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PostgreSQL pĂ€ringute jĂ”udluse jĂ€lgimine. 1. osa – aruandlus

Insener – ladina keelest tĂ”lgitud – inspireeritud.
Insener vÔib kÔike teha. c) R. Diesel.
Epigraafid.
PostgreSQL pĂ€ringute jĂ”udluse jĂ€lgimine. 1. osa – aruandlus
VÔi lugu sellest, miks andmebaasi administraator peab oma programmeerimise minevikku meeles pidama.

EessÔna

KÔik nimed on muudetud. MÀngud on juhuslikud. Materjal on ainult autori isiklik arvamus.

Garantiidest loobumine: kavandatavas artiklisarjas ei ole kasutatud tabelite ja skriptide ĂŒksikasjalikku ja tĂ€pset kirjeldust. Materjale ei saa kohe "NAGU ON" kasutada.
Esiteks, materjali suure hulga tÔttu
teiseks teravuse tÔttu reaalse kliendi tootmisbaasiga.
SeetĂ”ttu antakse artiklites ainult ideid ja kirjeldusi kĂ”ige ĂŒldisemal kujul.
VĂ”ib-olla kasvab sĂŒsteem tulevikus GitHubis postitamise tasemele vĂ”i vĂ”ib-olla mitte. Eks aeg nĂ€itab.

Loo algus -Kas mÀletate, kuidas see kÔik algas'.
Mis selle tulemusena juhtus, kĂ”ige ĂŒldisemalt öeldes - "SĂŒntees kui ĂŒks PostgreSQL-i jĂ”udluse parandamise meetodeid»

Miks mul seda kÔike vaja on?

Noh, esiteks, et mitte unustada ennast, meenutades kuulsusrikkaid pÀevi pensionil.
Teiseks kirjutatu sĂŒstematiseerimine. Juba enda jaoks hakkan vahel segadusse minema ja eraldi osad unustama.

No ja mis kĂ”ige tĂ€htsam – Ă€kki vĂ”ib see kellelegi kasuks tulla ja aidata jalgratast mitte uuesti leiutada ja reha mitte koguda. TeisisĂ”nu parandage oma karmat (mitte Habrovski). Sest kĂ”ige vÀÀrtuslikum asi siin maailmas on ideed. Peaasi on idee leida. Ja idee ellu viimine on juba puhtalt tehniline kĂŒsimus.

Alustame siis aeglaselt...

Probleemi sÔnastamine.

Saadaval:

PostgreSQL (10.5), segakoormus (OLTP+DSS), keskmine kuni kerge koormus, hostitud AWS-i pilves.
Andmebaasi jÀlgimine puudub, infrastruktuuri jÀlgimine on esitatud standardsete AWS-i tööriistadena minimaalses konfiguratsioonis.

NÔutav:

JÀlgige andmebaasi jÔudlust ja olekut, leidke ja omage algteavet raskete andmebaasipÀringute optimeerimiseks.

Lahenduste lĂŒhitutvustus vĂ”i analĂŒĂŒs

Alustuseks proovime analĂŒĂŒsida probleemi lahendamise vĂ”imalusi inseneri eeliste ja probleemide vĂ”rdleva analĂŒĂŒsi vaatenurgast ning laske kasude ja kahjudega tegeleda neil, kes peaksid olema töötajate nimekirjas. juhtimisest.

1. valik – „Töötamine nĂ”udmisel”

JÀtame kÔik nii nagu on. Kui klient pole millegagi andmebaasi vÔi rakenduse töös, töökorras rahul, teavitab ta DBA insenere e-posti teel vÔi loob piletikasti intsidendi.
Teate saanud insener saab probleemist aru, pakub lahenduse vÔi jÀtab probleemi riiulile, lootes, et kÔik laheneb iseenesest ja niikuinii unustatakse varsti kÔik.
Piparkoogid ja sÔÔrikud, sinikad ja punnidPiparkoogid ja sÔÔrikud:
1. Midagi ekstra teha
2. Alati on vÔimalus vÀlja tulla ja end mÀÀrida.
3. Palju aega, mida saad veeta omaette.
Verevalumid ja muhud:
1. Varem vĂ”i hiljem hakkab klient mĂ”tlema olemise ja universaalse Ă”igluse olemuse ĂŒle siin maailmas ning esitab endale veel kord kĂŒsimuse – miks ma neile oma raha maksan? TagajĂ€rg on alati sama – kĂŒsimus on vaid selles, millal kliendil hakkab igav ja ta lehvitab hĂŒvastijĂ€tuks. Ja söötja on tĂŒhi. See on kurb.
2. Inseneri areng on null.
3. Raskused töö ja laadimise ajakava koostamisel

