Ufuatiliaji wa utendaji wa hoja za PostgreSQL. Sehemu ya 1 - kuripoti

Mhandisi - kutafsiriwa kutoka Kilatini - aliongoza.
Mhandisi anaweza kufanya chochote. (c) R. Dizeli.
Epigraphs.

Au hadithi kuhusu kwa nini msimamizi wa hifadhidata anahitaji kukumbuka programu yake ya zamani.

utangulizi

Majina yote yamebadilishwa. Mechi ni za kubahatisha. Nyenzo ni maoni ya kibinafsi ya mwandishi.

Kanusho la dhamana: katika mfululizo uliopangwa wa makala hakutakuwa na maelezo ya kina na sahihi ya meza na maandiko yaliyotumiwa. Nyenzo haziwezi kutumika mara moja "AS IS".
Kwanza, kwa sababu ya idadi kubwa ya nyenzo.
pili, kwa sababu ya ukali na msingi wa uzalishaji wa mteja halisi.
Kwa hiyo, mawazo tu na maelezo katika fomu ya jumla yatatolewa katika makala.
Labda katika siku zijazo mfumo utakua hadi kiwango cha kuchapisha kwenye GitHub, au labda sivyo. Muda utaonyesha.

Mwanzo wa hadithi -Unakumbuka jinsi yote yalianza'.
Ni nini kilitokea kama matokeo, kwa maneno ya jumla - "Usanifu kama mojawapo ya mbinu za kuboresha utendaji wa PostgreSQL»

Kwa nini ninahitaji haya yote?

Kweli, kwanza, ili usijisahau, ukikumbuka siku tukufu za kustaafu.
Pili, kupanga kile kilichoandikwa. Kwa tayari mwenyewe, wakati mwingine mimi huanza kuchanganyikiwa na kusahau sehemu tofauti.

Naam, na muhimu zaidi - ghafla inaweza kuja kwa manufaa kwa mtu na kusaidia si kurejesha gurudumu na si kukusanya reki. Kwa maneno mengine, kuboresha karma yako (si Khabrovsky). Kwa maana jambo la thamani zaidi katika ulimwengu huu ni mawazo. Jambo kuu ni kupata wazo. Na kutafsiri wazo kuwa ukweli tayari ni suala la kiufundi.

Basi tuanze taratibu...

Uundaji wa shida.

Inapatikana:

PostgreSQL(10.5), mzigo mseto (OLTP+DSS), upakiaji wa kati hadi mwepesi, unaopangishwa katika wingu la AWS.
Hakuna ufuatiliaji wa hifadhidata, ufuatiliaji wa miundombinu unawasilishwa kama zana za kawaida za AWS katika usanidi mdogo.

Inahitajika:

Fuatilia utendakazi na hali ya hifadhidata, pata na uwe na taarifa ya awali ili kuboresha maswali mazito ya hifadhidata.

Utangulizi mfupi au uchambuzi wa suluhisho

Kuanza, hebu tujaribu kuchambua chaguzi za kutatua shida kutoka kwa mtazamo wa uchambuzi wa kulinganisha wa faida na shida za mhandisi, na wacha wale ambao wanapaswa kuwa kwenye orodha ya wafanyikazi washughulike na faida na hasara. ya usimamizi.

Chaguo 1 - "Kufanya kazi kwa mahitaji"

Tunaacha kila kitu kama ilivyo. Ikiwa mteja hajaridhika na kitu katika afya, utendakazi wa hifadhidata au programu, atawaarifu wahandisi wa DBA kwa barua pepe au kwa kuunda tukio kwenye kisanduku cha tikiti.
Mhandisi, akipokea arifa, ataelewa shida, atatoa suluhisho, au ataweka rafu shida, akitumaini kwamba kila kitu kitasuluhisha yenyewe, na hata hivyo, kila kitu kitasahaulika hivi karibuni.
Mkate wa tangawizi na donuts, michubuko na matutaMkate wa tangawizi na donuts:
1. Hakuna ziada ya kufanya
2. Daima kuna fursa ya kutoka na kupata uchafu.
3. Muda mwingi ambao unaweza kuutumia peke yako.
Michubuko na matuta:
1. Hivi karibuni au baadaye, mteja atafikiri juu ya kiini cha kuwa na haki ya ulimwengu wote katika ulimwengu huu na mara nyingine tena ajiulize swali - kwa nini ninawalipa pesa yangu? Matokeo huwa yale yale kila wakati - swali pekee ni wakati mteja anapata kuchoka na kutikiswa kwaheri. Na feeder ni tupu. Inasikitisha.
2. Maendeleo ya mhandisi ni sifuri.
3. Ugumu katika kupanga kazi na upakiaji

Chaguo 2 - "Ngoma na matari, vaa na uvae viatu"

