PostgreSQL pĂ€ringute tulemuslikkuse jĂ€lgimine. Osa 1 — aruandlus

Insener — ladina keelest tĂ”lgituna — inspireeritud.
Insener suudab kÔike. (c) R.Dizel.
Epigrammid.
PostgreSQL pĂ€ringute tulemuslikkuse jĂ€lgimine. Osa 1 — aruandlus
VÔi lugu sellest, miks andmebaasi administraator peab meenutama oma programmeerija minevikku.

EessÔna

KÔik nimed on muudetud. Kokkusattumised on juhuslikud. Materjal esindab autori isiklikku arvamust.

GarantiivÀÀrdenyse lahtiseletus: planeeritavas artiklite tsĂŒklis ei ole pĂ”hjalikku ja tĂ€pset kirjeldust kasutatud tabelite ja skriptide kohta. Materjale ei saa kohe kasutada "NII NAGU ON".
Esiteks, materjali suuruse tÔttu,
teiseks, kuna see on suunatud reaalse kliendi prodaktsiooni baasi.
SeetĂ”ttu sisaldavad artiklid vaid ideid ja kirjeldusi ĂŒldiselt.
VĂ”ib-olla tulevikus sĂŒsteem kasvab selleni, et see tĂ”statatakse GitHubi, aga vĂ”ib-olla ka mitte. Aeg nĂ€itab.

Loo algus — "Kas sa mĂ€letad, kuidas kĂ”ik algas».
Mis tulemuseks sai, kĂ”ige ĂŒldisemates joontes — "SĂŒntes kui ĂŒks meetod PostgreSQLi jĂ”udluse parandamiseks»

Miks mul seda kÔike vaja on?

No, esmalt, et ise ei unustaks, meenutades pensionile jÀÀdes hiidpÀevi.
Teiseks, et sĂŒstematiseerida kirjutatut. Sest isegi mina, mĂ”nikord, hakkan segadusse minema ja unustan eraldi osad.

Ja mis kĂ”ige tĂ€htsam — Ă€kki on see kellelegi kasulik ja aitab vĂ€ltida rattaga taassĂŒnni ja naelu korjamist. TeisisĂ”nu, parandada oma kar maha (mitte Habr'i oma). Sest kĂ”ige vÀÀrtuslikum asi selles maailmas on ideed. Peamine on leida idee. Idee teostamine reaalsuses on juba puhtalt tehniline kĂŒsimus.

Nii et, alustame, tasapisi...

Probleemi seadmine.

On olemas:

Andmebaas PostgreSQL (10.5), segatud koormusega (OLTP+DSS), keskmise-vÀikese koormusega, mis asub AWS pilves.
Andmebaasi jÀlgimine puudub, infrastruktuuri jÀlgimine on esindatud AWS standardsete vahenditega minimaalsetes seadistustes.

NÔutav:

JÀlgida andmebaasi jÔudlust ja seisundit, leida ja omada algandmeid raskete pÀringute optimeerimiseks andmebaasile.

LĂŒhike eelĂ”htu vĂ”i lahenduste variandid

Kuna, proovime kĂ”igepealt lahenduse vĂ”imalusi lahata vĂ”rdleva analĂŒĂŒsi valguses, kasu ja probleemidega insenerile, samas kui kasumi ja kahjude ĂŒle muretsegu need, kellele see kuulub vastavalt ametijuhendile.

Variant 1 - «Töötame nÔudmisel»

JÀtame kÔik nii nagu on. Kui tellija ei ole rahul andmebaasi vÔi rakenduse töövÔime vÔi jÔudlusega, teavitab ta DBA insenere e-posti teel vÔi loob probleemist pÀringu tiketikaupa.
Insener, olles teate saanud, uurib probleemi, pakub lahendust vĂ”i lĂŒkkab probleemi edasisse tulevikku, lootes, et see lahendatakse iseenesest ning varsti unustatakse ikkagi.
KĂŒpsised ja pannkoogid, sinikad ja muhkudKĂŒpsised ja pannkoogid:
1. Ei ole vaja midagi liigset teha.
2. Alati on vÔimalus vabandada ja kergekÀeliselt asja kÀsitleda.
3. Üksjagu aega, mida saab kasutada omal soovil.
Sinikad ja muhkud:
1. Varsti vĂ”i hiljem hakkab tellija mĂ”tlema eluteemale ja universumliku Ă”iguse olemusele ning esitab endale taas kĂŒsimuse — milleks ma maksan neile oma raha? TagajĂ€rg on alati sama — kĂŒsimus on vaid selles, millal tellija kaotab huvi ja loobub. Ja toiduahela tĂŒhjaks jÀÀb. See on kurb.
2. Inseneri areng — null.
3. Töö planeerimise ja koormuse keerukused.