Valik 2 - "Tantsi parmupillidega, pange jalga ja pange kingad jalga"

LĂ”ige 1-Miks meil on vaja seiresĂŒsteemi, saame kĂ”ik taotlused vastu. KĂ€ivitame hunniku kĂ”ikvĂ”imalikke pĂ€ringuid andmesĂ”naraamatusse ja dĂŒnaamilistesse vaadetesse, lĂŒlitame sisse kĂ”ikvĂ”imalikud loendurid, toome kĂ”ik tabelitesse, analĂŒĂŒsime perioodiliselt justkui loendeid ja tabeleid. Selle tulemusena on meil ilusad vĂ”i mitte vĂ€ga graafikud, tabelid, aruanded. Peaasi – et oleks rohkem, rohkem.
LĂ”ige 2- Looge tegevus - kĂ€ivitage selle kĂ”ige analĂŒĂŒs.
LÔige 3-Me valmistame ette teatud dokumenti, me nimetame seda dokumenti lihtsalt - "kuidas me andmebaasi varustame."
LĂ”ige 4- Klient, nĂ€hes kogu seda graafikute ja jooniste suurepĂ€rasust, on lapselikult naiivses enesekindluses - nĂŒĂŒd hakkab kĂ”ik meie heaks varsti toimima. Ja lihtsalt ja valutult jagage oma rahalisi vahendeid. Juhtkond on samuti kindel, et meie insenerid teevad kĂ”vasti tööd. Maksimaalne laadimine.
LÔige 5- Korrake 1. sammu regulaarselt.
Piparkoogid ja sÔÔrikud, sinikad ja punnidPiparkoogid ja sÔÔrikud:
1. Juhtide ja inseneride elu on lihtne, etteaimatav ja tegevust tÀis. KÔik sumiseb, kÔik on hÔivatud.
2. Kliendi elu pole ka halb - ta on alati kindel, et pead veidi kannatust varuma ja kÔik saab korda. Ei parane, noh, hÀsti - see maailm on ebaÔiglane, jÀrgmises elus - Ônne.
Verevalumid ja muhud:
1. Varem vÔi hiljem leidub targem sarnase teenuse pakkuja, kes teeb sama asja, kuid veidi odavamalt. Ja kui tulemus on sama, miks siis rohkem maksta. Mis jÀllegi toob kaasa sööturi kadumise.
2. See on igav. Kui igav on igasugune vÀike mÔtestatud tegevus.
3. Nagu eelmises versioonis - arendus puudub. Kuid inseneri jaoks on miinus see, et erinevalt esimesest vĂ”imalusest peate siin pidevalt IDB-d genereerima. Ja see vĂ”tab aega. Mille saab kulutada oma kallima hĂŒvanguks. Sest sa ei saa enda eest hoolitseda, kĂ”ik hoolivad sinust.

Valik 3 – Jalgratast pole vaja leiutada, see tuleb osta ja sellega sĂ”ita.

Teiste firmade insenerid söövad teadlikult pitsat Ă”llega (oh, 90ndate Peterburi kuulsusrikas aeg). Kasutame seiresĂŒsteeme, mis on tehtud, silutud ja töökorras ning ĂŒldiselt öeldes toovad need kasu (noh, vĂ€hemalt nende loojatele).
Piparkoogid ja sÔÔrikud, sinikad ja punnidPiparkoogid ja sÔÔrikud:
1. Pole vaja raisata aega juba leiutatu vÀljamÔtlemisele. VÔtke ja kasutage.
2. SeiresĂŒsteeme ei kirjuta lollid ja loomulikult on need kasulikud.
3. Töötavad seiresĂŒsteemid pakuvad tavaliselt kasulikku filtreeritud teavet.
Verevalumid ja muhud:
1. Insener ei ole antud juhul insener, vaid lihtsalt kellegi teise toote kasutaja vÔi kasutaja.
2. Klient peab olema veendunud, et on vaja osta midagi, millest ta ĂŒldiselt ei taha aru saada ja ei peakski ning ĂŒldiselt on aasta eelarve kinnitatud ja see ei muutu. SeejĂ€rel peate eraldama eraldi ressursi, konfigureerima selle konkreetse sĂŒsteemi jaoks. Need. KĂ”igepealt pead maksma, maksma ja veel kord maksma. Ja klient on ihne. See on selle elu norm.