Kifungu cha 1-Kwa nini tunahitaji mfumo wa ufuatiliaji, tutapokea maombi yote. Tunazindua rundo la maswali ya kila aina kwenye kamusi ya data na mionekano inayobadilika, kuwasha vihesabio vya kila aina, kuleta kila kitu kwenye majedwali, kuchambua mara kwa mara orodha na majedwali, kana kwamba ni. Matokeo yake, tuna grafu nzuri au sio sana, meza, ripoti. Jambo kuu - hiyo itakuwa zaidi, zaidi.
Kifungu cha 2-Kuzalisha shughuli-endesha uchambuzi wa haya yote.
Kifungu cha 3-Tunatayarisha hati fulani, tunaita hati hii, kwa urahisi - "tunawezaje kuandaa hifadhidata."
Kifungu cha 4- Mteja, akiona utukufu huu wote wa grafu na takwimu, yuko katika imani ya kitoto isiyo na maana - sasa kila kitu kitafanya kazi kwetu, hivi karibuni. Na, kwa urahisi na bila maumivu sehemu na rasilimali zao za kifedha. Usimamizi pia una uhakika kwamba wahandisi wetu wanafanya kazi kwa bidii. Upakiaji wa juu zaidi.
Kifungu cha 5- Rudia hatua ya 1 mara kwa mara.
Mkate wa tangawizi na donuts, michubuko na matutaMkate wa tangawizi na donuts:
1. Maisha ya wasimamizi na wahandisi ni rahisi, yanaweza kutabirika na kujazwa na shughuli. Kila kitu kinavuma, kila mtu yuko busy.
2. Maisha ya mteja pia sio mabaya - ana hakika kila wakati kuwa unahitaji kuwa na subira kidogo na kila kitu kitafanya kazi. Sio kuwa bora, vizuri, vizuri - ulimwengu huu hauna haki, katika maisha yajayo - utakuwa na bahati.
Michubuko na matuta:
1. Hivi karibuni au baadaye, kutakuwa na mtoa huduma nadhifu wa huduma kama hiyo ambayo itafanya kitu kimoja, lakini kwa bei nafuu kidogo. Na ikiwa matokeo ni sawa, kwa nini ulipe zaidi. Ambayo tena itasababisha kutoweka kwa feeder.
2. Inachosha. Jinsi shughuli yoyote ya maana inavyochosha.
3. Kama katika toleo la awali - hakuna maendeleo. Lakini kwa mhandisi, minus ni kwamba, tofauti na chaguo la kwanza, hapa unahitaji daima kuzalisha IDB. Na hiyo inachukua muda. Ambayo inaweza kutumika kwa faida ya mpendwa wako. Kwa maana huwezi kujijali mwenyewe, kila mtu anakujali.

Chaguo 3-Hakuna haja ya kuvumbua baiskeli, unahitaji kuinunua na kuiendesha.

Wahandisi kutoka makampuni mengine wanajua kula pizza na bia (oh, nyakati za utukufu wa St. Petersburg katika miaka ya 90). Hebu tutumie mifumo ya ufuatiliaji ambayo imeundwa, kutatuliwa na kufanya kazi, na kwa ujumla, inaleta manufaa (vizuri, angalau kwa waundaji wao).
Mkate wa tangawizi na donuts, michubuko na matutaMkate wa tangawizi na donuts:
1. Hakuna haja ya kupoteza muda kuvumbua kile ambacho tayari kimevumbuliwa. Chukua na utumie.
2. Mifumo ya ufuatiliaji haijaandikwa na wapumbavu, na bila shaka ni muhimu.
3. Mifumo ya ufuatiliaji wa kufanya kazi kawaida hutoa habari muhimu iliyochujwa.
Michubuko na matuta:
1. Mhandisi katika kesi hii si mhandisi, bali ni mtumiaji wa bidhaa ya mtu mwingine au mtumiaji.
2. Mteja lazima awe na hakika ya haja ya kununua kitu ambacho kwa ujumla hataki kuelewa, na haipaswi, na kwa ujumla bajeti ya mwaka imeidhinishwa na haitabadilika. Kisha unahitaji kutenga rasilimali tofauti, usanidi kwa mfumo maalum. Wale. Kwanza unahitaji kulipa, kulipa na kulipa tena. Na mteja ni bahili. Hii ndiyo kawaida ya maisha haya.

Nini cha kufanya, Chernyshevsky? Swali lako ni muhimu sana. (Pamoja na)

Katika kesi hii na hali ya sasa, unaweza kufanya tofauti kidogo - tutengeneze mfumo wetu wa ufuatiliaji.

Naam, si mfumo, bila shaka, kwa maana kamili ya neno, hii ni kubwa sana na ya kiburi, lakini angalau kwa namna fulani iwe rahisi kwako mwenyewe na kukusanya taarifa zaidi ili kutatua matukio ya utendaji. Ili usijikute katika hali - "nenda huko, sijui wapi, pata hiyo, sijui nini."

Ni nini faida na hasara za chaguo hili:

Faida:
1. Inavutia. Kweli, angalau ya kufurahisha zaidi kuliko "faili ya data iliyopunguzwa, badilisha nafasi ya meza, nk."
2. Hizi ni ujuzi mpya na maendeleo mapya. Ambayo katika siku zijazo, mapema au baadaye, itatoa mkate wa tangawizi unaostahili na donuts.
Minus:
1. Lazima kufanya kazi. Fanya kazi sana.
2. Utalazimika kueleza mara kwa mara maana na mitazamo ya shughuli zote.
3. Kitu kitalazimika kutolewa dhabihu, kwa sababu rasilimali pekee inayopatikana kwa mhandisi - wakati - imepunguzwa na Ulimwengu.
4. Mbaya zaidi na mbaya zaidi - kama matokeo, takataka kama "Sio panya, sio chura, lakini mnyama mdogo asiyejulikana" inaweza kugeuka.

Nani hahatarishi kitu hanywi champagne.
Kwa hivyo, furaha huanza.

Wazo la jumla - schematic

(Mchoro uliochukuliwa kutoka kwa kifungu «Usanifu kama mojawapo ya mbinu za kuboresha utendaji wa PostgreSQL")

Maelezo:

• Hifadhidata lengwa imesakinishwa kwa kiendelezi cha kawaida cha PostgreSQL "pg_stat_statements".
• Katika hifadhidata ya ufuatiliaji, tunaunda seti ya majedwali ya huduma ili kuhifadhi historia ya pg_stat_statements katika hatua ya awali na kusanidi vipimo na ufuatiliaji katika siku zijazo.
• Kwenye seva pangishi ya ufuatiliaji, tunaunda seti ya hati za bash, ikijumuisha zile za kutengeneza matukio katika mfumo wa tikiti.

