Re: Query taking long time

[Evgeny Shishkin <itparanoia@xxxxxxxxx>]

Hello,

new server with more ram will definitely help to keep your working set in memory.

But if you want your queries be fast on cold (on disk) data, then you need more/faster disks.

And work_mem = 1000MB is too much, better set to 32MB so you don’t get OOM Killer.

And may be slightly lower shared_buffers. 

On 11 Mar 2014, at 18:56, acanada <acanada@xxxxxxx> wrote:

Hello,

I cannot do explain (analyze, buffers) since I am on 8.3 postgres version.

I am migrating to the new server and upgrading it.

Once it is ready again I will post the explain query here.

The new disk is SATA disk with 5TB, raid 0 or 1...

lspci | grep -i raid

00:1f.2 RAID bus controller: Intel Corporation C600/X79 series chipset SATA RAID Controller (rev 05)

All database is 200GB and the table entity2document2 is 

x=> select pg_size_pretty(pg_relation_size('entity2document2'));

 pg_size_pretty 

----------------

 11 GB

(1 row)

x=> select pg_size_pretty(pg_total_relation_size('entity2document2'));

 pg_size_pretty 

----------------

 29 GB

(1 row)

The index of the name column:

x=> select pg_size_pretty(pg_relation_size('entity2document2_name'));

 pg_size_pretty 

----------------

 2550 MB

(1 row)

I am tunning the new server with this parameters...

shared_buffers = 15000MB

work_mem = 1000MB

maintenance_work_mem = 2000MB

Any other parameter that should be modified?

Thank you for your help!

Andrés

El Mar 10, 2014, a las 9:22 PM, desmodemone escribió:

Hello Andres,
                       with enable_bitmapscan=off;   could you do :

explain ( analyze , buffers ) select * from entity2document2  where name='ranitidine' ;

I think it's interesting to understand how much it's clustered the table  entity2document2.

infact the query extract 13512 rows in 79945.362 ms around 4 ms for row, and I suspect the table is not well clustered on that column, so every time the

process is asking for a different page of the table or the i/o system have some problem.

Moreover, another point it's : how much it's big ? the rows are arounf 94M , but how much it's big ?  it's important the average row length

Have a nice day

2014-03-06 15:45 GMT+01:00 acanada <acanada@xxxxxxx>:

Hello Mat,

Setting enable_bitmapscan to off doesn't really helps. It gets worse...

x=> SET enable_bitmapscan=off; 

SET

x=> explain analyze select * from (select * from entity2document2  where name='ranitidine' ) as a  order by a.hepval;

                                                                           QUERY PLAN                                                                           

----------------------------------------------------------------------------------------------------------------------------------------------------------------

 Sort  (cost=18789.21..18800.70 rows=4595 width=131) (actual time=79965.282..79966.657 rows=13512 loops=1)

   Sort Key: entity2document2.hepval

   Sort Method:  quicksort  Memory: 2301kB

   ->  Index Scan using entity2document2_name on entity2document2  (cost=0.00..18509.70 rows=4595 width=131) (actual time=67.507..79945.362 rows=13512 loops=1)

         Index Cond: ((name)::text = 'ranitidine'::text)

 Total runtime: 79967.705 ms

(6 rows)

Any other idea? 

Thank you very much for your help. Regards,

Andrés

El Mar 6, 2014, a las 2:11 PM, desmodemone escribió:

