cache magically filled?

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Hi,

While checking a performance issue, I came across something really strange:
 From Sybase Central, I stopped and restarted a database on an engine which  
kept running.
Then I opened ISQL which was the only connection to the newly started  
database,
ran "call sa_flush_cache()",
changed the plan settings to graphical with statistics,
entered the select statement and hit Get Plan without having run the  
statement before.

But the plan tells me it found most of the data in cache (see attachment).
How can that happen?

ASA 9.0.2.3182.
Service start line is:
-xtcpip -c2300m -ca 0 -m -o <file> -os1m -ti0 -tl0 <db file> -cw

Frank
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------------6wkeiJxRBIubIsV2xmBkUu--
0
Frank
10/24/2007 6:15:46 PM
sybase.sqlanywhere.general 32637 articles. 4 followers. Follow

9 Replies
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[PageSpeed] 38

The DiskRead=73,408 statistic shows that the engine did in fact read the 
table from disk. In this case, I/O hinting was used effectively. Those 
73,408 disk reads were mostly group reads of 64K each. The 
DiskReadTable=1.1604e6 shows that 1.16 million table pages were read by the 
group reads (working out to a 4K page size)

I/O hinting issues asynchronous read requests for 64K blocks, trying to keep 
ahead of the execution plan so that data is already loaded into the cache by 
the time the scan reads it. In this case, the I/O hinting worked perfectly, 
as seen by CacheReads = 3.4813e6 and CacheHits=3.4813e6. Every time the scan 
object tried to latch a page, it had already been read in by the I/O 
hinting. Note that individual pages can be latched multiple times to 
retrieve multiple rows off of the page, leading to CachReadTable > 
DiskReadTable (and the number of table pages in that table). This behaviour 
is reduced in version 10.0 and above. You will note that 
QueryRowsBuffereFetch =1.5129e6 is less than RowsReturned=2.6733e6 (and both 
may be lower than the number of rows in the table if there are predicates 
evaluated at the scan). In 10.0 and above, for this type of plan most of the 
rows would be buffer fetched and CacheRead should be lower (a savings of CPU 
time).

Since it looks like the IO hinting was very effective at overlapping IO wait 
time with CPU time, I'd suggest that you look at the CPU costs in your 
query, particularly at the scan node. Do you have predicates that are 
expensive to evaluate? Are there UDF or other complex functions? Are there 
complications in the schema that make the scan expensive?

The graphical plan with statistics adds CPU costs as it monitors the timing 
of fetching each row, and this effect can be exacerbated at the leaves of 
the plan as they see the most rows. Using fetchtst may give a more 
representative timing as it does not have the statistic monitors installed. 
Alternatively, you can select to only have the root-level statistics 
monitored when you fetch the graphical plan; that reduces the overhead to 
rows returned by the root. With the plan I am seeing, I would expect that 
fetchtst -ga would report that the CPU time is nearly equal to the total 
elapsed time.

The command line switch -zt and sa_performance_diagnostics() may be of use, 
the procedure will report the time that the server spent blocked (waiting 
for IO, a lock, or for a shared engine data structure) and the time spent 
active (actively using CPU). My feel from the portion of the plan that you 
sent is that the time active will be most of the execution time, and that 
improving the CPU cost of the query should be the first line of attack.

In 10.0 and above, parallel execution plans could be of use for this query 
if you have multiple logical processors availalble.

Another caution with caching behaviour is that the server can pre-warm the 
cache at server startup. Since you call sa_flush_cache() explicitly, you 
should avoid that complication but I mention it here for completeness.

Regards,
-- 
Ivan T. Bowman
SQLAnywhere Research and Development

Whitepapers, TechDocs, bug fixes are all available through the iAnywhere 
Developer Community at
http://www.ianywhere.com/developer


"Frank Ploessel" <fpl...@d_e.i_m_s_h_e_a_l_t_h.c_o_m> wrote in message 
news:op.t0prohdij0bybf@bonw00164.internal.imsglobal.com...
> Hi,
>
> While checking a performance issue, I came across something really 
> strange:
> From Sybase Central, I stopped and restarted a database on an engine which
> kept running.
> Then I opened ISQL which was the only connection to the newly started
> database,
> ran "call sa_flush_cache()",
> changed the plan settings to graphical with statistics,
> entered the select statement and hit Get Plan without having run the
> statement before.
>
> But the plan tells me it found most of the data in cache (see attachment).
> How can that happen?
>
> ASA 9.0.2.3182.
> Service start line is:
> -xtcpip -c2300m -ca 0 -m -o <file> -os1m -ti0 -tl0 <db file> -cw
>
> Frank 


0
Ivan
10/24/2007 9:24:23 PM
Ivan,

Thank you for this insightful and detailed answer.

My original post was just as I did not understand the plan details about=
  =

cachings, and you answered that in detaiil.

Actually, this query is the fast version taking one minute, and the slow=
  =

one is the exact same query but on a table half the size, but taking ten=
  =

minutes. I keep searching for reasons of the bad performance.