Meza za huduma

Kuanza, ERD iliyorahisishwa kimkakati, ni nini kilifanyika mwishoni:

Maelezo mafupi ya mezaMwisho - mwenyeji, mahali pa uunganisho kwa mfano
database - Chaguzi za hifadhidata
pg_stat_historia - jedwali la kihistoria la kuhifadhi muhtasari wa muda wa pg_stat_statements mtazamo wa hifadhidata lengwa
metric_glossary - Kamusi ya vipimo vya utendaji
metric_config - usanidi wa metrics ya mtu binafsi
metric - kipimo mahususi cha ombi ambalo linafuatiliwa
historia_ya_tahadhari_ya_kipimo - historia ya maonyo ya utendaji
log_query - jedwali la huduma la kuhifadhi rekodi zilizochanganuliwa kutoka kwa faili ya kumbukumbu ya PostgreSQL iliyopakuliwa kutoka kwa AWS
msingi - vigezo vya muda uliotumika kama msingi
cheki - usanidi wa metrics kwa kuangalia hali ya hifadhidata
historia_ya_tahadhari - historia ya onyo ya vipimo vya ukaguzi wa hali ya hifadhidata
pg_stat_db_queries - Jedwali la huduma ya maombi amilifu
logi_ya_ shughuli - Jedwali la huduma ya kumbukumbu ya shughuli
trap_oid - Jedwali la huduma ya usanidi wa mtego

Hatua ya 1 - kukusanya takwimu za utendaji na kupata ripoti

Jedwali hutumiwa kuhifadhi habari za takwimu. pg_stat_historia
muundo wa jedwali la pg_stat_history

                                          Jedwali Safu ya "public.pg_stat_history" | aina | Virekebishaji------------------------------------------------ ------------------------------ kitambulisho | jumla | si chaguo-msingi batili nextval('pg_stat_history_id_seq'::regclass) muhuri_wa_muda | muhuri wa saa bila eneo la saa | kitambulisho_cha_data | jumla | dbid | mafuta | mtumiaji | mafuta | swali | kubwa | swali | maandishi | simu | kubwa | jumla_saa | usahihi maradufu | muda_wa_wakati | usahihi maradufu | muda_wa_max | usahihi maradufu | wakati_wa_wakati | usahihi maradufu | stddev_time | usahihi maradufu | safu | kubwa | pamoja_blks_hit | kubwa | pamoja_blks_kusoma | kubwa | imeshirikiwa_blks_iliyochafuliwa | kubwa | imeshirikiwa_blks_imeandikwa | kubwa | local_blks_hit | kubwa | local_blks_soma | kubwa | local_blks_chafu | kubwa | local_blks_imeandikwa | kubwa | temp_blks_soma | kubwa | temp_blks_imeandikwa | kubwa | blk_read_time | usahihi maradufu | blk_write_time | usahihi maradufu | kitambulisho_cha_msingi | jumla | Fahirisi: "pg_stat_history_pkey" UFUNGUO WA MSINGI, btree (id) "database_idx" btree (database_id) "queryid_idx" btree (queryid) "snapshot_timestamp_idx" btree (snapshot_timestamp) Ufunguo wa data ya kigeni "Kpingamizi_data ya ufunguo wa kigeni" REIGbase_database ya REIGRE: Vikwazo vya ufunguo wa kigeni hifadhidata ya NCES(id ) ILIPOFUTA KESI

Kama unaweza kuona, jedwali ni data ya jumla ya mtazamo pg_stat_statements katika hifadhidata lengwa.

Matumizi ya meza hii ni rahisi sana.

pg_stat_historia itawakilisha takwimu zilizokusanywa za utekelezaji wa hoja kwa kila saa. Mwanzoni mwa kila saa, baada ya kujaza meza, takwimu pg_stat_statements weka upya na pg_stat_statements_reset().
Kumbuka: Takwimu hukusanywa kwa maombi kwa muda wa zaidi ya sekunde 1.
Inajaza jedwali la pg_stat_history

--pg_stat_history.sql
CREATE OR REPLACE FUNCTION pg_stat_history( ) RETURNS boolean AS $$
DECLARE
  endpoint_rec record ;
  database_rec record ;
  pg_stat_snapshot record ;
  current_snapshot_timestamp timestamp without time zone;
BEGIN
  current_snapshot_timestamp = date_trunc('minute',now());  
  
  FOR endpoint_rec IN SELECT * FROM endpoint 
  LOOP
    FOR database_rec IN SELECT * FROM database WHERE endpoint_id = endpoint_rec.id 
	  LOOP
	    
		RAISE NOTICE 'NEW SHAPSHOT IS CREATING';
		
		--Connect to the target DB	  
	    EXECUTE 'SELECT dblink_connect(''LINK1'',''host='||endpoint_rec.host||' dbname='||database_rec.name||' user=USER password=PASSWORD '')';
 
        RAISE NOTICE 'host % and dbname % ',endpoint_rec.host,database_rec.name;
		RAISE NOTICE 'Creating snapshot of pg_stat_statements for database %',database_rec.name;
		
