{"id":93138,"date":"2020-09-03T01:42:51","date_gmt":"2020-09-02T23:42:51","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/awr-naskolko-ekzadatitsya-rabota-bazy-dannyh"},"modified":"2020-09-03T01:42:51","modified_gmt":"2020-09-02T23:42:51","slug":"awr-naskolko-ekzadatitsya-rabota-bazy-dannyh","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/administrirovanie\/awr-naskolko-ekzadatitsya-rabota-bazy-dannyh","title":{"rendered":"AWR: kui kaua \"ekskaditsioon\" toimub andmebaasi t\u00f6\u00f6s?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Selles v\u00e4ikeses postituses tahaksin hajutada \u00fche arusaamatuse, mis on seotud AWR andmebaaside anal\u00fc\u00fcsiga, mis t\u00f6\u00f6tavad Oracle Exadata. Peaaegu 10 aastat olen pidevalt kokku puutunud k\u00fcsimusega: milline on Exadata tarkvara panus j\u00f5udlusesse? V\u00f5i uute s\u00f5nade kasutamisel: kui palju \u201eekzadateeritakse\u201d selle v\u00f5i teise andmebaasi t\u00f6\u00f6d?<\/p>\n

\"AWR:<\/p>\n

Sageli antakse sellele \u00f5igustatud k\u00fcsimusele, minu arvates, vale vastus, viidates AWR statistikale. Selles esitatakse s\u00fcsteemi ootuste meetod, mis t\u00f5lgendab reageerimisaega protsessorite t\u00f6\u00f6aja (DB CPU) ja erinevate klasside ooteaegade summana.<\/p>\n

Exadata tulekuga on AWR statistikasse ilmunud spetsiifilised s\u00fcsteemi ootused, mis on seotud Exadata tarkvara toimimisega. Reeglina algavad selliste ootuste nimetused s\u00f5naga \"cell\" (Exadata salvestusseadme nimetatakse \u201erakuks\u201d), k\u00f5ige sagedamini esinevad ootused, mis kannavad k\u00f5nekaid nimesid nagu \"cell smart table scan\", \"cell multiblock physical read\" ja \"cell single block physical read\".<\/p>\n

Enamikul juhtudel on Exadata ooteaja osa koguvastusest v\u00e4ike, mist\u00f5ttu nad ei satu isegi jaotisse Top10 Esmased \u00dcritused Kogunemise Aja J\u00e4rgi (selles osas tuleks neid otsida Foreground Wait Events alt). Me oleme suure vaeva n\u00e4gemisega leidnud meie klientide seas n\u00e4ite \u00f6isest AWR-ist, kus Exadata ooteajad p\u00e4\u00e4sesid Top10 sektsiooni ja nende kogusumma ulatus umbes 5%-ni:<\/p>\n

\u00dcritus<\/strong><\/p>\n

Ootamised<\/strong><\/p>\n

Koguaeg Ooteaja J\u00e4rgi (sekundites)<\/strong><\/p>\n

Keskmine Ootus<\/strong><\/p>\n

% DB aega<\/strong><\/p>\n

Oote Kategooria<\/strong><\/p>\n

DB CPU<\/p>\n

<\/p>\n

115.2K<\/p>\n

<\/p>\n

70.4<\/p>\n

<\/p>\n

SQL*Net rohkem andmeid dblinkilt<\/p>\n

670,196<\/p>\n

5471.5<\/p>\n

8.16ms<\/p>\n

3.3<\/p>\n

V\u00f5rk\n log \/dev\/log local0\n log \/dev\/log local1 notice\n chroot \/var\/lib\/haproxy\n stats timeout 30s\n user haproxy\n group haproxy\n daemon\n\ndefaults\n log global\n mode http\n option httplog\n option dontlognull\n timeout connect 5000\n timeout client 50000\n timeout server 50000\n\nfrontend http_front\n bind *:80\n stats uri \/haproxy?stats\n default_backend http_back\n\nbackend http_back\n balance roundrobin\n server server_name1 private_ip1:80 check\n server server_name2 private_ip2:80 check<\/p>\n

