Re: Dirty reads on index scan,

[Koen De Groote]

Alright.

So, if I want to speed up the query, apart from trying to vacuum it
beforehand, I suspect I've hit the limit of what this query can do?

Because, the table is just going to keep growing. And it's a usually a
query that runs one time per day, so it's a cold run each time.

Is this just going to get slower and slower and there's nothing that can be
done about it?

Regards,
Koen De Groote



On Thu, Sep 21, 2023 at 9:30 PM Laurenz Albe 
wrote:

> On Thu, 2023-09-21 at 17:05 +0200, Koen De Groote wrote:
> > I'm doing the following query:
> > select * from my_table where hasbeenchecked = true and hasbeenverified =
> true and insert_timestamp <= '2023-09-01 00:00:00.000' limit 1000;
> >
> > The date is an example, it is the format that is used in the query.
> >
> > The table has 81M rows. Is 50GB in size. And the index is 34MB
> >
> > The index is as follows:
> > btree (insert_timestamp DESC) WHERE hasbeenchecked = true
> AND hasbeenverified = true
> >
> > I'm seeing a slow query first, then a fast one, and if I move the date,
> a slow query again.
> >
> > What I'm seeing is:
> > Attempt 1:
> > Hit: 5171(40MB)
> > Read: 16571(130MB)
> > Dirtied: 3940(31MB)
> >
> > Attempt 2:
> > Hit: 21745 (170MB)
> > Read: Nothing
> > Dirtied: Nothing.
> >
> > It's slow once, then consistently fast, and then slow again if I move
> the date around.
> > And by slow I mean: around 60 seconds. And fast is below 1 second.
>
> That's normal behavior: after the first execution, the data are cached, so
> the query
> becomes much faster.
>
> Dirtying pages happens because the first reader has to set hint bits,
> which is an extra
> chore.  You can avoid that if you VACUUM the table before you query it.
>
> Yours,
> Laurenz Albe
>

Re: Dirty reads on index scan,

[Laurenz Albe]

On Fri, 2023-09-22 at 10:35 +0200, Koen De Groote wrote:
> On Thu, Sep 21, 2023 at 9:30 PM Laurenz Albe  wrote:
> > On Thu, 2023-09-21 at 17:05 +0200, Koen De Groote wrote:
> > > I'm doing the following query:
> > > select * from my_table where hasbeenchecked = true and hasbeenverified = 
> > > true and insert_timestamp <= '2023-09-01 00:00:00.000' limit 1000;
> > > 
> > > The date is an example, it is the format that is used in the query.
> > > 
> > > The table has 81M rows. Is 50GB in size. And the index is 34MB
> > > 
> > > The index is as follows:
> > > btree (insert_timestamp DESC) WHERE hasbeenchecked = true AND 
> > > hasbeenverified = true
> > > 
> > > I'm seeing a slow query first, then a fast one, and if I move the date, a 
> > > slow query again.
> > > 
> > > What I'm seeing is:
> > > Attempt 1:
> > > Hit: 5171(40MB)
> > > Read: 16571(130MB)
> > > Dirtied: 3940(31MB)
> > > 
> > > Attempt 2:
> > > Hit: 21745 (170MB)
> > > Read: Nothing
> > > Dirtied: Nothing.
> > > 
> > > It's slow once, then consistently fast, and then slow again if I move the 
> > > date around.
> > > And by slow I mean: around 60 seconds. And fast is below 1 second.
> > 
> > That's normal behavior: after the first execution, the data are cached, so 
> > the query
> > becomes much faster.
> > 
> > Dirtying pages happens because the first reader has to set hint bits, which 
> > is an extra
> > chore.  You can avoid that if you VACUUM the table before you query it.
>
> So, if I want to speed up the query, apart from trying to vacuum it 
> beforehand, I suspect
> I've hit the limit of what this query can do?
>
> Because, the table is just going to keep growing. And it's a usually a query 
> that runs one
> time per day, so it's a cold run each time.
>
> Is this just going to get slower and slower and there's nothing that can be 
> done about it?

Essentially yes.

If the table does not have too many columns, or you can be more selective than 
"SELECT *",
you could use an index-only scan with an index like

  CREATE INDEX ON my_table (insert_timestamp)
 INCLUDE (/* all the columns in the SELECT list */)
 WHERE hasbeenchecked AND hasbeenverified;

  VACUUM my_table;

You need to configure autovacuum so that it vacuums the table often enough if 
you want
an efficient index-only scan.