		SELECT 
	      *
		INTO 
		  pg_stat_snapshot
	    FROM dblink('LINK1',
	      'SELECT 
	       dbid , SUM(calls),SUM(total_time),SUM(rows) ,SUM(shared_blks_hit) ,SUM(shared_blks_read) ,SUM(shared_blks_dirtied) ,SUM(shared_blks_written) , 
           SUM(local_blks_hit) , SUM(local_blks_read) , SUM(local_blks_dirtied) , SUM(local_blks_written) , SUM(temp_blks_read) , SUM(temp_blks_written) , SUM(blk_read_time) , SUM(blk_write_time)
	       FROM pg_stat_statements WHERE dbid=(SELECT oid from pg_database where datname=current_database() ) 
		   GROUP BY dbid
  	      '
	               )
	      AS t
	       ( dbid oid , calls bigint , 
  	         total_time double precision , 
	         rows bigint , shared_blks_hit bigint , shared_blks_read bigint ,shared_blks_dirtied bigint ,shared_blks_written	 bigint ,
             local_blks_hit	 bigint ,local_blks_read bigint , local_blks_dirtied bigint ,local_blks_written bigint ,
             temp_blks_read	 bigint ,temp_blks_written bigint ,
             blk_read_time double precision , blk_write_time double precision	  
	       );
		 
		INSERT INTO pg_stat_history
          ( 
		    snapshot_timestamp  ,database_id  ,
			dbid , calls  ,total_time ,
            rows ,shared_blks_hit  ,shared_blks_read  ,shared_blks_dirtied  ,shared_blks_written ,local_blks_hit , 	 	
            local_blks_read,local_blks_dirtied,local_blks_written,temp_blks_read,temp_blks_written, 	
            blk_read_time, blk_write_time 
		  )		  
	    VALUES
	      (
	       current_snapshot_timestamp ,
		   database_rec.id ,
	       pg_stat_snapshot.dbid ,pg_stat_snapshot.calls,
	       pg_stat_snapshot.total_time,
	       pg_stat_snapshot.rows ,pg_stat_snapshot.shared_blks_hit ,pg_stat_snapshot.shared_blks_read ,pg_stat_snapshot.shared_blks_dirtied ,pg_stat_snapshot.shared_blks_written , 
           pg_stat_snapshot.local_blks_hit , pg_stat_snapshot.local_blks_read , pg_stat_snapshot.local_blks_dirtied , pg_stat_snapshot.local_blks_written , 
	       pg_stat_snapshot.temp_blks_read , pg_stat_snapshot.temp_blks_written , pg_stat_snapshot.blk_read_time , pg_stat_snapshot.blk_write_time 	   
	      );		   
		  
        RAISE NOTICE 'Creating snapshot of pg_stat_statements for queries with min_time more than 1000ms';
	
        FOR pg_stat_snapshot IN
          --All queries with max_time greater than 1000 ms
	      SELECT 
	        *
	      FROM dblink('LINK1',
	        'SELECT 
	         dbid , userid ,queryid,query,calls,total_time,min_time ,max_time,mean_time, stddev_time ,rows ,shared_blks_hit ,
			 shared_blks_read ,shared_blks_dirtied ,shared_blks_written , 
             local_blks_hit , local_blks_read , local_blks_dirtied , 
			 local_blks_written , temp_blks_read , temp_blks_written , blk_read_time , 
			 blk_write_time
	         FROM pg_stat_statements 
			 WHERE dbid=(SELECT oid from pg_database where datname=current_database() AND min_time >= 1000 ) 
  	        '

	                  )
	        AS t
	         ( dbid oid , userid oid , queryid bigint ,query text , calls bigint , 
  	           total_time double precision ,min_time double precision	 ,max_time double precision	 , mean_time double precision	 ,  stddev_time double precision	 , 
	           rows bigint , shared_blks_hit bigint , shared_blks_read bigint ,shared_blks_dirtied bigint ,shared_blks_written	 bigint ,
               local_blks_hit	 bigint ,local_blks_read bigint , local_blks_dirtied bigint ,local_blks_written bigint ,
               temp_blks_read	 bigint ,temp_blks_written bigint ,
               blk_read_time double precision , blk_write_time double precision	  
	         )
	    LOOP
		  INSERT INTO pg_stat_history
          ( 
		    snapshot_timestamp  ,database_id  ,
			dbid ,userid  , queryid  , query  , calls  ,total_time ,min_time ,max_time ,mean_time ,stddev_time ,
            rows ,shared_blks_hit  ,shared_blks_read  ,shared_blks_dirtied  ,shared_blks_written ,local_blks_hit , 	 	
            local_blks_read,local_blks_dirtied,local_blks_written,temp_blks_read,temp_blks_written, 	
            blk_read_time, blk_write_time 
		  )		  
	      VALUES
	      (
	       current_snapshot_timestamp ,
		   database_rec.id ,
	       pg_stat_snapshot.dbid ,pg_stat_snapshot.userid ,pg_stat_snapshot.queryid,pg_stat_snapshot.query,pg_stat_snapshot.calls,
	       pg_stat_snapshot.total_time,pg_stat_snapshot.min_time ,pg_stat_snapshot.max_time,pg_stat_snapshot.mean_time, pg_stat_snapshot.stddev_time ,
	       pg_stat_snapshot.rows ,pg_stat_snapshot.shared_blks_hit ,pg_stat_snapshot.shared_blks_read ,pg_stat_snapshot.shared_blks_dirtied ,pg_stat_snapshot.shared_blks_written , 
           pg_stat_snapshot.local_blks_hit , pg_stat_snapshot.local_blks_read , pg_stat_snapshot.local_blks_dirtied , pg_stat_snapshot.local_blks_written , 
	       pg_stat_snapshot.temp_blks_read , pg_stat_snapshot.temp_blks_written , pg_stat_snapshot.blk_read_time , pg_stat_snapshot.blk_write_time 	   
	      );
		  
        END LOOP;

        PERFORM dblink_disconnect('LINK1');  
				
	  END LOOP ;--FOR database_rec IN SELECT * FROM database WHERE endpoint_id = endpoint_rec.id 
    
  END LOOP;

RETURN TRUE;  
END
$$ LANGUAGE plpgsql;

Matokeo yake, baada ya muda fulani katika meza pg_stat_historia tutakuwa na seti ya snapshots ya yaliyomo kwenye jedwali pg_stat_statements hifadhidata inayolengwa.