Il 05/mar/2014 00:36 "Venkata Balaji Nagothi" <vbnpgc@xxxxxxxxx> ha scritto:
>
> After looking at the distinct values, yes the composite Index on "name" and "hepval" is not recommended. That would worsen - its expected.
>
> We need to look for other possible work around. Please drop off the above Index. Let me see if i can drill further into this.
>
> Meanwhile - can you help us know the memory parameters (work_mem, temp_buffers etc) set ?
>
> Do you have any other processes effecting this query's performance ?
>
> Any info about your Disk, RAM, CPU would also help.
>
> Regards,
> Venkata Balaji N
>
> Fujitsu Australia
>
>
>
>
> Venkata Balaji N
>
> Sr. Database Administrator
> Fujitsu Australia
>
>
> On Tue, Mar 4, 2014 at 10:23 PM, acanada <acanada@xxxxxxx> wrote:
>>
>> Hello,
>>
>> I don't know if this helps to figure out what is the problem but after adding the multicolumn index on name and hepval, the performance is even worse (¿?).  Ten times worse...
>>
>> explain analyze select * from (select * from entity_compounddict2document  where name='progesterone') as a order by a.hepval;
>>                                                                          QUERY PLAN                                                                          
>> -------------------------------------------------------------------------------------------------------------------------------------------------------------
>>  Sort  (cost=422746.18..423143.94 rows=159104 width=133) (actual time=95769.674..95797.943 rows=138165 loops=1)
>>    Sort Key: entity_compounddict2document.hepval
>>    Sort Method:  quicksort  Memory: 25622kB
>>    ->  Bitmap Heap Scan on entity_compounddict2document  (cost=3501.01..408999.90 rows=159104 width=133) (actual time=70.789..95519.258 rows=138165 loops=1)
>>          Recheck Cond: ((name)::text = 'progesterone'::text)
>>          ->  Bitmap Index Scan on entity_compound2document_name  (cost=0.00..3461.23 rows=159104 width=0) (actual time=35.174..35.174 rows=138165 loops=1)
>>                Index Cond: ((name)::text = 'progesterone'::text)
>>  Total runtime: 95811.838 ms
>> (8 rows)
>>
>> Any ideas please?
>>
>> Thank you 
>> Andrés.
>>
>>
>>
>> El Mar 4, 2014, a las 12:28 AM, Venkata Balaji Nagothi escribió:
>>
>>> On Mon, Mar 3, 2014 at 9:17 PM, acanada <acanada@xxxxxxx> wrote:
>>>>
>>>> Hello,
>>>>
>>>> Thankyou for your answer.
>>>> I have made more changes than a simple re-indexing recently. I have moved the sorting field to the table in order to avoid the join clause. Now the schema is very simple. The query only implies one table:
>>>>
>>>> x=> \d+ entity_compounddict2document;
>>>>                       Table "public.entity_compounddict2document"
>>>>       Column      |              Type              | Modifiers | Storage  | Description 
>>>> ------------------+--------------------------------+-----------+----------+-------------
>>>>  id               | integer                        | not null  | plain    | 
>>>>  document_id      | integer                        |           | plain    | 
>>>>  name             | character varying(255)         |           | extended | 
>>>>  qualifier        | character varying(255)         |           | extended | 
>>>>  tagMethod        | character varying(255)         |           | extended | 
>>>>  created          | timestamp(0) without time zone |           | plain    | 
>>>>  updated          | timestamp(0) without time zone |           | plain    | 
>>>>  curation         | integer                        |           | plain    | 
>>>>  hepval           | double precision               |           | plain    | 
>>>>  cardval          | double precision               |           | plain    | 
>>>>  nephval          | double precision               |           | plain    | 
>>>>  phosval          | double precision               |           | plain    | 
>>>>  patternCount     | double precision               |           | plain    | 
>>>>  ruleScore        | double precision               |           | plain    | 
>>>>  hepTermNormScore | double precision               |           | plain    | 
>>>>  hepTermVarScore  | double precision               |           | plain    | 
>>>> Indexes:
>>>>     "entity_compounddict2document_pkey" PRIMARY KEY, btree (id)
>>>>     "entity_compound2document_cardval" btree (cardval)
>>>>     "entity_compound2document_heptermnormscore" btree ("hepTermNormScore")
>>>>     "entity_compound2document_heptermvarscore" btree ("hepTermVarScore")
>>>>     "entity_compound2document_hepval" btree (hepval)
>>>>     "entity_compound2document_name" btree (name)
>>>>     "entity_compound2document_nephval" btree (nephval)
>>>>     "entity_compound2document_patterncount" btree ("patternCount")
>>>>     "entity_compound2document_phosval" btree (phosval)
>>>>     "entity_compound2document_rulescore" btree ("ruleScore")
>>>> Has OIDs: no
>>>>
