and a few
> >     extra CPU cycles to check the length when storing into a
> >     length-constrained column. While character(n) has performance
> advantages
> >     in some other database systems, there is no such advantage in
> >     PostgreSQL; in fact character(n) is usually the slowest of the three
> >     because of its additional storage costs. In most situations text or
> >     character varying should be used instead.
> >     "
> >
> >
> > Thank you. I was looking into those casting(::text) in the explain plan
> output
> > in similar way (as it was happening for int8 to numeric join scenario)
> and was
> > thinking, may be it's spending some cpu cycles on doing these ::text
> casting
> > behind the scenes for that column and if there is someway(data type
> change) to
> > stop those. But from your explanation, it looks like those
> representation in
> > the query plan is normal and have no performance overhead as such. Thanks
> > again.
> >
> > In regards to the below, "nested loop" having response time of 100ms. I
> > understand, here the casting function us now removed after changing the
> data
> > type of columns to match in both side of the join.
> >
> > So, is this expected to do a nested loop on 500k rows to take 100ms?
> >
> > ->  Nested Loop  (cost=262.77..1342550.91 rows=579149 width=20) (actual
> time=
> > 6.406..107.946 rows=1049 loops=1)
> >               Join Filter: (df.ent_id = m.ent_id)
> >               Rows Removed by Join Filter: 514648
> >               Buffers: shared hit=1972
> >
>
> Take a closer look at what that nested loop does:
>
>         ->  Nested Loop  (cost=266.53..1548099.38 rows=411215 width=20)
> (actual time=6.009..147.695 rows=1049 loops=1)
>               Join Filter: ((df.ent_id)::numeric = m.ent_id)
>               Rows Removed by Join Filter: 513436
>               Buffers: shared hit=1939
>               ->  Index Scan Backward using txn_tbl_due_dt_idx on txn_tbl
> df  (cost=0.43..115471.09 rows=1417983 width=20) (actual time=0.047..20.155
> rows=43626 loops=1)
>                     Filter: ((txn_tbl_type_nm)::text = ANY
> ('{.......}'::text[]))
>                     Rows Removed by Filter: 17
>                     Buffers: shared hit=1816
>               ->  Materialize  (cost=266.10..328.09 rows=58 width=16)
> (actual time=0.000..0.001 rows=12 loops=43626)
>                   [lots of stuff]
>
> It scans backwards through txn_tbl_due_dt_idx which returns 43626 rows
> and takes 20 milliseconds.
>
> For each of these rows it performs the "Materialize" node, which in turn
> does lots of stuff, but whatever it is, it's fast and probably not worth
> optimizing. The problem is that it's done 43626 times, which takes
> another 120ms.
>
> So the most promising way to proceed it to try to reduce those 43626
> rows. Since the query is already scanning txn_tbl_due_dt_idx from newest
> to oldest, is there a cutoff date where it is safe to ignore everything
> older? If you can get it to scan only 2000 rows that would be 20 times
> faster ...
>
> (I'm a bit confused by your naming. I'm guessing that the "Index Scan
> Backward using txn_tbl_due_dt_idx" is there because of the "order by
> df.tran_date desc", but the name of the index and the column don't
> match.)
>
>
Got it. Thank you.

Yes , As folks here suggested, I created the new index on  "tran_date"
which is used as "order by desc" to only show the newest 1000 rows with a
"limit" operator. And this index backward scan is getting used and helping
to a large extent to drop the response time as opposed to early "table
sequential scan'.

Now , in this query as you said we need to see if we can further put a
filter on the tran_date so as to minimize the records from table txn_tbl
which would minimize the number of loops the materialize operation is
happening. Need to check if that is possible without impacting business
functionality. However,  Is there any way this materialized operation will
happen once i.e kind of a "HASH" Join fashion (where only once it will be
scanned) rather in a nested loop fashion which is currently happening ~43K
times?

Another question i had in mind as there is the filter " Filter:
((txn_tbl_type_nm)::text = ANY ('{.......}'::text[]))" , will including
this column in the index i.e. making it composite (TRAN_DATE,
txn_tbl_type_nm) will be a good idea. Mainly in scenarios where this
txn_tbl_type_nm will filter out more rows i.e. ~100-500K + rows?