Variant 2 - «Tantsime trummide ĂŒmber, mĂŒĂŒme ja varustame»

Punkt 1-Miks me vajame seire sĂŒsteemi? Saame kĂ”ik pĂ€ringud. KĂ€ivitame erinevaid pĂ€ringuid andmebaasi ja dĂŒnaamiliste esitusviiside kaudu, aktiveerime mitmesuguseid loendureid, koondame kĂ”ik tabelitesse ja perioodiliselt analĂŒĂŒsime neid. Tulemuseks on ilusad vĂ”i vĂ€hem ilusad graafikud, tabelid ja raportid. Peamine on, et neid oleks palju, palju.
Punkt2-KĂ€ivitame aktiivsuse - teeme kogu selle analĂŒĂŒsi.
Punkt3-Valmistame ette mingi dokumendi, kutsume seda lihtsalt - «kuidas korraldada andmebaasi».
Punkt4-Kliendi nĂ€hes seda graafikute ja numbrite ilu usub lapseoomes naiivsuses, et nĂŒĂŒd kĂ”ik hakkab tööle, varsti. Ja loobub lihtsalt ja valutult oma rahalistest ressurssidest. Juhtkond on samuti kindel - meie insenerid teevad head tööd. Koormus on maksimaalne.
Punkt5-Korrata regulaarselt punkti 1.
KĂŒpsised ja pannkoogid, sinikad ja muhkudKĂŒpsised ja pannkoogid:
1. Juhtide ja inseneride elu on lihtne, ettearvatav ja tÀis aktiivsust. KÔik sumiseb, kÔik on hÔivatud.
2. Klientide elu ei ole samuti halb — nad on alati kindlad, et tuleb vaid veidi oodata ja kĂ”ik laabub. Kui see ei toimi, noh, mis siis — maailm on ebaĂ”iglane, jĂ€rgmises elus on ehk vedamine.
Sinikad ja muhkud:
1. Varsti vÔi hiljem leitakse kiirem teenusepakkuja, kes teeb sama asja pisut odavamalt. Ja kui tulemus on sama, miks maksta rohkem? See viib jÀlle toidupauside kadumiseni.
2. See on igav. Nagu igasugune vÀhe mÔtestatud tegevus.
3. Nagu eelnevas variandis — arengut ei toimu. Kuid inseneri jaoks on miinus see, et eristavalt esimese variandi puhul tuleb siin pidevalt genereerida andmebaasi. See Ă”tab aega. Mille vĂ”iks kulutada enda kasuks. Sest kui sa enda eest ei hoolitse, siis ei hooli keegi sinust.

Variant 3 — pole vaja leiutada jalgratast, tuleb see osta ja sĂ”ita.

Teiste firmade insenerid ei söö pitsa ja joo Ă”lut asjata (ah, need head ajad Peterburi 90ndatel). Kasutame juba olemasolevaid monitooringusĂŒsteeme, mis on vĂ€lja töötatud, tööd ja toovad ĂŒldiselt kasu (noh, vĂ€hemalt nende loojatele).
KĂŒpsised ja pannkoogid, sinikad ja muhkudKĂŒpsised ja pannkoogid:
1. Ei ole vajalik kulutada aega sellele, mis on juba vÀlja mÔeldud. Lihtsalt vÔta ja kasuta.
2. MonitooringusĂŒsteemide loomine ei ole lollide teema; nad on kindlasti kasulikud.
3. Tootlikud monitooringusĂŒsteemid annavad tavaliselt kasulikku filtreeritud teavet.
Sinikad ja muhkud:
1. Insener ei ole siin insener, vaid lihtsalt kellegi teise toote kasutaja. VÔi kasutaja.
2. Tellijat tuleb veenda, et on vaja osta midagi, millesse ta ei soovi sĂŒveneda, ning mis tal ei peaks olema ka kohustuseks, ning aastabĂŒrot on kinnitatud ja ei muutu. SeejĂ€rel tuleb eraldi ressursid eraldada ja need konkreetse sĂŒsteemi jaoks seadistada. Ehk siis kĂ”igepealt tuleb maksta, maksta ja veel kord maksta. Tellija on aga kitsi. See on elu norm.