Frank

On Wed, 24 Oct 2007 23:24:23 +0200, Ivan T. Bowman  =

<ibowman@ianywhere.NOSPAM.com> wrote:

> The DiskRead=3D73,408 statistic shows that the engine did in fact read=
 the
> table from disk. In this case, I/O hinting was used effectively. Those=

> 73,408 disk reads were mostly group reads of 64K each. The
> DiskReadTable=3D1.1604e6 shows that 1.16 million table pages were read=
 by  =

> the
> group reads (working out to a 4K page size)
>
> I/O hinting issues asynchronous read requests for 64K blocks, trying t=
o  =

> keep
> ahead of the execution plan so that data is already loaded into the  =

> cache by
> the time the scan reads it. In this case, the I/O hinting worked  =

> perfectly,
> as seen by CacheReads =3D 3.4813e6 and CacheHits=3D3.4813e6. Every tim=
e the  =

> scan
> object tried to latch a page, it had already been read in by the I/O
> hinting. Note that individual pages can be latched multiple times to
> retrieve multiple rows off of the page, leading to CachReadTable >
> DiskReadTable (and the number of table pages in that table). This  =

> behaviour
> is reduced in version 10.0 and above. You will note that
> QueryRowsBuffereFetch =3D1.5129e6 is less than RowsReturned=3D2.6733e6=
 (and  =

> both
> may be lower than the number of rows in the table if there are predica=
tes
> evaluated at the scan). In 10.0 and above, for this type of plan most =
of  =

> the
> rows would be buffer fetched and CacheRead should be lower (a savings =
of  =

> CPU
> time).
>
> Since it looks like the IO hinting was very effective at overlapping I=
O  =

> wait
> time with CPU time, I'd suggest that you look at the CPU costs in your=

> query, particularly at the scan node. Do you have predicates that are
> expensive to evaluate? Are there UDF or other complex functions? Are  =

> there
> complications in the schema that make the scan expensive?
>
> The graphical plan with statistics adds CPU costs as it monitors the  =

> timing
> of fetching each row, and this effect can be exacerbated at the leaves=
 of
> the plan as they see the most rows. Using fetchtst may give a more
> representative timing as it does not have the statistic monitors  =

> installed.
> Alternatively, you can select to only have the root-level statistics
> monitored when you fetch the graphical plan; that reduces the overhead=
 to
> rows returned by the root. With the plan I am seeing, I would expect t=
hat
> fetchtst -ga would report that the CPU time is nearly equal to the tot=
al
> elapsed time.
>
> The command line switch -zt and sa_performance_diagnostics() may be of=
  =

> use,
> the procedure will report the time that the server spent blocked (wait=
ing
> for IO, a lock, or for a shared engine data structure) and the time sp=
ent
> active (actively using CPU). My feel from the portion of the plan that=
  =

> you
> sent is that the time active will be most of the execution time, and t=
hat
> improving the CPU cost of the query should be the first line of attack=
..
>
> In 10.0 and above, parallel execution plans could be of use for this  =

> query
> if you have multiple logical processors availalble.
>
> Another caution with caching behaviour is that the server can pre-warm=
  =

> the
> cache at server startup. Since you call sa_flush_cache() explicitly, y=
ou
> should avoid that complication but I mention it here for completeness.=

>
> Regards,

0
Frank
10/25/2007 12:46:13 PM
As a side note, you can save a plan to a file directly from DBISQL. Here 
is my 'canned' request for plans that includes how to save the file...

	To generate a Graphical Plan with Statistics

	1. From DBISQL, go to Tools | Options and set the "Plan" option
	   to Graphical Plan with Statistics
	2. Press Shift-F5 to get the plan
	3. For ASA 8 and ASA9, Select File | Save As...
            and Set the file type to XML
	4. For SA 10, Select File | Save Plan...
	5. provide a file name
	6. Click Ok

	You can view a saved graphical plan by

	1. For ASA 8 and ASA9, from DBISQL, select File | Open...
            and Set the file type to XML
	2. For SA 10, select File | Open Plan...
	3. Select the Graphical plan file



Frank Ploessel wrote:
> Hi,
> 
> While checking a performance issue, I came across something really strange:
>  From Sybase Central, I stopped and restarted a database on an engine 
> which kept running.
> Then I opened ISQL which was the only connection to the newly started 
> database,
> ran "call sa_flush_cache()",
> changed the plan settings to graphical with statistics,
> entered the select statement and hit Get Plan without having run the 
> statement before.
> 
> But the plan tells me it found most of the data in cache (see attachment).
> How can that happen?
> 
> ASA 9.0.2.3182.
> Service start line is:
> -xtcpip -c2300m -ca 0 -m -o <file> -os1m -ti0 -tl0 <db file> -cw
> 
> Frank
0
Chris
10/25/2007 1:16:29 PM
------------fL0AYWpurqRzCTPYGriiJB
Content-Type: text/plain; format=flowed; delsp=yes; charset=iso-8859-15
Content-Transfer-Encoding: Quoted-Printable

Ivan,

Let me summarize my general performance issue:
I have the exact same query in the same database, run on table Big (450 =
 =

columns, 2.7 million rows), it took 40-60 columns. Run on table Small (4=
00  =

columns, a subset of the columns of table Big in the same physical order=
,  =

and 1.4 million rows), it took 9-12 minutes. As table Small only has hal=
f  =

the size (545 thousand vs. 1160 thousand pages), this was not as expecte=
d.