Mida teha, TĆĄernÔƥevski? Teie kĂŒsimus on vĂ€ga asjakohane. (koos)

Sel konkreetsel juhul ja praeguses olukorras saate teha veidi teisiti - teeme oma jĂ€lgimissĂŒsteemi.
PostgreSQL pĂ€ringute jĂ”udluse jĂ€lgimine. 1. osa – aruandlus
Noh, muidugi mitte sĂŒsteem, selle sĂ”na tĂ€ies tĂ€henduses, see on liiga vali ja ĂŒlemeelik, aga tee vĂ€hemalt kuidagi enda jaoks lihtsamaks ja kogub rohkem infot esinemisintsidentide lahendamiseks. Et mitte sattuda olukorda - "mine sinna, ma ei tea, kust, leidke see, ma ei tea mis."

Millised on selle valiku plussid ja miinused:

plussid:
1. See on huvitav. Noh, vÀhemalt huvitavam kui pidev "andmefaili kokkutÔmbamine, tabeliruumi muutmine jne."
2. Need on uued oskused ja uus areng. Mis tulevikus annab varem vÔi hiljem vÀljateenitud piparkooke ja sÔÔrikuid.
miinuseid:
1. Peab töötama. Töötage palju.
2. Peate regulaarselt selgitama kogu tegevuse tÀhendust ja perspektiive.
3. Midagi tuleb ohverdada, sest ainsat inseneri kĂ€sutuses olevat ressurssi – aega – piirab Universum.
4. KĂ”ige hullem ja ebameeldivam - selle tulemusena vĂ”ib vĂ€lja tulla prĂŒgi nagu "Mitte hiir, mitte konn, vaid tundmatu vĂ€ike loom".

Kes millegagi ei riski, see ĆĄampanjat ei joo.
Niisiis, lÔbus algab.

Üldine idee - skemaatiline

PostgreSQL pĂ€ringute jĂ”udluse jĂ€lgimine. 1. osa – aruandlus
(Illustratsioon vĂ”etud artiklist «SĂŒntees kui ĂŒks PostgreSQL-i jĂ”udluse parandamise meetodeid»)

Selgitus:

  • Sihtandmebaas on installitud standardse PostgreSQL-laiendiga "pg_stat_statements".
  • JĂ€lgimisandmebaasis loome teenusetabelite komplekti, et salvestada algetapis pg_stat_statements ajalugu ning edaspidi konfigureerida mÔÔdikuid ja jĂ€lgimist
  • JĂ€lgimishostis loome bash-skriptide komplekti, sealhulgas need, mis on ette nĂ€htud piletisĂŒsteemis vahejuhtumite genereerimiseks.

Teeninduslauad

Alustuseks skemaatiliselt lihtsustatud ERD, mis lÔpuks juhtus:
PostgreSQL pĂ€ringute jĂ”udluse jĂ€lgimine. 1. osa – aruandlus
Tabelite lĂŒhikirjeldustulemusnĂ€itaja - host, ĂŒhenduspunkt eksemplariga
andmebaas - andmebaasi valikud
pg_stat_history - ajalooline tabel sihtandmebaasi vaate pg_stat_statements ajutiste hetktÔmmiste salvestamiseks
meetriline_sÔnastik - jÔudlusmÔÔdikute sÔnastik
metric_config - ĂŒksikute mÔÔdikute konfigureerimine
meetriline - jÀlgitava pÀringu konkreetne mÔÔdik
metric_alert_history - jÔudlushoiatuste ajalugu
logi_pÀring - hooldustabel AWS-ist alla laaditud PostgreSQL-i logifaili parsitud kirjete salvestamiseks
algtaseme - aluseks vÔetud ajaperioodi parameetrid
kontrollpunkt - mÔÔdikute konfigureerimine andmebaasi oleku kontrollimiseks
checkpoint_alert_history - andmebaasi oleku kontrolli mÔÔdikute hoiatusajalugu
pg_stat_db_queries — aktiivsete pĂ€ringute teenindustabel
aktiivsus Logi — tegevuste logi teenindustabel
trap_oid - pĂŒĂŒnise konfiguratsiooni teenindustabel