Mis siis teha - TĆĄernÔƥevski? Sinu kĂŒsimus on tĂ€iesti kohane. (c)

Antud konkreetses olukorras ja olemasolevate asjaolude tĂ”ttu on vĂ”imalik tegutseda veidi teisiti — aga loome omaenda monitooringusĂŒsteemi.
PostgreSQL pĂ€ringute tulemuslikkuse jĂ€lgimine. Osa 1 — aruandlus
Muidugi mitte sĂŒsteemi tĂ€ielikus mĂ”ttes, see oleks liiga suurejooneline ja enesekehtestav, kuid vĂ€hemalt vĂ”iks endale ĂŒlesande lihtsamaks teha ning koguda rohkem teavet jĂ”udluse probleemide lahendamiseks. Et mitte sattuda olukorda — „mine sinna, ei tea kuhu, leia see, ei tea mida.”

Millised on selle variandi plussid ja miinused:

Plussid:
1. See on huvitav. No vĂ€hemalt huvitavam kui pidevad „shrink datafile, alter tablespace jne.”
2. Need on uued oskused ja uus areng. Mis tulevikus varem vÔi hiljem toob vÀlja teenitud preemiad ja maiustused.
Miinused:
1. Töö tuleb teha. Töö tuleb palju teha.
2. Tuleb regulaarselt seletada, mis on kogu tegevuse mÔte ja perspektiivid.
3. Millegagi tuleb ohverdada, kuna inseneri ainus saadaval olev ressurss — aeg — on Universumi piiratud.
4. KĂ”ige hullem ja kĂ”ige ebameeldivam — vĂ”ib tulemuseks olla midagi, mis on „Ei hiirepojake, ei konn, vaid tundmatu loom.”

Kes ei riski, see ei joo ĆĄampanjat.
Nii et — algab kĂ”ige huvitavam osa.

Üldine idee — skeemiliselt

PostgreSQL pĂ€ringute tulemuslikkuse jĂ€lgimine. Osa 1 — aruandlus
(Illustratsioon on vĂ”etud artiklist «SĂŒntes kui ĂŒks meetod PostgreSQLi jĂ”udluse parandamiseks»)

Selgitus:

  • Sihtandmebaasi installitakse PostgreSQLi standaardne laiendus — „pg_stat_statements.”
  • JĂ€lgimisandmebaasis loome teenuste tabelite komplekti pg_stat_statements ajaloo salvestamiseks algfaasis ning edaspidiste mÔÔdikute ja jĂ€lgimise seadistamiseks.
  • JĂ€lgimisseadmestikus loome bash-skriptide komplekti, sealhulgas tĂ”rgete genereerimiseks pileti sĂŒsteemis.

Teenustabelid

Alustuseks skeemiliselt lihtsustatud ERD, mis me lÔpuks saime:
PostgreSQL pĂ€ringute tulemuslikkuse jĂ€lgimine. Osa 1 — aruandlus
Tabelite lĂŒhike kirjeldusendpoint — host, ĂŒhenduspunkt instantsiga
database — andmebaasi parameetrid
pg_stat_history — ajaline tabel, mis salvestab ajutised nĂ€idud pg_stat_statements vaates sihtandmebaasist
metric_glossary — jĂ”udluse mÔÔdikute sĂ”nastik
metric_config — konkreetsete mÔÔdikute konfiguratsioon
metric — konkreetne mÔÔdik jĂ€lgitavale pĂ€ringule
metric_alert_history — jĂ”udluse hoiatusite ajalugu
log_query — teenustabel, mis salvestab PostgreSQL logifailist analĂŒĂŒsitud kirjeid, mis laaditakse AWSt
baseline — ajavahemiku parameetrid, mida kasutatakse baasi alusena
checkpoint — andmebaasi olekukontrolli mÔÔdikute konfiguratsioon
checkpoint_alert_history — andmebaasi olekukontrolli mÔÔdikute hoiatusite ajalugu
pg_stat_db_queries — aktiivsete pĂ€ringute teenustabel
activity_log — aktiivsuse logi teenustabel
trap_oid — trap konfiguratsiooni teenustabel