The query is:

SELECT IntegerCol, coalesce(sum(numericCol * 1.), 0)
   FROM Big
  GROUP BY IntegerCol
HAVING coalesce(sum(numericCol * 1.), 0) <> 0

having a result set of 16 rows after HAVING eliminates one row.
ASA uses a hash join, so the main driver of runtime is the full table sc=
an  =

of the millions of records from the base table (Big or Small), which  =

cannot be avoided.

1. I found the db file had 13000 fragments. Defragmentig it down to 8  =

fragments did not help much.
2. I found that table Small was fragmented (1.28 segments per row), whil=
e  =

Big was not. Defragmenting it (actually creating a table with the same  =

structure and running insert select, to keep the original available)  =

brought the runtime down to about 90 to 120 seconds, better, but still  =

much longer than on table Big.

Going through the differences in the plans now, what I found was that in=
  =

the reading from the base table - as expected - less rows and less pages=
  =

were read from the new table Small than from Big. But the number of page=
s  =

read is the same as the number of reads for table Small, while for table=
  =

Big, Disk Table reads / DIsk reads was 15.8, so as I learnt from your po=
st  =

mainly 64K reads were issued.

I assume ASA did not issue 64K read requests at all but 4K read requests=
  =

for table Small. And probably the reason is that the table is spread too=
  =

much across the database file and not saved continuously. And eventually=
,  =

the higher number of I/O requests made the query on table Small slower.
So this means we should take more care of fragmentation in future,  =

preallocating database space before filling big tables to avoid table  =

spreading in the db file, and try to avoid table fragmentation as far as=
  =

feasable, maybe experimenting with pctfree settings.

Do you think my interpretation sounds reasonable?

Is there any possibility to find out if a table is saved in the DB file =
 =

continously or not?

Frank


On Thu, 25 Oct 2007 14:46:13 +0200, Frank Ploessel  =

<fpl...@d_e.i_m_s_h_e_a_l_t_h.c_o_m> wrote:

> Ivan,
>
> Thank you for this insightful and detailed answer.
>
> My original post was just as I did not understand the plan details abo=
ut  =

> cachings, and you answered that in detaiil.
>
> Actually, this query is the fast version taking one minute, and the sl=
ow  =

> one is the exact same query but on a table half the size, but taking t=
en  =

> minutes. I keep searching for reasons of the bad performance.
>
>
> Frank
>
> On Wed, 24 Oct 2007 23:24:23 +0200, Ivan T. Bowman  =

> <ibowman@ianywhere.NOSPAM.com> wrote:
>
>> The DiskRead=3D73,408 statistic shows that the engine did in fact rea=
d the
>> table from disk. In this case, I/O hinting was used effectively. Thos=
e
>> 73,408 disk reads were mostly group reads of 64K each. The
>> DiskReadTable=3D1.1604e6 shows that 1.16 million table pages were rea=
d by  =

>> the
>> group reads (working out to a 4K page size)
>>
>> I/O hinting issues asynchronous read requests for 64K blocks, trying =
to  =

>> keep
>> ahead of the execution plan so that data is already loaded into the  =

>> cache by
>> the time the scan reads it. In this case, the I/O hinting worked  =

>> perfectly,
>> as seen by CacheReads =3D 3.4813e6 and CacheHits=3D3.4813e6. Every ti=
me the  =

>> scan
>> object tried to latch a page, it had already been read in by the I/O
>> hinting. Note that individual pages can be latched multiple times to
>> retrieve multiple rows off of the page, leading to CachReadTable >
>> DiskReadTable (and the number of table pages in that table). This  =

>> behaviour
>> is reduced in version 10.0 and above. You will note that
>> QueryRowsBuffereFetch =3D1.5129e6 is less than RowsReturned=3D2.6733e=
6 (and  =

>> both
>> may be lower than the number of rows in the table if there are  =

>> predicates
>> evaluated at the scan). In 10.0 and above, for this type of plan most=
  =

>> of the
>> rows would be buffer fetched and CacheRead should be lower (a savings=
  =

>> of CPU
>> time).
>>
>> Since it looks like the IO hinting was very effective at overlapping =
IO  =

>> wait
>> time with CPU time, I'd suggest that you look at the CPU costs in you=
r
>> query, particularly at the scan node. Do you have predicates that are=

>> expensive to evaluate? Are there UDF or other complex functions? Are =
 =

>> there
>> complications in the schema that make the scan expensive?
>>
>> The graphical plan with statistics adds CPU costs as it monitors the =
 =

>> timing
>> of fetching each row, and this effect can be exacerbated at the leave=
s  =

>> of
>> the plan as they see the most rows. Using fetchtst may give a more
>> representative timing as it does not have the statistic monitors  =

>> installed.
>> Alternatively, you can select to only have the root-level statistics
>> monitored when you fetch the graphical plan; that reduces the overhea=
d  =

>> to
>> rows returned by the root. With the plan I am seeing, I would expect =
 =

>> that
>> fetchtst -ga would report that the CPU time is nearly equal to the to=
tal
>> elapsed time.
>>
>> The command line switch -zt and sa_performance_diagnostics() may be o=
f  =

>> use,
>> the procedure will report the time that the server spent blocked  =

>> (waiting
>> for IO, a lock, or for a shared engine data structure) and the time  =