If that is not feasible, you can gain speed by clustering the table.  For that, 
you need
a different index:

  CREATE INDEX ckuster_idx ON my_table (hasbeenchecked, hasbeenverified, 
insert_timestamp);

  CLUSTER my_table USING cluster_idx;  -- attention: rewrites the table

That should speed up the query considerably, because it will have to read way 
fewer pages
from disk.  However, CLUSTER is not without problems.  Look at the 
documentation for the
caveats.

Yours,
Laurenz Albe

Re: Dirty reads on index scan,

[Frits Hoogland]

The actual thing that might be good to see is the query plan (explain).
It is commonly regarded an issue to select ‘*’, in many cases only a subset of 
the rows are needed, but I don’t know your exact case.
If a limited number of columns are actually needed from the table, it might 
help to create an index which has got all the columns in the index, either 
directly for the index, or included with the index.
This is called a covering index, and could prevent the need to read the actual 
table, which is visible by the row source 'index only scan’.
But that potential can only be assessed by looking at the explain output.

A covering index needs the visibility map to be recent for the blocks, 
otherwise a table visit must be done to get the latest tuple state. This can be 
done by vacuuming.

When your query is as efficient as it can be, there are two things left.
One is that blocks in the database buffer cache that are not frequently 
accessed will age out in favour of blocks that are accessed more recently. 
On the operating system, the same mechanism takes place, postgres reads data 
buffered, which means the operating system caches the IOs for the database 
blocks too.

This means that if you query data that is stored in blocks that are not 
recently used, these will not be present in the database cache, and not in the 
operating system cache, and thus require a physical IO from disk to be 
obtained. If the amount of blocks relative to the caches is modest, another 
execute of the same SQL can take advantage, and thus result in much lower 
latency.

You describe the query to be using a timestamp. If the timestamp moves forward 
in time, and the amount of data is equal over time, then the latency for the 
two scenario’s should remain stable. 
If the amount of data increases over time, and thus more blocks are needed to 
be read because more rows are stored that needs scanning to get a result, then 
the latency will increase.

Frits Hoogland




> On 22 Sep 2023, at 10:35, Koen De Groote  wrote:
> 
> Alright.
> 
> So, if I want to speed up the query, apart from trying to vacuum it 
> beforehand, I suspect I've hit the limit of what this query can do?
> 
> Because, the table is just going to keep growing. And it's a usually a query 
> that runs one time per day, so it's a cold run each time.
> 
> Is this just going to get slower and slower and there's nothing that can be 
> done about it?
> 
> Regards,
> Koen De Groote
> 
> 
> 
> On Thu, Sep 21, 2023 at 9:30 PM Laurenz Albe  > wrote:
>> On Thu, 2023-09-21 at 17:05 +0200, Koen De Groote wrote:
>> > I'm doing the following query:
>> > select * from my_table where hasbeenchecked = true and hasbeenverified = 
>> > true and insert_timestamp <= '2023-09-01 00:00:00.000' limit 1000;
>> > 
>> > The date is an example, it is the format that is used in the query.
>> > 
>> > The table has 81M rows. Is 50GB in size. And the index is 34MB
>> > 
>> > The index is as follows:
>> > btree (insert_timestamp DESC) WHERE hasbeenchecked = true AND 
>> > hasbeenverified = true
>> > 
>> > I'm seeing a slow query first, then a fast one, and if I move the date, a 
>> > slow query again.
>> > 
>> > What I'm seeing is:
>> > Attempt 1:
>> > Hit: 5171(40MB)
>> > Read: 16571(130MB)
>> > Dirtied: 3940(31MB)
>> > 
>> > Attempt 2:
>> > Hit: 21745 (170MB)
>> > Read: Nothing
>> > Dirtied: Nothing.
>> > 
>> > It's slow once, then consistently fast, and then slow again if I move the 
>> > date around.
>> > And by slow I mean: around 60 seconds. And fast is below 1 second.
>> 
>> That's normal behavior: after the first execution, the data are cached, so 
>> the query
>> becomes much faster.
>> 
>> Dirtying pages happens because the first reader has to set hint bits, which 
>> is an extra
>> chore.  You can avoid that if you VACUUM the table before you query it.
>> 
>> Yours,
>> Laurenz Albe

Re: Dirty reads on index scan,

[Koen De Groote]

The "select * " is a replacement for the actual fields, which are all
queried. I simply want to avoid pasting the entire query. The names that
are there, too, are edited.