Etapp 1 — kogume jĂ”udluse statistikat ja saame aruanded

Statistika talletamiseks kasutatakse tabelit pg_stat_history
pg_stat_history tabeli struktuur

                                          Tabel "public.pg_stat_history"
       Veerg        |            TĂŒĂŒp             |                          Muutujad
---------------------+-----------------------------+-------------------------------------------
 id                  | tÀisarv                     | mitte null vaikimisi nextval('pg_stat_history_id_seq'::regclass)
 snapshot_timestamp  | ajatemperatuur ilma ajavööndita |
 database_id         | tÀisarv                     |
 dbid                | oid                         |
 userid              | oid                         |
 queryid             | suur arv                   |
 query               | tekst                       |
 calls               | suur arv                   |
 total_time          | kahekordne tÀpsus          |
 min_time            | kahekordne tÀpsus          |
 max_time            | kahekordne tÀpsus          |
 mean_time           | kahekordne tÀpsus          |
 stddev_time         | kahekordne tÀpsus          |
 rows                | suur arv                   |
 shared_blks_hit     | suur arv                   |
 shared_blks_read    | suur arv                   |
 shared_blks_dirtied | suur arv                   |
 shared_blks_written | suur arv                   |
 local_blks_hit      | suur arv                   |
 local_blks_read     | suur arv                   |
 local_blks_dirtied  | suur arv                   |
 local_blks_written  | suur arv                   |
 temp_blks_read      | suur arv                   |
 temp_blks_written   | suur arv                   |
 blk_read_time       | kahekordne tÀpsus          |
 blk_write_time      | kahekordne tÀpsus          |
 baseline_id         | tÀisarv                     |
Indeksid:
    "pg_stat_history_pkey" PRIIMARNE VÕTI, btree (id)
    "database_idx" btree (database_id)
    "queryid_idx" btree (queryid)
    "snapshot_timestamp_idx" btree (snapshot_timestamp)
VÀlisvÔtmiste piirangud:
    "database_id_fk" VÄLISVÕTI (database_id) VIITAB andmebaas(id) KUSTUTA CASCADE

Nagu nÀha, esitab tabel lihtsalt kumulatiivseid andmeid kuvamisest pg_stat_statements sihtandmebaasis.

Selle tabeli kasutamine on vÀga lihtne

pg_stat_history ja see esindab iga tunni jooksul kogunenud pÀringute tÀitmise statistikat. Iga tunni alguses, pÀrast tabeli tÀitmist, statistika pg_stat_statements nulldatakse abil pg_stat_statements_reset().
MĂ€rkus: statistika kogutakse pĂ€ringute jaoks, mille tĂ€itmise kestus ĂŒletab 1 sekundi.
Tabeli tÀitmine 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 'LOODUS ALLA KASUTATAVAD';
		
		--Ühenda siht DB-ga	  
	    EXECUTE 'SELECT dblink_connect(''LINK1'',''host='||endpoint_rec.host||' dbname='||database_rec.name||' user=USER password=PASSWORD '')';
 
        RAISE NOTICE 'host % ja dbname % ',endpoint_rec.host,database_rec.name;
		RAISE NOTICE 'Loodud snapshoot pg_stat_statements andmebaasi %',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 'Loodud snapshoot pg_stat_statements kysimustega, mille min_time on suurem kui 1000ms';
	
        FOR pg_stat_snapshot IN
          --KÔik kysimused maks_time suurem kui 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;

SeetÔttu, pÀrast teatud perioodi tabelis pg_stat_history on meil tabeli sisu kogum pg_stat_statements sihtandmebaasist.

Tegelikult raportimine

Lihtsate pĂ€ringute abil on vĂ”imalik saada ĂŒsna kasulikke ja huvitavaid aruandeid.