>> spent
>> active (actively using CPU). My feel from the portion of the plan tha=
t  =

>> you
>> sent is that the time active will be most of the execution time, and =
 =

>> that
>> improving the CPU cost of the query should be the first line of attac=
k.
>>
>> In 10.0 and above, parallel execution plans could be of use for this =
 =

>> query
>> if you have multiple logical processors availalble.
>>
>> Another caution with caching behaviour is that the server can pre-war=
m  =

>> the
>> cache at server startup. Since you call sa_flush_cache() explicitly, =
you
>> should avoid that complication but I mention it here for completeness=
..
>>
>> Regards,
>


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------------fL0AYWpurqRzCTPYGriiJB--
0
Frank
10/25/2007 5:32:00 PM
Chris,

I know. But as these files contain some currently confidential information  
(prospect names in directory names ...), I prefered to not post them  
completely.

Frank

On Thu, 25 Oct 2007 15:16:29 +0200, Chris Keating (Sybase iAnywhere)  
<keating_spam_free@ianywhere.com> wrote:

> As a side note, you can save a plan to a file directly from DBISQL. Here  
> is my 'canned' request for plans that includes how to save the file...
>
> 	To generate a Graphical Plan with Statistics
>
> 	1. From DBISQL, go to Tools | Options and set the "Plan" option
> 	   to Graphical Plan with Statistics
> 	2. Press Shift-F5 to get the plan
> 	3. For ASA 8 and ASA9, Select File | Save As...
>             and Set the file type to XML
> 	4. For SA 10, Select File | Save Plan...
> 	5. provide a file name
> 	6. Click Ok
>
> 	You can view a saved graphical plan by
>
> 	1. For ASA 8 and ASA9, from DBISQL, select File | Open...
>             and Set the file type to XML
> 	2. For SA 10, select File | Open Plan...
> 	3. Select the Graphical plan file
>
>
>
> Frank Ploessel wrote:
>> Hi,
>>  While checking a performance issue, I came across something really  
>> strange:
>>  From Sybase Central, I stopped and restarted a database on an engine  
>> which kept running.
>> Then I opened ISQL which was the only connection to the newly started  
>> database,
>> ran "call sa_flush_cache()",
>> changed the plan settings to graphical with statistics,
>> entered the select statement and hit Get Plan without having run the  
>> statement before.
>>  But the plan tells me it found most of the data in cache (see  
>> attachment).
>> How can that happen?
>>  ASA 9.0.2.3182.
>> Service start line is:
>> -xtcpip -c2300m -ca 0 -m -o <file> -os1m -ti0 -tl0 <db file> -cw
>>  Frank

0
Frank
10/25/2007 5:35:47 PM
fair enough.. didn't know there was confidential info.


Frank Ploessel wrote:
> Chris,
> 
> I know. But as these files contain some currently confidential 
> information (prospect names in directory names ...), I prefered to not 
> post them completely.
> 
> Frank
> 
> On Thu, 25 Oct 2007 15:16:29 +0200, Chris Keating (Sybase iAnywhere) 
> <keating_spam_free@ianywhere.com> wrote:
> 
>> As a side note, you can save a plan to a file directly from DBISQL. 
>> Here is my 'canned' request for plans that includes how to save the 
>> file...
>>
>>     To generate a Graphical Plan with Statistics
>>
>>     1. From DBISQL, go to Tools | Options and set the "Plan" option
>>        to Graphical Plan with Statistics
>>     2. Press Shift-F5 to get the plan
>>     3. For ASA 8 and ASA9, Select File | Save As...
>>             and Set the file type to XML
>>     4. For SA 10, Select File | Save Plan...
>>     5. provide a file name
>>     6. Click Ok
>>
>>     You can view a saved graphical plan by
>>
>>     1. For ASA 8 and ASA9, from DBISQL, select File | Open...
>>             and Set the file type to XML
>>     2. For SA 10, select File | Open Plan...
>>     3. Select the Graphical plan file
>>
>>
>>
>> Frank Ploessel wrote:
>>> Hi,
>>>  While checking a performance issue, I came across something really 
>>> strange:
>>>  From Sybase Central, I stopped and restarted a database on an engine 
>>> which kept running.
>>> Then I opened ISQL which was the only connection to the newly started 
>>> database,
>>> ran "call sa_flush_cache()",
>>> changed the plan settings to graphical with statistics,
>>> entered the select statement and hit Get Plan without having run the 
>>> statement before.
>>>  But the plan tells me it found most of the data in cache (see 
>>> attachment).
>>> How can that happen?
>>>  ASA 9.0.2.3182.
>>> Service start line is:
>>> -xtcpip -c2300m -ca 0 -m -o <file> -os1m -ti0 -tl0 <db file> -cw
>>>  Frank
> 
0
Chris
10/25/2007 7:32:28 PM
From looking at the plan fragment you have posted, I agree that the scan of 
the small table is not doing 64K group reads. Instead, each table page is 
being read individually. If you use a file system monitor, you will see that 
the read size is smaller than the Big case and that the number of reads is 
higher.

There are a few reasons why the 64K reads might not be used. One of these 
reasons can come up if you have rows that are continued across pages; 64K 
reads only operate on the head of rows, not on continuations. The statistic 
of 1.28 segments per row indicated that each row was an average of 1.28 
segments. If the columns on the continuation segment were needed by the 
query, then the continuation page would need to be read as it would not have 
been read by an asynchronous hint. The problem of continued rows does not 
match the statistcs that you see, though.