Kwa kweli kuripoti

Kwa kutumia maswali rahisi, unaweza kupata ripoti muhimu na za kuvutia.

Data iliyojumlishwa kwa muda fulani

Omba

SELECT 
  database_id , 
  SUM(calls) AS calls ,SUM(total_time)  AS total_time ,
  SUM(rows) AS rows , SUM(shared_blks_hit)  AS shared_blks_hit,
  SUM(shared_blks_read) AS shared_blks_read ,
  SUM(shared_blks_dirtied) AS shared_blks_dirtied,
  SUM(shared_blks_written) AS shared_blks_written , 
  SUM(local_blks_hit) AS local_blks_hit , 
  SUM(local_blks_read) AS local_blks_read , 
  SUM(local_blks_dirtied) AS local_blks_dirtied , 
  SUM(local_blks_written)  AS local_blks_written,
  SUM(temp_blks_read) AS temp_blks_read, 
  SUM(temp_blks_written) temp_blks_written , 
  SUM(blk_read_time) AS blk_read_time , 
  SUM(blk_write_time) AS blk_write_time
FROM 
  pg_stat_history
WHERE 
  queryid IS NULL AND
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT
GROUP BY database_id ;

Wakati wa D.B

to_char(muda '1 millisecond' * pg_total_stat_history_rec.total_time, 'HH24:MI:SS.MS')

Wakati wa I/O

to_char(muda '1 millisecond' * ( pg_total_stat_history_rec.blk_read_time + pg_total_stat_history_rec.blk_write_time ), 'HH24:MI:SS.MS')

TOP10 SQL by total_time

Omba

SELECT 
  queryid , 
  SUM(calls) AS calls ,
  SUM(total_time)  AS total_time  	
FROM 
  pg_stat_history
WHERE 
  queryid IS NOT NULL AND 
  database_id = DATABASE_ID AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT 
GROUP BY queryid 
ORDER BY 3 DESC 
LIMIT 10

----------------------------------------------- ----------------------------------- | TOP10 SQL KWA JUMLA YA MUDA WA UTEKELEZAJI | #| swali| simu| simu %| jumla_saa (ms) | dbtime % +----+------------------------------------------ -------------------+----------- | 1| 821760255| 2| .00001|00:03:23.141( 203141.681 ms.)| 5.42 | 2| 4152624390| 2| .00001|00:03:13.929( 193929.215 ms.)| 5.17 | 3 | 1484454471| 4| .00001|00:02:09.129( 129129.057 ms.)| 3.44 | 4| 655729273| 1| .00000|00:02:01.869( 121869.981 ms.)| 3.25 | 5 | 2460318461| 1| .00000|00:01:33.113( 93113.835 ms.)| 2.48 | 6 | 2194493487| 4| .00001|00:00:17.377( 17377.868 ms.)| .46 | 7| 1053044345| 1| .00000|00:00:06.156( 6156.352 ms.)| .16 | 8| 3644780286| 1| .00000|00:00:01.063( 1063.830 ms.)| .03

TOP10 SQL kwa jumla ya muda wa I/O

Omba

SELECT 
  queryid , 
  SUM(calls) AS calls ,
  SUM(blk_read_time + blk_write_time)  AS io_time
FROM 
  pg_stat_history
WHERE 
  queryid IS NOT NULL AND 
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT
GROUP BY  queryid 
ORDER BY 3 DESC 
LIMIT 10

----------------------------------------------- ------------------------------------- | TOP10 SQL KWA JUMLA YA WAKATI WA I/O | #| swali| simu| simu %| Wakati wa I/O (ms)|db I/O wakati % +----+-------------------------------- -----+------------------------------+----------- -- | 1| 4152624390| 2| .00001|00:08:31.616( 511616.592 ms.)| Juni 31.06 | 2| 821760255| 2| .00001|00:08:27.099( 507099.036 ms.)| 30.78 | 3 | 655729273| 1| .00000|00:05:02.209( 302209.137 ms.)| 18.35 | 4| 2460318461| 1| .00000|00:04:05.981( 245981.117 ms.)| 14.93 | 5 | 1484454471| 4| .00001|00:00:39.144( 39144.221 ms.)| 2.38 | 6 | 2194493487| 4| .00001|00:00:18.182( 18182.816 ms.)| 1.10 | 7| 1053044345| 1| .00000|00:00:16.611( 16611.722 ms.)| 1.01 | 8| 3644780286| 1| .00000|00:00:00.436( 436.205 ms.)| .03

TOP10 SQL kwa muda wa juu zaidi wa utekelezaji

Omba

SELECT 
  id AS snapshotid , 
  queryid , 
  snapshot_timestamp ,  
  max_time 
FROM 
  pg_stat_history 
WHERE 
  queryid IS NOT NULL AND 
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT
ORDER BY 4 DESC 
LIMIT 10