cell \u00fcksiku ploki f\u00fc\u00fcsiline lugemine<\/p>\n

5,661,452<\/p>\n

3827.6<\/p>\n

676.07us<\/p>\n

2.3<\/p>\n

Kasutaja I\/O<\/p>\n

Sync ASM tasakaalu reguleerimine<\/p>\n

4,350,012<\/p>\n

3481.3<\/p>\n

800.30us<\/p>\n

2.1<\/p>\n

Muu<\/p>\n

cell mitme ploki f\u00fc\u00fcsiline lugemine<\/p>\n

759,885<\/p>\n

2252<\/p>\n

2.96ms<\/p>\n

1.4<\/p>\n

Kasutaja I\/O<\/p>\n

otsene tee lugemine<\/p>\n

374,368<\/p>\n

1811.3<\/p>\n

4.84ms<\/p>\n

1.1<\/p>\n

Kasutaja I\/O<\/p>\n

SQL*Net s\u00f5num dblinkilt<\/p>\n

7,983<\/p>\n

1725<\/p>\n

216.08ms<\/p>\n

1.1<\/p>\n

V\u00f5rk\n log \/dev\/log local0\n log \/dev\/log local1 notice\n chroot \/var\/lib\/haproxy\n stats timeout 30s\n user haproxy\n group haproxy\n daemon\n\ndefaults\n log global\n mode http\n option httplog\n option dontlognull\n timeout connect 5000\n timeout client 50000\n timeout server 50000\n\nfrontend http_front\n bind *:80\n stats uri \/haproxy?stats\n default_backend http_back\n\nbackend http_back\n balance roundrobin\n server server_name1 private_ip1:80 check\n server server_name2 private_ip2:80 check<\/p>\n

cell nutikas tabeli skaneerimine<\/p>\n

1,007,520<\/p>\n

1260.7<\/p>\n

1.25ms<\/p>\n

0.8<\/p>\n

Kasutaja I\/O<\/p>\n

otsene tee lugemine temp<\/p>\n

520,211<\/p>\n

808.4<\/p>\n

1.55ms<\/p>\n

0.5<\/p>\n

Kasutaja I\/O<\/p>\n

enq: TM — contention<\/p>\n

652<\/p>\n

795.8<\/p>\n

1220.55ms<\/p>\n

0.5<\/p>\n

Application<\/p>\n

Sellest AWR statistikast tehakse sageli j\u00e4rgmised j\u00e4reldused:<\/p>\n

1. \u0412\u043a\u043b\u0430\u0434 \u043c\u0430\u0433\u0438\u0438 Exadata \u0432 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c \u0431\u0430\u0437\u044b \u0434\u0430\u043d\u043d\u044b\u0445 \u043d\u0435 \u0432\u044b\u0441\u043e\u043a \u2014 \u043d\u0435 \u043f\u0440\u0435\u0432\u044b\u0448\u0430\u0435\u0442 5 %, \u0430 \u0431\u0430\u0437\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u00ab\u044d\u043a\u0437\u0430\u0434\u0430\u0442\u0438\u0442\u0441\u044f\u00bb \u043f\u043b\u043e\u0445\u043e.<\/p>\n