Kogutud andmed mÀÀratud ajavahemiku jooksul

PĂ€ring

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 ;

DB aeg

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

I/O aeg

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

TOP10 SQL koguaegade pÔhjal

PĂ€ring

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 KOKKU EXECUTION AEG
|   #|    queryid|      kutseid|    kutseid %|                kokku_aeg (ms) |  db_time %
+----+-----------+-----------+-----------+--------------------------------+----------
|   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 kokku I/O aeg

PĂ€ring

VALI 
  queryid , 
  SUM(kutseid) AS kutseid ,
  SUM(blk_lugemise_aeg + blk_kirjutamise_aeg)  AS io_aeg
KUST 
  pg_stat_historia
KUS 
  queryid EI OLE NULL JA 
  andmebaasi_id = ANDMEBAASI_ID  JA
  hetk_tempus BETWEEN ALGUS_AEG ja LÕPP_AEG
RÜHMITA QUERYID 
KORDA 3 DESC 
PIIRANG 10
----------------------------------------------------------------------------------------
| TOP10 SQL KOGUSE I/O AEG ASJA
|   #|    queryid|      kutsed|    kutsed %|                   I/O aeg (ms)|db I/O aeg %
+----+-----------+-----------+-----------+--------------------------------+-------------
|   1| 4152624390|          2|     .00001|00:08:31.616(    511616.592 ms.)|        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 maksimaalse tÀitmise aja jÀrgi

PĂ€ring

VALI 
  id NIMETAMISEKS , 
  queryid , 
  snapshot_timestamp ,  
  max_time 
KUSTUTA 
  pg_stat_history 
KUS 
  queryid EI OLE NULL JA 
  database_id = DATABASE_ID  JA
  snapshot_timestamp VAHEMAL BEGIN_TIMEPOINT JA END_TIMEPOINT
KORDA 4 DESC 
PIIRANG 10

-----------------------------------------------------------------------------------------
| TOP10 SQL MAXIMAALNE SOORDEMI AEG
|   #|          snapshot| snapshotID|    queryid|                           max_time (ms)
+----+------------------+-----------+-----------+----------------------------------------
|   1|  05.04.2019 01:03|       4169|  655729273|        00:02:01.869(    121869.981 ms.)
|   2|  04.04.2019 17:00|       4153|  821760255|        00:01:41.570(    101570.841 ms.)
|   3|  04.04.2019 16:00|       4146|  821760255|        00:01:41.570(    101570.841 ms.)
|   4|  04.04.2019 16:00|       4144| 4152624390|        00:01:36.964(     96964.607 ms.)
|   5|  04.04.2019 17:00|       4151| 4152624390|        00:01:36.964(     96964.607 ms.)
|   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 ms.)
|   8|  04.04.2019 15:00|       4140| 1484454471|        00:00:11.892(     11892.302 ms.)
|   9|  04.04.2019 16:00|       4145| 1484454471|        00:00:11.892(     11892.302 ms.)
|  10|  04.04.2019 17:00|       4152| 1484454471|        00:00:11.892(     11892.302 ms.)

TOP10 SQL jagatud puhvri lugemine/kirjutamine

PĂ€ring

VALI 
  id AS snapshotid , 
  queryid ,
  snapshot_timestamp , 
  shared_blks_read , 
  shared_blks_written 
KUST 
  pg_stat_history
KUS 
  queryid EI OLE NULL JA 
  database_id = DATABASE_ID  JA
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT JA END_TIMEPOINT JA
  ( shared_blks_read > 0 VÕI shared_blks_written > 0 )
KORDA 4 ALLA  , 5 ALLA 
PIIRA 10
--------------------------------------------------------------------------------------------
| TOP10 SQL ÖHIKUDE JAGAMISSE PÄRAST LOETLETUD BLOKKE
|   #|          hetkepilt| hetkepildi ID|    pÀringu ID|   jagatud blokeeritud lugemine|  jagatud blokeeritud kirjutamine
+----+------------------+-----------+-----------+---------------------+---------------------
|   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
--------------------------------------------------------------------------------------------

PÀringute jaotumise histogramm maksimaalse tÀitmise aja jÀrgi

PĂ€ringud

VALI  
  MIN(max_time) AS hist_min  , 
  MAX(max_time) AS hist_max , 
  (( MAX(max_time) - MIN(min_time) ) / hist_columns ) AS hist_width
KUSTA  
  pg_stat_history 
KUS  
  queryid EI OLE NULL JA
  database_id = DATABASE_ID  JA
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT JA END_TIMEPOINT ;