Other than continued rows, you mention the possibility that the table could 
be spread out. This is certainly a reason why 64K reads would not be used, 
as the group reads must start on a 64K boundary. It is possible that the 
pages are allocated in such a way that group reads can not be used (although 
the server does try to allocate table pages in clusters). Due to the attempt 
to allocate pages in clusters, I would not recommend being inordinately 
careful about table fragmentation within the dbspace. Of course, avoiding 
continued rows through appropriate PCTFREE settings is a really good idea.

From your statistics, though, it looks like _no_ 64K reads at all were 
issued in the Small case (since DiskRead > DiskReadTable). I  am not sure 
that the non-contiguous pages idea explains the stats you are seeing; I 
would have expected some blocks of contiguous pages even in a very 
non-contiguos table. If you are investigating this further, I would suggest 
creating a new dbspace then creating a copy of Small in the new dbspace. The 
pages should all be contiguous in that space, so performance ought to be as 
good as Big unless there is another factor at work besides contiguity.

There are some other reasons why 64K reads might not be used. One is related 
to database file version, but since both Big and Small tables are in the 
same database, that should not apply. There may be some reason that I am not 
thinking of that Small would not use the group reads. I do not have a good 
answer based on the data available.

I don't know of a good way in 9.0 to identify how table pages are allocated 
throughout the database. One mechanism is to use a filemonitor to observe 
the disk reads performed for a sequential scan, then correlate those back to 
an allocation pattern; that is a bit tedious. In 10.0 and above, the 
allocated pages of a table are stored in a long varbit column in the catalog 
and that column can be manipulated from SQL.

I am interested in your performance case as a possible regression test for 
us (wide tables of 400+ columns can have unique performance problems). I 
don't know if there is a way for you to create a non-sensitive reproducible 
case for us to look at, but if you could I would like to investigate a bit 
further and possibly create regression performance tests based on your 
setup.

Regards,
-- 
Ivan T. Bowman
SQLAnywhere Research and Development


"Frank Ploessel" <fpl...@d_e.i_m_s_h_e_a_l_t_h.c_o_m> wrote in message 
news:op.t0rkbjmlj0bybf@bonw00164.internal.imsglobal.com...
Ivan,

Let me summarize my general performance issue:
I have the exact same query in the same database, run on table Big (450
columns, 2.7 million rows), it took 40-60 columns. Run on table Small (400
columns, a subset of the columns of table Big in the same physical order,
and 1.4 million rows), it took 9-12 minutes. As table Small only has half
the size (545 thousand vs. 1160 thousand pages), this was not as expected.

The query is:

SELECT IntegerCol, coalesce(sum(numericCol * 1.), 0)
   FROM Big
  GROUP BY IntegerCol
HAVING coalesce(sum(numericCol * 1.), 0) <> 0

having a result set of 16 rows after HAVING eliminates one row.
ASA uses a hash join, so the main driver of runtime is the full table scan
of the millions of records from the base table (Big or Small), which
cannot be avoided.

1. I found the db file had 13000 fragments. Defragmentig it down to 8
fragments did not help much.
2. I found that table Small was fragmented (1.28 segments per row), while
Big was not. Defragmenting it (actually creating a table with the same
structure and running insert select, to keep the original available)
brought the runtime down to about 90 to 120 seconds, better, but still
much longer than on table Big.

Going through the differences in the plans now, what I found was that in
the reading from the base table - as expected - less rows and less pages
were read from the new table Small than from Big. But the number of pages
read is the same as the number of reads for table Small, while for table
Big, Disk Table reads / DIsk reads was 15.8, so as I learnt from your post
mainly 64K reads were issued.

I assume ASA did not issue 64K read requests at all but 4K read requests
for table Small. And probably the reason is that the table is spread too
much across the database file and not saved continuously. And eventually,
the higher number of I/O requests made the query on table Small slower.
So this means we should take more care of fragmentation in future,
preallocating database space before filling big tables to avoid table
spreading in the db file, and try to avoid table fragmentation as far as
feasable, maybe experimenting with pctfree settings.

Do you think my interpretation sounds reasonable?

Is there any possibility to find out if a table is saved in the DB file
continously or not?

Frank


On Thu, 25 Oct 2007 14:46:13 +0200, Frank Ploessel
<fpl...@d_e.i_m_s_h_e_a_l_t_h.c_o_m> wrote:

> Ivan,
>
> Thank you for this insightful and detailed answer.
>
> My original post was just as I did not understand the plan details about
> cachings, and you answered that in detaiil.
>
> Actually, this query is the fast version taking one minute, and the slow
> one is the exact same query but on a table half the size, but taking ten
> minutes. I keep searching for reasons of the bad performance.
>
>
> Frank
>
> On Wed, 24 Oct 2007 23:24:23 +0200, Ivan T. Bowman
> <ibowman@ianywhere.NOSPAM.com> wrote:
>
>> The DiskRead=73,408 statistic shows that the engine did in fact read the
>> table from disk. In this case, I/O hinting was used effectively. Those
>> 73,408 disk reads were mostly group reads of 64K each. The
>> DiskReadTable=1.1604e6 shows that 1.16 million table pages were read by
>> the
>> group reads (working out to a 4K page size)
>>
>> I/O hinting issues asynchronous read requests for 64K blocks, trying to
>> keep
>> ahead of the execution plan so that data is already loaded into the
>> cache by
>> the time the scan reads it. In this case, the I/O hinting worked
>> perfectly,
>> as seen by CacheReads = 3.4813e6 and CacheHits=3.4813e6. Every time the
>> scan
>> object tried to latch a page, it had already been read in by the I/O
>> hinting. Note that individual pages can be latched multiple times to
>> retrieve multiple rows off of the page, leading to CachReadTable >
>> DiskReadTable (and the number of table pages in that table). This
>> behaviour
>> is reduced in version 10.0 and above. You will note that
>> QueryRowsBuffereFetch =1.5129e6 is less than RowsReturned=2.6733e6 (and
>> both
>> may be lower than the number of rows in the table if there are
>> predicates
>> evaluated at the scan). In 10.0 and above, for this type of plan most
>> of the
>> rows would be buffer fetched and CacheRead should be lower (a savings
>> of CPU
>> time).
>>
>> Since it looks like the IO hinting was very effective at overlapping IO
>> wait
>> time with CPU time, I'd suggest that you look at the CPU costs in your
>> query, particularly at the scan node. Do you have predicates that are
>> expensive to evaluate? Are there UDF or other complex functions? Are
>> there
>> complications in the schema that make the scan expensive?
>>
>> The graphical plan with statistics adds CPU costs as it monitors the
>> timing
>> of fetching each row, and this effect can be exacerbated at the leaves
>> of
>> the plan as they see the most rows. Using fetchtst may give a more
>> representative timing as it does not have the statistic monitors
>> installed.
>> Alternatively, you can select to only have the root-level statistics
>> monitored when you fetch the graphical plan; that reduces the overhead
>> to
>> rows returned by the root. With the plan I am seeing, I would expect
>> that
>> fetchtst -ga would report that the CPU time is nearly equal to the total
>> elapsed time.
>>
>> The command line switch -zt and sa_performance_diagnostics() may be of
>> use,
>> the procedure will report the time that the server spent blocked
>> (waiting
>> for IO, a lock, or for a shared engine data structure) and the time
>> spent
>> active (actively using CPU). My feel from the portion of the plan that
>> you
>> sent is that the time active will be most of the execution time, and
>> that
>> improving the CPU cost of the query should be the first line of attack.
>>
>> In 10.0 and above, parallel execution plans could be of use for this
>> query
>> if you have multiple logical processors availalble.
>>
>> Another caution with caching behaviour is that the server can pre-warm
>> the
>> cache at server startup. Since you call sa_flush_cache() explicitly, you
>> should avoid that complication but I mention it here for completeness.
>>
>> Regards,
>



0
Ivan
10/25/2007 10:36:27 PM
After further discussion with a colleague, it doesn't seem likely that 
non-contiguous allocation of your Small table pages would lead the server to 
not use the 64K group reads. You would need to have each 64K block 
containing only 1 table page, and that is very unlikely (c.f. the birthday 
paradox). This layout particularly should not occur due to the server's 
attempt to grow a table in 64K blocks.

There remain a few other reasons why group reads would not be used. One 
possibility is that a table bitmap has not yet been created for the table. 
The first sequential scan will create the bitmap if the table is 
sufficiently large, so it may be that the first execution of the query on 
Small would be slow (with no page bitmap) but then later ones should be 
faster.

In order to investigate this issue further it may be most expedient to open 
a case with technical support and give us a copy of the database or other 
information to reproduce the problem.