>>>>            tablename            |                   indexname                                              |  num_rows    | table_size  | index_size | unique | number_of_scans | tuples_read | tuples_fetched 
>>>>  entity_compounddict2document   | entity_compound2document_cardval               | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_heptermnormscore      | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_heptermvarscore       | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_hepval                | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_name                  | 5.42452e+07 | 6763 MB    | 1505 MB    | Y      |              24 |      178680 |              0
>>>>  entity_compounddict2document   | entity_compound2document_nephval               | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_patterncount          | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_phosval               | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compound2document_rulescore             | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>  entity_compounddict2document   | entity_compounddict2document_pkey              | 5.42452e+07 | 6763 MB    | 1162 MB    | Y      |               0 |           0 |              0
>>>>
>>>> The table has aprox. 54,000,000 rows
>>>> There are no NULLs in hepval field and pg_settings haven't changed. I also have done "analyze" to this table.
>>>>
>>>> I have simplified the query and added the last advise that you told me:
>>>>
>>>> Query: 
>>>>
>>>>  explain analyze select * from (select * from entity_compounddict2document  where name='ranitidine') as a order by a.hepval;
>>>>                                                                       QUERY PLAN                                                                      
>>>> ------------------------------------------------------------------------------------------------------------------------------------------------------
>>>>  Sort  (cost=11060.50..11067.55 rows=2822 width=133) (actual time=32715.097..32716.488 rows=13512 loops=1)
>>>>    Sort Key: entity_compounddict2document.hepval
>>>>    Sort Method:  quicksort  Memory: 2301kB
>>>>    ->  Bitmap Heap Scan on entity_compounddict2document  (cost=73.82..10898.76 rows=2822 width=133) (actual time=6.034..32695.483 rows=13512 loops=1)
>>>>          Recheck Cond: ((name)::text = 'ranitidine'::text)
>>>>          ->  Bitmap Index Scan on entity_compound2document_name  (cost=0.00..73.12 rows=2822 width=0) (actual time=3.221..3.221 rows=13512 loops=1)
>>>>                Index Cond: ((name)::text = 'ranitidine'::text)
>>>>  Total runtime: 32717.548 ms
>>>>
>>>> Another query:
>>>> explain analyze select * from (select * from entity_compounddict2document  where name='progesterone' ) as a  order by a.hepval;
>>>>
>>>> QUERY PLAN
>>>> ------------------------------------------------------------------------------------------------------------------------------------------------------------
>>>>  Sort  (cost=367879.25..368209.24 rows=131997 width=133) (actual time=9262.887..9287.046 rows=138165 loops=1)
>>>>    Sort Key: entity_compounddict2document.hepval
>>>>    Sort Method:  quicksort  Memory: 25622kB
>>>>    ->  Bitmap Heap Scan on entity_compounddict2document  (cost=2906.93..356652.81 rows=131997 width=133) (actual time=76.316..9038.485 rows=138165 loops=1)
>>>>          Recheck Cond: ((name)::text = 'progesterone'::text)
>>>>          ->  Bitmap Index Scan on entity_compound2document_name  (cost=0.00..2873.93 rows=131997 width=0) (actual time=40.913..40.913 rows=138165 loops=1)
>>>>                Index Cond: ((name)::text = 'progesterone'::text)
>>>>  Total runtime: 9296.815 ms
>>>>
>>>>
>>>> It has improved (I supose because of the lack of the join table) but still taking a lot of time... Anything I can do??
>>>>
>>>> Any help would be very appreciated. Thank you very much.
>>>
>>>
>>>
>>> Good to know performance has increased.
>>>
>>> "entity_compounddict2document" table goes through high INSERTS ?
>>>
>>> Can you help us know if the "helpval" column and "name" column have high duplicate values ? "n_distinct" value from pg_stats table would have that info. 
>>>
>>> Below could be a possible workaround -
>>>
>>> As mentioned earlier in this email, a composite Index on name and hepval column might help. If the table does not go through lot of INSERTS, then consider performing a CLUSTER on the table using the same INDEX.
>>>
>>> Other recommendations -
>>>
>>> Please drop off all the Non-primary key Indexes which have 0 scans / hits. This would harm the DB and the DB server whilst maintenance and DML operations.
>>>
>>> Regards,
>>> Venkata Balaji N
>>>
>>> Fujitsu Australia
>>
>>
>>
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>>
>

Hi I think the problem is th heap scan of the table , that the backend have to do because the btree to bitmap conversion becomes lossy. Try to disable the enable_bitmapscan for the current session and rerun the query.

Mat Dba

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