2. \u0415\u0441\u043b\u0438 \u0442\u0430\u043a\u0443\u044e \u0431\u0430\u0437\u0443 \u043f\u0435\u0440\u0435\u043d\u0435\u0441\u0442\u0438 \u0441 Exadata \u043d\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0447\u0435\u0441\u043a\u0443\u044e \u0430\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u0443 \u00ab\u0441\u0435\u0440\u0432\u0435\u0440 + \u043c\u0430\u0441\u0441\u0438\u0432\u00bb, \u0442\u043e \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c \u0438\u0437\u043c\u0435\u043d\u0438\u0442\u0441\u044f \u043d\u0435 \u0441\u0438\u043b\u044c\u043d\u043e. \u041f\u043e\u0442\u043e\u043c\u0443 \u0447\u0442\u043e \u0434\u0430\u0436\u0435 \u0435\u0441\u043b\u0438 \u044d\u0442\u043e\u0442 \u043c\u0430\u0441\u0441\u0438\u0432 \u043e\u043a\u0430\u0436\u0435\u0442\u0441\u044f \u0432\u0442\u0440\u043e\u0435 \u043c\u0435\u0434\u043b\u0435\u043d\u043d\u0435\u0435 \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f Exadata (\u0447\u0442\u043e \u0435\u0434\u0432\u0430 \u043b\u0438 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e \u0434\u043b\u044f \u0441\u043e\u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445 All Flash \u043c\u0430\u0441\u0441\u0438\u0432\u043e\u0432), \u0442\u043e \u0443\u043c\u043d\u043e\u0436\u0438\u0432 5% \u043d\u0430 \u0442\u0440\u0438 \u043c\u044b \u043f\u043e\u043b\u0443\u0447\u0438\u043c \u0443\u0432\u0435\u043b\u0438\u0447\u0435\u043d\u0438\u0435 \u0434\u043e\u043b\u0438 \u043e\u0436\u0438\u0434\u0430\u043d\u0438\u0439 \u0432\u0432\u043e\u0434\u0430-\u0432\u044b\u0432\u043e\u0434\u0430 \u0434\u043e 15% \u00ad\u2014 \u0442\u0430\u043a\u043e\u0435 \u0431\u0430\u0437\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u043d\u0430\u0432\u0435\u0440\u043d\u044f\u043a\u0430 \u043f\u0435\u0440\u0435\u0436\u0438\u0432\u0435\u0442!<\/p>\n

M\u00f5lemad need j\u00e4reldused on ebat\u00e4psed, veelgi enam, need moonutavad arusaama Exadata tarkvara ideest. Exadata ei paku mitte ainult kiiret IO-d, vaid toimib p\u00f5him\u00f5tteliselt t\u00e4iesti erinevalt v\u00f5rreldes klassikalise arhitektuuriga \u00abserver + salvestus\u00bb. Kui andmebaas t\u00f5eliselt \u00abexadatiseerub\u00bb \u2014 siis kantakse SQL-loogika salvestusseadmest. Storage serverid<\/a> t\u00e4nu rida spetsiaalsetele mehhanismidele (eelk\u00f5ige Exadata salvestuse indeksid, kuid mitte ainult) leiavad nad vajalikud andmed ja edastavad need DB serveritele. Nad suudavad seda teha piisavalt t\u00f5husalt, seega on Exadata iseloomulike ootuste osakaal \u00fcldises vastuse ajas v\u00e4ike. <\/p>\n

Kuidas see osa Exadata-st v\u00e4ljaspool muutub? Kuidas see m\u00f5jutab kogu andmebaasi j\u00f5udlust? Parimad vastused nendele k\u00fcsimustele annab testimine. N\u00e4iteks v\u00e4line ootus 'cell smart table scan' v\u00f5ib muutuda nii raskeks table full scan'iks, et sisendi ja v\u00e4ljundi t\u00f6\u00f6tlemine v\u00f5tab kogu reageerimisaega ja j\u00f5udlus halveneb dramaatiliselt. Just seet\u00f5ttu on vale anal\u00fc\u00fcsida AWR-i andmeid, pidades Exadata oote kogusummat kui osa selle maagilisest j\u00f5udlusest ning kindlasti ei tohiks seda protsenti kasutada j\u00f5udluse prognoosimiseks v\u00e4ljaspool Exadata. Et m\u00f5ista, kui palju on andmebaas 'ekzadatiseeritud', tuleb uurida AWR-i sektsiooni 'Instance Activity Stats' statistikat (seal on palju statistikat k\u00f5nekate nimedega) ja v\u00f5rrelda neid omavahel.<\/p>\n