VALI  
  SUM(calls) AS calls
KUSTA  
  pg_stat_history 
KUS  
  queryid EI OLE NULL JA
  database_id = DATABASE_ID  JA
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT JA END_TIMEPOINT JA 
  ( max_time >= hist_current_min JA  max_time < hist_current_max ) ;
|-----------------------------------------------------------------------------------------------
| MAX_TIME HISTOGRAM
| KOKKU KÕNE : 33851920
| MIN AEG  : 00:00:01.063
| MAX AEG  : 00:02:01.869
---------------------------------------------------------------------------------
|                      min kestus|                      max kestus|     kÔned
+----------------------------------+----------------------------------+----------
| 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

TOP10 KOHANDUSED PÄEVAKÜSIMUSI

PĂ€ringud

--pg_qps.sql
--KĂŒsimuste arv sekundis
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 'VIGA - pole leidnud pg_stat_history id-ga = %',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  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
|-----------------------------------------------------------------------------------------------
| TOP10 Snapshots tellitud QPS numbrite jÀrgi
-----------------------------------------------------------------------------------------------------------------------------------------------
|    #|          snapshot| snapshotID|      calls|                      total dbtime|        QPS|                          I/O aeg| I/O aeg %
+-----+------------------+-----------+-----------+----------------------------------+-----------+----------------------------------+-----------
|    1|  04.04.2019 20:04|       4161|    5758631|  00:06:30.513(    390513.926 ms.)|   1573.396|  00:00:01.470(      1470.110 ms.)|       .376
|    2|  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
|    3|  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
|    4|  04.04.2019 21:03|       4163|    2781536|  00:03:06.470(    186470.979 ms.)|    785.745|  00:00:00.249(       249.865 ms.)|       .134
|    5|  04.04.2019 19:03|       4159|    2890362|  00:03:16.784(    196784.755 ms.)|    776.979|  00:00:01.441(      1441.386 ms.)|       .732
|    6|  04.04.2019 14:00|       4137|    2397326|  00:04:43.033(    283033.854 ms.)|    665.924|  00:00:00.024(        24.505 ms.)|       .009
|    7|  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
|    8|  04.04.2019 13:00|       4135|    2373043|  00:04:26.791(    266791.988 ms.)|    659.179|  00:00:00.064(        64.261 ms.)|       .024
|    9|  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
|   10|  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

Tunnine tÀitmise ajalugu QueryPerSeconds ja I/O aja jÀrgi

PĂ€ring

VALI 
  id , 
  snapshot_timestamp ,
  calls , 	
  total_time , 
  ( vali pg_qps( id )) KPS ,
  blk_read_time ,
  blk_write_time
KUST 
  pg_stat_history
KUS 
  queryid ON NULL JA 
  database_id = DATABASE_ID  JA
  snapshot_timestamp BETWEEN BEGIN_TIMEPOINT JA END_TIMEPOINT
KORDA 2
|-----------------------------------------------------------------------------------------------
| TUNNID AJAOTAMISE AJALUGU QueryPerSeconds ja I/O Aega
-----------------------------------------------------------------------------------------------------------------------------------------------
| KÜSIMUS PER SEKUND AJALUGU
|    #|          hetk| hetkID|      kÔned|                      koguaeg|        QPS|                          I/O aeg| I/O aja %
+-----+------------------+-----------+-----------+----------------------------------+-----------+----------------------------------+-----------
|    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

KÔik SQL-valikute tekst

PĂ€ring

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

KokkuvÔte

Nagu nĂ€ha, on ĂŒsna lihtsate vahenditega vĂ”imalik saada palju kasulikku teavet andmebaasi koormusest ja olekust.

MÀrkus:Kui pÀringutes fikseerida queryid, saame ajaloo iga pÀringu kohta (ruumi sÀÀstmise eesmÀrgil on eraldi pÀringu kohta aruanded vahele jÀetud).

Nii et pÀringu tulemuslikkuse statistika on olemas ja kogutakse.
Esimene etapp 'statistika kogumine' on lÔpetatud.

Saame liikuda teise etapi, 'tulemuse mÔÔdikute seadistamise' juurde.
PostgreSQL pĂ€ringute tulemuslikkuse jĂ€lgimine. Osa 1 — aruandlus

Aga see on juba hoopis teine lugu.

JĂ€tkub


Allikas: habr.com

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