Regards,
-- 
Ivan T. Bowman
SQLAnywhere Research and Development

"Ivan T. Bowman" <ibowman@ianywhere.NOSPAM.com> wrote in message 
news:47211a6b$2@forums-1-dub...
> From looking at the plan fragment you have posted, I agree that the scan 
> of the small table is not doing 64K group reads. Instead, each table page 
> is being read individually. If you use a file system monitor, you will see 
> that the read size is smaller than the Big case and that the number of 
> reads is higher.
>
> There are a few reasons why the 64K reads might not be used. One of these 
> reasons can come up if you have rows that are continued across pages; 64K 
> reads only operate on the head of rows, not on continuations. The 
> statistic of 1.28 segments per row indicated that each row was an average 
> of 1.28 segments. If the columns on the continuation segment were needed 
> by the query, then the continuation page would need to be read as it would 
> not have been read by an asynchronous hint. The problem of continued rows 
> does not match the statistcs that you see, though.
>
> Other than continued rows, you mention the possibility that the table 
> could be spread out. This is certainly a reason why 64K reads would not be 
> used, as the group reads must start on a 64K boundary. It is possible that 
> the pages are allocated in such a way that group reads can not be used 
> (although the server does try to allocate table pages in clusters). Due to 
> the attempt to allocate pages in clusters, I would not recommend being 
> inordinately careful about table fragmentation within the dbspace. Of 
> course, avoiding continued rows through appropriate PCTFREE settings is a 
> really good idea.
>
> From your statistics, though, it looks like _no_ 64K reads at all were 
> issued in the Small case (since DiskRead > DiskReadTable). I  am not sure 
> that the non-contiguous pages idea explains the stats you are seeing; I 
> would have expected some blocks of contiguous pages even in a very 
> non-contiguos table. If you are investigating this further, I would 
> suggest creating a new dbspace then creating a copy of Small in the new 
> dbspace. The pages should all be contiguous in that space, so performance 
> ought to be as good as Big unless there is another factor at work besides 
> contiguity.
>
> There are some other reasons why 64K reads might not be used. One is 
> related to database file version, but since both Big and Small tables are 
> in the same database, that should not apply. There may be some reason that 
> I am not thinking of that Small would not use the group reads. I do not 
> have a good answer based on the data available.
>
> I don't know of a good way in 9.0 to identify how table pages are 
> allocated throughout the database. One mechanism is to use a filemonitor 
> to observe the disk reads performed for a sequential scan, then correlate 
> those back to an allocation pattern; that is a bit tedious. In 10.0 and 
> above, the allocated pages of a table are stored in a long varbit column 
> in the catalog and that column can be manipulated from SQL.
>
> I am interested in your performance case as a possible regression test for 
> us (wide tables of 400+ columns can have unique performance problems). I 
> don't know if there is a way for you to create a non-sensitive 
> reproducible case for us to look at, but if you could I would like to 
> investigate a bit further and possibly create regression performance tests 
> based on your setup.
>
> Regards,
> -- 
> Ivan T. Bowman
> SQLAnywhere Research and Development
>
>
> "Frank Ploessel" <fpl...@d_e.i_m_s_h_e_a_l_t_h.c_o_m> wrote in message 
> news:op.t0rkbjmlj0bybf@bonw00164.internal.imsglobal.com...
> Ivan,
>
> Let me summarize my general performance issue:
> I have the exact same query in the same database, run on table Big (450
> columns, 2.7 million rows), it took 40-60 columns. Run on table Small (400
> columns, a subset of the columns of table Big in the same physical order,
> and 1.4 million rows), it took 9-12 minutes. As table Small only has half
> the size (545 thousand vs. 1160 thousand pages), this was not as expected.
>
> The query is:
>
> SELECT IntegerCol, coalesce(sum(numericCol * 1.), 0)
>   FROM Big
>  GROUP BY IntegerCol
> HAVING coalesce(sum(numericCol * 1.), 0) <> 0
>
> having a result set of 16 rows after HAVING eliminates one row.
> ASA uses a hash join, so the main driver of runtime is the full table scan
> of the millions of records from the base table (Big or Small), which
> cannot be avoided.
>
> 1. I found the db file had 13000 fragments. Defragmentig it down to 8
> fragments did not help much.
> 2. I found that table Small was fragmented (1.28 segments per row), while
> Big was not. Defragmenting it (actually creating a table with the same
> structure and running insert select, to keep the original available)
> brought the runtime down to about 90 to 120 seconds, better, but still
> much longer than on table Big.
>
> Going through the differences in the plans now, what I found was that in
> the reading from the base table - as expected - less rows and less pages
> were read from the new table Small than from Big. But the number of pages
> read is the same as the number of reads for table Small, while for table
> Big, Disk Table reads / DIsk reads was 15.8, so as I learnt from your post
> mainly 64K reads were issued.
>
> I assume ASA did not issue 64K read requests at all but 4K read requests
> for table Small. And probably the reason is that the table is spread too
> much across the database file and not saved continuously. And eventually,
> the higher number of I/O requests made the query on table Small slower.
> So this means we should take more care of fragmentation in future,
> preallocating database space before filling big tables to avoid table
> spreading in the db file, and try to avoid table fragmentation as far as
> feasable, maybe experimenting with pctfree settings.
>
> Do you think my interpretation sounds reasonable?
>
> Is there any possibility to find out if a table is saved in the DB file
> continously or not?
>
> Frank
>
>
> On Thu, 25 Oct 2007 14:46:13 +0200, Frank Ploessel
> <fpl...@d_e.i_m_s_h_e_a_l_t_h.c_o_m> wrote:
>
>> Ivan,
>>
>> Thank you for this insightful and detailed answer.
>>
>> My original post was just as I did not understand the plan details about
>> cachings, and you answered that in detaiil.
>>
>> Actually, this query is the fast version taking one minute, and the slow
>> one is the exact same query but on a table half the size, but taking ten
>> minutes. I keep searching for reasons of the bad performance.
>>
>>
>> Frank
>>
>> On Wed, 24 Oct 2007 23:24:23 +0200, Ivan T. Bowman
>> <ibowman@ianywhere.NOSPAM.com> wrote:
>>
>>> The DiskRead=73,408 statistic shows that the engine did in fact read the
>>> table from disk. In this case, I/O hinting was used effectively. Those
>>> 73,408 disk reads were mostly group reads of 64K each. The
>>> DiskReadTable=1.1604e6 shows that 1.16 million table pages were read by
>>> the
>>> group reads (working out to a 4K page size)
>>>
>>> I/O hinting issues asynchronous read requests for 64K blocks, trying to
>>> keep
>>> ahead of the execution plan so that data is already loaded into the
>>> cache by
>>> the time the scan reads it. In this case, the I/O hinting worked
>>> perfectly,
>>> as seen by CacheReads = 3.4813e6 and CacheHits=3.4813e6. Every time the
>>> scan
>>> object tried to latch a page, it had already been read in by the I/O
>>> hinting. Note that individual pages can be latched multiple times to
>>> retrieve multiple rows off of the page, leading to CachReadTable >
>>> DiskReadTable (and the number of table pages in that table). This
>>> behaviour
>>> is reduced in version 10.0 and above. You will note that
>>> QueryRowsBuffereFetch =1.5129e6 is less than RowsReturned=2.6733e6 (and
>>> both
>>> may be lower than the number of rows in the table if there are
>>> predicates
>>> evaluated at the scan). In 10.0 and above, for this type of plan most
>>> of the
>>> rows would be buffer fetched and CacheRead should be lower (a savings
>>> of CPU
>>> time).
>>>
>>> Since it looks like the IO hinting was very effective at overlapping IO
>>> wait
>>> time with CPU time, I'd suggest that you look at the CPU costs in your
>>> query, particularly at the scan node. Do you have predicates that are
>>> expensive to evaluate? Are there UDF or other complex functions? Are
>>> there
>>> complications in the schema that make the scan expensive?
>>>
>>> The graphical plan with statistics adds CPU costs as it monitors the
>>> timing
>>> of fetching each row, and this effect can be exacerbated at the leaves
>>> of
>>> the plan as they see the most rows. Using fetchtst may give a more
>>> representative timing as it does not have the statistic monitors
>>> installed.
>>> Alternatively, you can select to only have the root-level statistics
>>> monitored when you fetch the graphical plan; that reduces the overhead
>>> to
>>> rows returned by the root. With the plan I am seeing, I would expect
>>> that
>>> fetchtst -ga would report that the CPU time is nearly equal to the total
>>> elapsed time.
>>>
>>> The command line switch -zt and sa_performance_diagnostics() may be of
>>> use,
>>> the procedure will report the time that the server spent blocked
>>> (waiting
>>> for IO, a lock, or for a shared engine data structure) and the time
>>> spent
>>> active (actively using CPU). My feel from the portion of the plan that
>>> you
>>> sent is that the time active will be most of the execution time, and
>>> that
>>> improving the CPU cost of the query should be the first line of attack.
>>>
>>> In 10.0 and above, parallel execution plans could be of use for this
>>> query
>>> if you have multiple logical processors availalble.
>>>
>>> Another caution with caching behaviour is that the server can pre-warm
>>> the
>>> cache at server startup. Since you call sa_flush_cache() explicitly, you
>>> should avoid that complication but I mention it here for completeness.
>>>
>>> Regards,
>>
>
>
> 