1. etapp – koguge toimivusstatistikat ja hankige aruandeid

Statistilise teabe salvestamiseks kasutatakse tabelit. pg_stat_history
pg_stat_history tabeli struktuur

                                          Tabel "public.pg_stat_history" Veerg | tĂŒĂŒp | Modifikaatorid--------------------+--------------------- --+----- -------------------------------- id | tĂ€isarv | not null vaikimisi nextval('pg_stat_history_id_seq'::regclass) snapshot_timestamp | ajatempel ilma ajavööndita | andmebaasi_id | tĂ€isarv | dbid | oid | kasutajatunnus | oid | queryid | bigint | pĂ€ring | tekst | kĂ”ned | bigint | kokku_aeg | topelttĂ€psus | min_aeg | topelttĂ€psus | max_time | topelttĂ€psus | keskmine_aeg | topelttĂ€psus | stddev_time | topelttĂ€psus | rida | bigint | shared_blks_hit | bigint | shared_blks_read | bigint | shared_blks_dirtied | bigint | jagatud_blks_kirjutatud | 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 | topelttĂ€psus | blk_write_time | topelttĂ€psus | baasjoone_id | tĂ€isarv | Indeksid: "pg_stat_history_pkey" PRIMARY KEY, btree (id) "database_idx" btree (andmebaase_id) "queryid_idx" btree (queryid) "snapshot_timestamp_idx" btree (snapshot_timestamp) Fight_key KEY_tabstraase id) VIITED andmebaas(id ) KUSTUTUSKASKAD

Nagu nÀete, on tabel vaid kumulatiivsed vaateandmed pg_stat_statements sihtandmebaasis.

Selle tabeli kasutamine on vÀga lihtne.

pg_stat_history tÀhistab pÀringu tÀitmise akumuleeritud statistikat iga tunni kohta. Iga tunni alguses peale tabeli tÀitmist statistika pg_stat_statements lÀhtestada koos pg_stat_statements_reset().
MĂ€rkus: statistikat kogutakse pĂ€ringute kohta, mille kestus on ĂŒle 1 sekundi.
Tabeli pg_stat_history tÀitmine

--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;

Selle tulemusena pÀrast teatud ajaperioodi tabelis pg_stat_history meil on tabeli sisu hetktÔmmised pg_stat_statements sihtandmebaas.

Tegelikult aruandlus

Lihtsate pĂ€ringute abil saate ĂŒsna kasulikke ja huvitavaid aruandeid.

Teatud ajaperioodi koondandmed

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 ;

D.B. aeg

to_char(intervall '1 millisekund' * pg_total_stat_history_rec.total_time, 'HH24:MI:SS.MS')

I/O aeg

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

TOP10 SQL-i total_time jÀrgi

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-i KOKKU TÄITMISAJA JÄRGI | #| queryid| kĂ”ned| kĂ”ned %| kokku_aeg (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-i kogu I/O aja jÀrgi

PĂ€ring

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-i KOKKU I/O AJA JÄRGI | #| queryid| kĂ”ned| kĂ”ned %| I/O aeg (ms)|db I/O aeg % +----+-----------+-----------+------- -----+--------------------------------+------------ -- | 1| 4152624390| 2| .00001|00:08:31.616( 511616.592 ms.)| 31.06. juuni | 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 tÀitmisaja jÀrgi

PĂ€ring

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-i MAX TÄITMISAJA POOLT | #| hetktĂ”mmis| snapshotID| queryid| 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 ms.) | 8| 04.04.2019/15/00 4140:1484454471| 00| 00| 11.892:11892.302:9( 04.04.2019 ms.) | 16| 00/4145/1484454471 00:00| 11.892| 11892.302| 10:04.04.2019:17( 00 ms.) | 4152| 1484454471/00/00 11.892:11892.302| XNUMX| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.) | XNUMX| XNUMX/XNUMX/XNUMX XNUMX:XNUMX| XNUMX| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.)