----------------------------------------------- ----------------------------------- | TOP10 SQL KWA MUDA MAX WA UTEKELEZAJI | #| picha | snapshotID| swali| max_time (ms) +----+--------------------------------------- --+-------------------------------------- | 1| 05.04.2019/01/03 4169:655729273| 00| 02| 01.869:121869.981:2( 04.04.2019 ms.) | 17| 00/4153/821760255 00:01| 41.570| 101570.841| 3:04.04.2019:16( 00 ms.) | 4146 | 821760255/00/01 41.570:101570.841| 4| 04.04.2019| 16:00:4144( 4152624390 ms.) | 00| 01/36.964/96964.607 5:04.04.2019| 17| 00| 4151:4152624390:00( 01 ms.) | 36.964 | 96964.607/6/05.04.2019 10:00| 4188| 1484454471| 00:01:33.452( 93452.150 ms.) | 7 | 04.04.2019/17/00 4150:2460318461 | 00| 01| 33.113:93113.835:8( 04.04.2019 ms.) | 15| 00/4140/1484454471 00:00| 11.892| 11892.302| 9:04.04.2019:16( 00 ms.) | 4145| 1484454471/00/00 11.892:11892.302| 10| 04.04.2019| 17:00:4152( 1484454471 ms.) | 00| 00/11.892/11892.302 XNUMX:XNUMX| XNUMX| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.) | XNUMX | XNUMX/XNUMX/XNUMX XNUMX:XNUMX| XNUMX| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.)

TOP10 SQL kwa SHARED buffer soma/andika

Omba

SELECT 
  id AS snapshotid , 
  queryid ,
  snapshot_timestamp , 
  shared_blks_read , 
  shared_blks_written 
FROM 
  pg_stat_history
WHERE 
  queryid IS NOT NULL AND 
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT AND
  ( shared_blks_read > 0 OR shared_blks_written > 0 )
ORDER BY 4 DESC  , 5 DESC 
LIMIT 10

----------------------------------------------- ----------------------------------- | TOP10 SQL KWA BUFFER ILIYOSHIRIKIWA SOMA/ANDIKA | #| picha | snapshotID| swali| vizuizi vilivyoshirikiwa soma| vizuizi vilivyoshirikiwa andika +----+----------------------------------------- -+------------------------------------------------------------------------------------------------- 1| 04.04.2019/17/00 4153:821760255| 797308| 0| 2| 04.04.2019 | 16| 00/4146/821760255 797308:0| 3| 05.04.2019| 01| 03 | 4169 | 655729273/797158/0 4:04.04.2019| 16| 00| 4144| 4152624390 | 756514| 0/5/04.04.2019 17:00| 4151| 4152624390| 756514| 0 | 6 | 04.04.2019/17/00 4150:2460318461| 734117| 0| 7| 04.04.2019 | 17 | 00/4155/3644780286 52973:0| 8| 05.04.2019| 01| 03 | 4168| 1053044345/52818/0 9:04.04.2019| 15| 00| 4141| 2194493487 | 52813| 0/10/04.04.2019 16:00| 4147| 2194493487| 52813| 0 | XNUMX| XNUMX/XNUMX/XNUMX XNUMX:XNUMX| XNUMX| XNUMX| XNUMX| XNUMX | XNUMX | XNUMX/XNUMX/XNUMX XNUMX:XNUMX| XNUMX| XNUMX| XNUMX| XNUMX ---------------------------------------------- -----------------------------------------------

Histogramu ya usambazaji wa hoja kwa muda wa juu zaidi wa utekelezaji

Maombi

SELECT  
  MIN(max_time) AS hist_min  , 
  MAX(max_time) AS hist_max , 
  (( MAX(max_time) - MIN(min_time) ) / hist_columns ) as hist_width
FROM 
  pg_stat_history 
WHERE 
  queryid IS NOT NULL AND
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT ;

SELECT 
  SUM(calls) AS calls
FROM 
  pg_stat_history 
WHERE 
  queryid IS NOT NULL AND
  database_id =DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT AND 
  ( max_time >= hist_current_min AND  max_time < hist_current_max ) ;

|---------------------------------------------- --------------------------------------- | MAX_TIME HIstoGRAM | JUMLA YA SIMU : 33851920 | MUDA WA DAKIKA : 00:00:01.063 | MAX TIME : 00:02:01.869 --------------------------------- -------- --------------------------- | muda wa dakika| muda wa juu| simu +----------------------------------------------- --------------------+----------- | 00:00:01.063( 1063.830 ms.) | 00:00:13.144( 13144.445 ms.) | 9 | 00:00:13.144( 13144.445 ms.) | 00:00:25.225( 25225.060 ms.) | 0 | 00:00:25.225( 25225.060 ms.) | 00:00:37.305( 37305.675 ms.) | 0 | 00:00:37.305( 37305.675 ms.) | 00:00:49.386( 49386.290 ms.) | 0 | 00:00:49.386( 49386.290 ms.) | 00:01:01.466( 61466.906 ms.) | 0 | 00:01:01.466( 61466.906 ms.) | 00:01:13.547( 73547.521 ms.) | 0 | 00:01:13.547( 73547.521 ms.) | 00:01:25.628( 85628.136 ms.) | 0 | 00:01:25.628( 85628.136 ms.) | 00:01:37.708( 97708.751 ms.) | 4 | 00:01:37.708( 97708.751 ms.) | 00:01:49.789( 109789.366 ms.) | 2 | 00:01:49.789( 109789.366 ms.) | 00:02:01.869( 121869.981 ms.) | 0