Regards
Yudhi

Re: Top -N Query performance issue and high CPU usage

yudhi s <learnerdatabase99@gmail.com> — 2026-02-05T08:35:49Z

On Wed, Feb 4, 2026 at 9:18 PM <felix.quintgz@yahoo.com> wrote:

>
> Have you tried adding an index to txn_tbl.txn_type?
> And a vacuum on all tables? It seems the visibility map is outdated.
>
> I'm using https://explain.dalibo.com to view the plan visually; it's more
> convenient.
>
> You could use the option to periodically save the results of queries with
> common filters to another table, and then retrieve the results from that
> table when a user performs a query with their own filters.
> You should also store the user's query results somewhere for a while to
> prevent excessive database access.
>
> I imagine this is some kind of dashboard that each user is taken to after
> authenticating. It looks nice in presentations, but after a while in
> production, it can make the system unusable. I had to remove similar charts
> from the homepage of a system because after a year of work, they were
> taking a minute to load.
>
>
>  On Saturday, January 31, 2026 at 08:30:33 AM GMT-5, yudhi s <
> learnerdatabase99@gmail.com> wrote:
>  Hello Experts,
>  We have a "Select" query which is using three to five main transaction
> tables (txn_tbl, txn_status, txn_decision, txn_sale, ath) holding ~2million
> rows in each of them(which is going to increase to have ~50-100million in
> future) and others(6-7) tables out of which some are master and some other
> small tables.
>
> When we are running this query , and it's taking ~2-3seconds , however
> when we hit this query from 10-15 session at same time its causing CPU
> spike up to ~50-60% for the DB instance and this is increasing and touching
> 90% when we are increasing the hits further to 40-50 times concurrently.
>
> This query is going to be called in the first page of an UI screen and is
> supposed to show the latest 1000 rows based on a certain transaction date.
> This query is supposed to allow thousands of users to hit this same query
> at the first landing page at the same time.
>
> Its postgres version 17.  The instance has 2-VCPU and 16GB RAM.
>
> I have the following questions.
>
> 1)Why is this query causing a high cpu spike ,if there is any way in
> postgres to understand what part/line of the query is contributing to the
> high cpu time?
> 2)How can we tune this query to further reduce response time and mainly
> CPU consumption ? Is any additional index or anything will make this plan
> better further?
> 3) Is there any guidance or best practices exists , to create/design top
> N-queries for such UI scenarios where performance is an important factor?
> 4)And based on the CPU core and memory , is there any calculation by using
> which , we can say that this machine can support a maximum N number of
> concurrent queries of such type beyond which we need more cpu cores
> machines?
> Below is the query and its current plan:-
> https://gist.github.com/databasetech0073/6688701431dc4bf4eaab8d345c1dc65f
> RegardsYudhi
>
>
>
As folks suggested , adding an index on "tran_date" and combining the CTE
to two, and making the data type equal for the "ent_id" has helped reduce
the response to a large extent. Now I am trying to see if we can reduce any
further. As most of the time(100-20=~80ms) is now on materialize loop which
is happening 43K times.

Also thinking if adding "txn_tbl_type_nm" column to the index i.e.
composite index on (tran_date,txn_tbl_type_nm) will be advisable , in cases
where , ~500K rows will be filtered  by the *txn_tbl_type_nm *filter
criteria (currently its just 17 rows getting filtered though for this case).

https://gist.github.com/databasetech0073/558377c1939a9291e7b72b1cbac7c9f9

-> Nested Loop (cost=263.20..1680202.56 rows=483106 width=20) (actual
time=6.421..111.220 rows=1000 loops=1)
Buffers: shared hit=6168
-> Nested Loop (cost=262.77..1342550.91 rows=579149 width=20) (*actual
time=6.406..107.946* rows=1049 loops=1)
Join Filter: (df.ent_id = m.ent_id)
Rows Removed by Join Filter: 514648
Buffers: shared hit=1972
-> Index Scan Backward using txn_tbl_due_dt_idx on txn_tbl df
(cost=0.43..115879.87 rows=1419195 width=20) (*actual time=0.019..20.377*
rows=43727 loops=1)
*Filter: ((txn_tbl_type_nm)::text = ANY ('{TYPE1,TYPE2,TYPE3}'::text[]))*
*Rows Removed by Filter: 17*
Buffers: shared hit=1839
-> Materialize (cost=262.35..364.01 rows=58 width=8) (actual
time=0.000..0.001 rows=12 loops=43727)
Buffers: shared hit=133



Regards
Yudhi

Re: Top -N Query performance issue and high CPU usage

Thiemo Kellner <thiemo@gelassene-pferde.biz> — 2026-02-05T11:32:03Z

A nested loop is not bad per se, at least in Oracle. It depends on the data. If the number of rows participating in the join table are very unequal, the NL is the more efficient join. I would presume that every join of a fact table with a dimension table belongs to that category.