TOP10 SQL JAGATUD puhvri lugemine/kirjutamine

PĂ€ring

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-i JAGATUD PUHVRIGA LUGEGE/KIRJUTAMINE | #| hetktÔmmis| snapshotID| queryid| jagatud plokid loe| jagatud plokid kirjuta +----+------------------+------------+----------- -+---------------------+---------------------- | 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 -------------------------------------------------- -------------------------------------------------

PÀringu jaotuse histogramm maksimaalse tÀitmisaja jÀrgi

taotlused

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 | KÕNED KOKKU : 33851920 | MIN AEG : 00:00:01.063 | MAX AEG: 00:02:01.869 --------------------------------- --------- ----------------------------- | min kestus| max kestus| helistab +-----------------------------------+-------------- ---------------------+----------- | 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 hetktÔmmist pÀringu jÀrgi sekundis

taotlused

--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

|-------------------------------------------------- ----------------------------------------- | TOP10 hetktÔmmist QueryPerSeconds numbrite jÀrgi -------------------------------------- ------ -------------------------------------------- ------ -------------------------------------------- | #| hetktÔmmis| snapshotID| kÔned| kogu dbtime| QPS | I/O aeg | I/O aeg % +-----+-------------------+------------+-------- ----+-----------------------------------+----------- -+----------------------------------+------------ | 1| 04.04.2019/20/04 4161:5758631| 00| 06| 30.513:390513.926:1573.396( 00 ms.)| 00| 01.470:1470.110:376( 2 ms.)| .04.04.2019 | 17| 00/4149/3529197 00:11| 48.830| 708830.618| 980.332:00:12( 47.834 ms.)| 767834.052| 108.324:3:04.04.2019( 16 ms.)| 00 | 4143| 3525360/00/10 13.492:613492.351| 979.267| 00| 08:41.396:521396.555( 84.988 ms.)| 4| 04.04.2019:21:03( 4163 ms.)| 2781536 | 00| 03/06.470/186470.979 785.745:00| 00| 00.249| 249.865:134:5( 04.04.2019 ms.)| 19| 03:4159:2890362( 00 ms.)| .03 | 16.784| 196784.755/776.979/00 00:01.441| 1441.386| 732| 6:04.04.2019:14( 00 ms.)| 4137| 2397326:00:04( 43.033 ms.)| .283033.854 | 665.924| 00 00:00.024 | 24.505| 009| 7:04.04.2019:15( 00 ms.)| 4139| 2394416:00:04( 51.435 ms.)| .291435.010 | 665.116| 00/00/12.025 12025.895:4.126| 8| 04.04.2019| 13:00:4135( 2373043 ms.)| 00| 04:26.791:266791.988( 659.179 ms.)| 00 | 00| 00.064 64.261:024 | 9| 05.04.2019| 01:03:4167( 4387191 ms.)| 00| 06:51.380:411380.293( 609.332 ms.)| .00 | 05| 18.847/318847.407/77.507 10:04.04.2019| 18| 01| 4157:1145596:00( 01 ms.)| 19.217| 79217.372:313.004:00( 00 ms.)| 01.319 | 1319.676| 1.666/XNUMX/XNUMX XNUMX:XNUMX| XNUMX| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.)| XNUMX| XNUMX:XNUMX:XNUMX( XNUMX ms.)| XNUMX

TunnipÔhine tÀitmisajalugu koos QueryPerSecondsi ja I/O-ajaga

PĂ€ring

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

KÔikide SQL-i 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

Summaarne

Nagu nĂ€ete, saate ĂŒsna lihtsate vahenditega palju kasulikku teavet töökoormuse ja andmebaasi oleku kohta.

MÀrge:Kui parandate pÀringutes queryid, siis saame ajaloo eraldi pÀringu jaoks (ruumi sÀÀstmiseks jÀetakse eraldi pÀringu aruanded vÀlja).

Seega on statistilised andmed pÀringu toimivuse kohta saadaval ja kogutud.
Esimene etapp "statistiliste andmete kogumine" on lÔppenud.

VÔite jÀtkata teise etapiga - "jÔudlusmÔÔdikute konfigureerimine".
PostgreSQL pĂ€ringute jĂ”udluse jĂ€lgimine. 1. osa – aruandlus

Kuid see on tÀiesti erinev lugu.

JĂ€tkub ...

Allikas: www.habr.com

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