Picha 10 za TOP kwa Hoja kwa Sekunde

Maombi

--pg_qps.sql
--Calculate Query Per Second 
CREATE OR REPLACE FUNCTION pg_qps( pg_stat_history_id integer ) RETURNS double precision AS $$
DECLARE
 pg_stat_history_rec record ;
 prev_pg_stat_history_id integer ;
 prev_pg_stat_history_rec record;
 total_seconds double precision ;
 result double precision;
BEGIN 
  result = 0 ;
  
  SELECT *
  INTO pg_stat_history_rec
  FROM 
    pg_stat_history
  WHERE id = pg_stat_history_id ;

  IF pg_stat_history_rec.snapshot_timestamp IS NULL 
  THEN
    RAISE EXCEPTION 'ERROR - Not found pg_stat_history for id = %',pg_stat_history_id;
  END IF ;  
  
 --RAISE NOTICE 'pg_stat_history_id = % , snapshot_timestamp = %', pg_stat_history_id , 
 pg_stat_history_rec.snapshot_timestamp ;
  
  SELECT 
    MAX(id)   
  INTO
    prev_pg_stat_history_id
  FROM
    pg_stat_history
  WHERE 
    database_id = pg_stat_history_rec.database_id AND
	queryid IS NULL AND
	id < pg_stat_history_rec.id ;

  IF prev_pg_stat_history_id IS NULL 
  THEN
    RAISE NOTICE 'Not found previous pg_stat_history shapshot for id = %',pg_stat_history_id;
	RETURN NULL ;
  END IF;
  
  SELECT *
  INTO prev_pg_stat_history_rec
  FROM 
    pg_stat_history
  WHERE id = prev_pg_stat_history_id ;
  
  --RAISE NOTICE 'prev_pg_stat_history_id = % , prev_snapshot_timestamp = %', prev_pg_stat_history_id , prev_pg_stat_history_rec.snapshot_timestamp ;    

  total_seconds = extract(epoch from ( pg_stat_history_rec.snapshot_timestamp - prev_pg_stat_history_rec.snapshot_timestamp ));
  
  --RAISE NOTICE 'total_seconds = % ', total_seconds ;    
  
  --RAISE NOTICE 'calls = % ', pg_stat_history_rec.calls ;      
  
  IF total_seconds > 0 
  THEN
    result = pg_stat_history_rec.calls / total_seconds ;
  ELSE
   result = 0 ; 
  END IF;
   
 RETURN result ;
END
$$ LANGUAGE plpgsql;


SELECT 
  id , 
  snapshot_timestamp ,
  calls , 	
  total_time , 
  ( select pg_qps( id )) AS QPS ,
  blk_read_time ,
  blk_write_time
FROM 
  pg_stat_history
WHERE 
  queryid IS NULL AND 
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT AND
  ( select pg_qps( id )) IS NOT NULL 
ORDER BY 5 DESC 
LIMIT 10

|---------------------------------------------- --------------------------------------- | Picha 10 za TOP1 zilizopangwa kwa nambari za QueryPerSeconds ----------------------------------------------------------- ------------------------------------------ ------ ------------------------------------------ | #| picha | snapshotID| simu| jumla ya muda wa db| QPS | Wakati wa I/O | I/O wakati % +-----+-------------------------------------- ----+--------------------------------+---------- -+--------------------------------+-------------------------------------------------------------------------------------------------------------------------------- 04.04.2019| 20/04/4161 5758631:00| 06| 30.513| 390513.926:1573.396:00( 00 ms.)| 01.470| 1470.110:376:2( 04.04.2019 ms.)| .17 | 00| 4149/3529197/00 11:48.830| 708830.618| 980.332| 00:12:47.834( 767834.052 ms.)| 108.324| 3:04.04.2019:16( 00 ms.)| 4143 | 3525360 | 00/10/13.492 613492.351:979.267| 00| 08| 41.396:521396.555:84.988( 4 ms.)| 04.04.2019| 21:03:4163( 2781536 ms.)| 00 | 03| 06.470/186470.979/785.745 00:00| 00.249| 249.865| 134:5:04.04.2019( 19 ms.)| 03| 4159:2890362:00( 03 ms.)| .16.784 | 196784.755 | 776.979/00/00 01.441:1441.386| 732| 6| 04.04.2019:14:00( 4137 ms.)| 2397326| 00:04:43.033( 283033.854 ms.)| .665.924 | 00 | 00/00.024/24.505 009:7| 04.04.2019| 15| 00:4139:2394416( 00 ms.)| 04| 51.435:291435.010:665.116( 00 ms.)| .00 | 12.025| 12025.895/4.126/8 04.04.2019:13| 00| 4135| 2373043:00:04( 26.791 ms.)| 266791.988| 659.179:00:00( 00.064 ms.)| 64.261 | 024| 9/05.04.2019/01 03:4167| 4387191| 00| 06:51.380:411380.293( 609.332 ms.)| 00| 05:18.847:318847.407( 77.507 ms.)| .10 | 04.04.2019| 18/01/4157 1145596:00| 01| 19.217| 79217.372:313.004:00( 00 ms.)| 01.319| 1319.676:1.666:XNUMX( XNUMX ms.)| XNUMX | XNUMX | XNUMX/XNUMX/XNUMX XNUMX:XNUMX| XNUMX| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.)| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.)| XNUMX