Ja et m\u00f5ista, kuidas andmebaas v\u00e4ljaspool Exadata ennast tunneb, on k\u00f5ige parem luua varukoopiast klon sihtarhitektuuril ja anal\u00fc\u00fcsida selle kloni j\u00f5udlust koormuse all. Selline v\u00f5imalus on Exadata omanikel tavaliselt olemas.<\/p>\n

Autor: Aleks\u00e9i Strut\u0161enko, andmebaaside valdkonna juht 'Infos\u00fcsteemid Jet'<\/em><\/p>\n

Allikas: habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u042d\u0442\u0438\u043c \u043d\u0435\u0431\u043e\u043b\u044c\u0448\u0438\u043c \u043f\u043e\u0441\u0442\u043e\u043c \u0445\u043e\u0442\u0435\u043b\u043e\u0441\u044c \u0431\u044b \u0440\u0430\u0437\u0432\u0435\u044f\u0442\u044c \u043e\u0434\u043d\u043e \u043d\u0435\u0434\u043e\u0440\u0430\u0437\u0443\u043c\u0435\u043d\u0438\u0435, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u043e\u0435 \u0441 \u0430\u043d\u0430\u043b\u0438\u0437\u043e\u043c AWR \u0431\u0430\u0437 \u0434\u0430\u043d\u043d\u044b\u0445, \u0440\u0430\u0431\u043e\u0442\u0430\u044e\u0449\u0438\u0445 \u043d\u0430 Oracle Exadata. \u041f\u043e\u0447\u0442\u0438 10 \u043b\u0435\u0442 \u044f \u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u043e \u0441\u0442\u0430\u043b\u043a\u0438\u0432\u0430\u044e\u0441\u044c \u0441 \u0432\u043e\u043f\u0440\u043e\u0441\u043e\u043c: \u043a\u0430\u043a\u043e\u0432 \u0432\u043a\u043b\u0430\u0434 Exadata Software \u0432 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c? \u0418\u043b\u0438 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u043d\u043e\u0432\u043e\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0441\u043b\u043e\u0432: \u043d\u0430\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u00ab\u044d\u043a\u0437\u0430\u0434\u0430\u0442\u0438\u0442\u0441\u044f\u00bb \u0440\u0430\u0431\u043e\u0442\u0430 \u0442\u043e\u0439 \u0438\u043b\u0438 \u0438\u043d\u043e\u0439 \u0431\u0430\u0437\u044b \u0434\u0430\u043d\u043d\u044b\u0445? \u0427\u0430\u0441\u0442\u043e \u043d\u0430 \u044d\u0442\u043e\u0442 \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u044b\u0439 \u0432\u043e\u043f\u0440\u043e\u0441, \u043d\u0430 \u043c\u043e\u0439 \u0432\u0437\u0433\u043b\u044f\u0434, \u0434\u0430\u0435\u0442\u0441\u044f \u043d\u0435\u0432\u0435\u0440\u043d\u044b\u0439 […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":93139,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-93138","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47AWR: kui palju on andmebaasi t\u00f6\u00f6 \u00abekzadatiseeritud\u00bb? | ProHoster","description":"Selle v\u00e4ikese postitusega soovin hajutada \u00fchte arusaama, mis on seotud AWR andmebaaside anal\u00fc\u00fcsiga, mis t\u00f6\u00f6tavad Oracle Exadata-l. Peaaegu 10 aastat olen pidevalt kokku puutunud k\u00fcsimusega: milline on Exadata tarkvara panus j\u00f5udlusesse? V\u00f5i kasutades uusi v\u00e4ljendeid: kui palju on andmebaasi t\u00f6\u00f6 \u00abekzadatiseeritud\u00bb? 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