0
Ivan
10/26/2007 3:07:25 PM
Ivan,

Today, I created a copy of table Small in a new table space, and had a  
look at the query with FileMon.
I had the impression that getting a plan with statistic sometimes seems to  
have caused the reads to drop to 4k chunks instead of 64k (or 60k or 32 k,  
which I also found from time to time). So maybe this was the reason for  
the strange results.

I also realized that FileMon initially used as much CPU as the db engine  
(both around 20 percent), but from some number of entries shown, around  
100000, FileMon used 99% of CPU in task manager, probably to update its  
GUI. So it helps determine the read size but can create some overhead and  
runtimes may get wrong.

Results of runs from ISQL without statistics, timing without FileMon, and  
after defragmenting the new dbspace on file level (query runtime according  
to ISQL message pane and number of read actions shown in FileMon):
Small in new dbspace:  35 sec, 34000 reads
Small in orig dbspace: 30 sec, 38000 reads
Big:                   54 sec, 74000 reads

So within the general deviations of measuring (like more time for less  
reads for the two variants of Small), these results seem reasonable, and  
the statement runs faster on table Small than on Big - as expected!

Summary of what I learnt:
* Many details about the internal ASA query processing, and what to check  
in case of problems.
* Taking more care if the measurement itself does not influence execution  
too much, always cross-check results with non-instrumented runs (no  
FileMon, no statistics, ...).
* Taking fragmentation serious (at least on those two levels where this  
can be influenced: table fragmentation, and db file fragmentation, maybe  
on the level of table page within file in ASA10).

Thank you for your help.

Frank




On Fri, 26 Oct 2007 17:07:25 +0200, Ivan T. Bowman  
<ibowman@ianywhere.NOSPAM.com> wrote:

> After further discussion with a colleague, it doesn't seem likely that
> non-contiguous allocation of your Small table pages would lead the  
> server to
> not use the 64K group reads. You would need to have each 64K block
> containing only 1 table page, and that is very unlikely (c.f. the  
> birthday
> paradox). This layout particularly should not occur due to the server's
> attempt to grow a table in 64K blocks.
>
> There remain a few other reasons why group reads would not be used. One
> possibility is that a table bitmap has not yet been created for the  
> table.
> The first sequential scan will create the bitmap if the table is
> sufficiently large, so it may be that the first execution of the query on
> Small would be slow (with no page bitmap) but then later ones should be
> faster.
>
> In order to investigate this issue further it may be most expedient to  
> open
> a case with technical support and give us a copy of the database or other
> information to reproduce the problem.
>
> Regards,

0
Frank
10/26/2007 6:10:28 PM
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