Historia ya Utekelezaji ya Kila Saa yenye QueryPerSeconds na Wakati wa I/O

Omba

SELECT 
  id , 
  snapshot_timestamp ,
  calls , 	
  total_time , 
  ( select pg_qps( id )) AS QPS ,
  blk_read_time ,
  blk_write_time
FROM 
  pg_stat_history
WHERE 
  queryid IS NULL AND 
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT
ORDER BY 2

|-----------------------------------------------------------------------------------------------
| HOURLY EXECUTION HISTORY  WITH QueryPerSeconds and I/O Time
-----------------------------------------------------------------------------------------------------------------------------------------------
| QUERY PER SECOND HISTORY
|    #|          snapshot| snapshotID|      calls|                      total dbtime|        QPS|                          I/O time| I/O time %
+-----+------------------+-----------+-----------+----------------------------------+-----------+----------------------------------+-----------
|    1|  04.04.2019 11:00|       4131|       3747|  00:00:00.835(       835.374 ms.)|      1.041|  00:00:00.000(          .000 ms.)|       .000
|    2|  04.04.2019 12:00|       4133|    1002722|  00:01:52.419(    112419.376 ms.)|    278.534|  00:00:00.149(       149.105 ms.)|       .133
|    3|  04.04.2019 13:00|       4135|    2373043|  00:04:26.791(    266791.988 ms.)|    659.179|  00:00:00.064(        64.261 ms.)|       .024
|    4|  04.04.2019 14:00|       4137|    2397326|  00:04:43.033(    283033.854 ms.)|    665.924|  00:00:00.024(        24.505 ms.)|       .009
|    5|  04.04.2019 15:00|       4139|    2394416|  00:04:51.435(    291435.010 ms.)|    665.116|  00:00:12.025(     12025.895 ms.)|      4.126
|    6|  04.04.2019 16:00|       4143|    3525360|  00:10:13.492(    613492.351 ms.)|    979.267|  00:08:41.396(    521396.555 ms.)|     84.988
|    7|  04.04.2019 17:00|       4149|    3529197|  00:11:48.830(    708830.618 ms.)|    980.332|  00:12:47.834(    767834.052 ms.)|    108.324
|    8|  04.04.2019 18:01|       4157|    1145596|  00:01:19.217(     79217.372 ms.)|    313.004|  00:00:01.319(      1319.676 ms.)|      1.666
|    9|  04.04.2019 19:03|       4159|    2890362|  00:03:16.784(    196784.755 ms.)|    776.979|  00:00:01.441(      1441.386 ms.)|       .732
|   10|  04.04.2019 20:04|       4161|    5758631|  00:06:30.513(    390513.926 ms.)|   1573.396|  00:00:01.470(      1470.110 ms.)|       .376
|   11|  04.04.2019 21:03|       4163|    2781536|  00:03:06.470(    186470.979 ms.)|    785.745|  00:00:00.249(       249.865 ms.)|       .134
|   12|  04.04.2019 23:03|       4165|    1443155|  00:01:34.467(     94467.539 ms.)|    200.438|  00:00:00.015(        15.287 ms.)|       .016
|   13|  05.04.2019 01:03|       4167|    4387191|  00:06:51.380(    411380.293 ms.)|    609.332|  00:05:18.847(    318847.407 ms.)|     77.507
|   14|  05.04.2019 02:03|       4171|     189852|  00:00:10.989(     10989.899 ms.)|     52.737|  00:00:00.539(       539.110 ms.)|      4.906
|   15|  05.04.2019 03:01|       4173|       3627|  00:00:00.103(       103.000 ms.)|      1.042|  00:00:00.004(         4.131 ms.)|      4.010
|   16|  05.04.2019 04:00|       4175|       3627|  00:00:00.085(        85.235 ms.)|      1.025|  00:00:00.003(         3.811 ms.)|      4.471
|   17|  05.04.2019 05:00|       4177|       3747|  00:00:00.849(       849.454 ms.)|      1.041|  00:00:00.006(         6.124 ms.)|       .721
|   18|  05.04.2019 06:00|       4179|       3747|  00:00:00.849(       849.561 ms.)|      1.041|  00:00:00.000(          .051 ms.)|       .006
|   19|  05.04.2019 07:00|       4181|       3747|  00:00:00.839(       839.416 ms.)|      1.041|  00:00:00.000(          .062 ms.)|       .007
|   20|  05.04.2019 08:00|       4183|       3747|  00:00:00.846(       846.382 ms.)|      1.041|  00:00:00.000(          .007 ms.)|       .001
|   21|  05.04.2019 09:00|       4185|       3747|  00:00:00.855(       855.426 ms.)|      1.041|  00:00:00.000(          .065 ms.)|       .008
|   22|  05.04.2019 10:00|       4187|       3797|  00:01:40.150(    100150.165 ms.)|      1.055|  00:00:21.845(     21845.217 ms.)|     21.812

Maandishi ya SQL zote zilizochaguliwa

Omba

SELECT 
  queryid , 
  query 
FROM 
  pg_stat_history
WHERE 
  queryid IS NOT NULL AND 
  database_id = DATABASE_ID  AND
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT AND END_TIMEPOINT
GROUP BY queryid , query

Jumla ya

Kama unaweza kuona, kwa njia rahisi, unaweza kupata habari nyingi muhimu kuhusu mzigo wa kazi na hali ya hifadhidata.

Kumbuka:Ukirekebisha swali katika maswali, basi tutapata historia kwa ombi tofauti (ili kuhifadhi nafasi, ripoti za ombi tofauti zimeachwa).

Kwa hivyo, data ya takwimu juu ya utendaji wa hoja inapatikana na kukusanywa.
Hatua ya kwanza "mkusanyiko wa data ya takwimu" imekamilika.

Unaweza kuendelea hadi hatua ya pili - "kusanidi vipimo vya utendaji".


Lakini hiyo ni hadithi tofauti kabisa.

Kuendelea ...

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