>From what I'm reading, my best chance is to limit the amount of variables I
need and change to index, plus tune for more frequent vacuuming of the
table. I'll look into that.

Thanks for the advice, both of you.

Regards,
Koen De Groote

On Fri, Sep 22, 2023 at 3:22 PM Frits Hoogland 
wrote:

> The actual thing that might be good to see is the query plan (explain).
> It is commonly regarded an issue to select ‘*’, in many cases only a
> subset of the rows are needed, but I don’t know your exact case.
> If a limited number of columns are actually needed from the table, it
> might help to create an index which has got all the columns in the index,
> either directly for the index, or included with the index.
> This is called a covering index, and could prevent the need to read the
> actual table, which is visible by the row source 'index only scan’.
> But that potential can only be assessed by looking at the explain output.
>
> A covering index needs the visibility map to be recent for the blocks,
> otherwise a table visit must be done to get the latest tuple state. This
> can be done by vacuuming.
>
> When your query is as efficient as it can be, there are two things left.
> One is that blocks in the database buffer cache that are not frequently
> accessed will age out in favour of blocks that are accessed more recently.
> On the operating system, the same mechanism takes place, postgres reads
> data buffered, which means the operating system caches the IOs for the
> database blocks too.
>
> This means that if you query data that is stored in blocks that are not
> recently used, these will not be present in the database cache, and not in
> the operating system cache, and thus require a physical IO from disk to be
> obtained. If the amount of blocks relative to the caches is modest, another
> execute of the same SQL can take advantage, and thus result in much lower
> latency.
>
> You describe the query to be using a timestamp. If the timestamp moves
> forward in time, and the amount of data is equal over time, then the
> latency for the two scenario’s should remain stable.
> If the amount of data increases over time, and thus more blocks are needed
> to be read because more rows are stored that needs scanning to get a
> result, then the latency will increase.
>
> *Frits Hoogland*
>
>
>
>
> On 22 Sep 2023, at 10:35, Koen De Groote  wrote:
>
> Alright.
>
> So, if I want to speed up the query, apart from trying to vacuum it
> beforehand, I suspect I've hit the limit of what this query can do?
>
> Because, the table is just going to keep growing. And it's a usually a
> query that runs one time per day, so it's a cold run each time.
>
> Is this just going to get slower and slower and there's nothing that can
> be done about it?
>
> Regards,
> Koen De Groote
>
>
>
> On Thu, Sep 21, 2023 at 9:30 PM Laurenz Albe 
> wrote:
>
>> On Thu, 2023-09-21 at 17:05 +0200, Koen De Groote wrote:
>> > I'm doing the following query:
>> > select * from my_table where hasbeenchecked = true and hasbeenverified
>> = true and insert_timestamp <= '2023-09-01 00:00:00.000' limit 1000;
>> >
>> > The date is an example, it is the format that is used in the query.
>> >
>> > The table has 81M rows. Is 50GB in size. And the index is 34MB
>> >
>> > The index is as follows:
>> > btree (insert_timestamp DESC) WHERE hasbeenchecked = true
>> AND hasbeenverified = true
>> >
>> > I'm seeing a slow query first, then a fast one, and if I move the date,
>> a slow query again.
>> >
>> > What I'm seeing is:
>> > Attempt 1:
>> > Hit: 5171(40MB)
>> > Read: 16571(130MB)
>> > Dirtied: 3940(31MB)
>> >
>> > Attempt 2:
>> > Hit: 21745 (170MB)
>> > Read: Nothing
>> > Dirtied: Nothing.
>> >
>> > It's slow once, then consistently fast, and then slow again if I move
>> the date around.
>> > And by slow I mean: around 60 seconds. And fast is below 1 second.
>>
>> That's normal behavior: after the first execution, the data are cached,
>> so the query
>> becomes much faster.
>>
>> Dirtying pages happens because the first reader has to set hint bits,
>> which is an extra
>> chore.  You can avoid that if you VACUUM the table before you query it.
>>
>> Yours,
>> Laurenz Albe
>>
>
>