{"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\/sl\/blog\/administrirovanie\/awr-naskolko-ekzadatitsya-rabota-bazy-dannyh","title":{"rendered":"AWR: Kako mo\u010dno vpliva bazni podatkov na delovanje?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

S tem manj\u0161im prispevkom bi rad razjasnil eno zmedo, povezano z analizo AWR baz podatkov, ki delujejo na Oracle Exadata. \u017de skoraj 10 let se neprekinjeno sre\u010dujem z vpra\u0161anjem: kak\u0161en je prispevek Exadata Software k zmogljivosti? Ali z uporabo novotvorjenih izrazov: kako zelo 'exadata' je delo te ali one baze podatkov?<\/p>\n

\"AWR:<\/p>\n

Na to pravilno vpra\u0161anje se pogosto, po mojem mnenju, odgovarja napa\u010dno s sklicem na statistiko AWR. V njej je prikazana metoda sistemskih \u010dakanj, ki razume \u010das odziva kot vsoto \u010dasa delovanja procesorjev (DB CPU) in \u010dasa \u010dakanja razli\u010dnih razredov.<\/p>\n

S pojavom Exadata so se v statistiki AWR pojavila specifi\u010dna sistemska \u010dakanja, povezana z delovanjem Exadata Software. Navadno se imena takih \u010dakanj za\u010dnejo s besedo \u201ccell\u201d (cell se imenuje Exadata Storage stre\u017enik), najpogosteje pa se sre\u010dujemo s \u010dakanji z izrazitimi imeni, kot so \u201ccell smart table scan\u201d, \u201ccell multiblock physical read\u201d in \u201ccell single block physical read\u201d.<\/p>\n

V ve\u010dini primerov dele\u017e takih Exadata \u010dakanj v skupnem \u010dasu odziva ni velik, zato se niti ne uvrstijo v odsek Top10 Foreground Events by Total Wait Time (v tem primeru jih je treba iskati v razdelku Foreground Wait Events). Z velikimi te\u017eavami smo pri na\u0161ih strankah odkrili primer dnevne AWR, v katerem so se Exadata \u010dakanja uvrstila v odsek Top10 in skupaj predstavljala pribli\u017eno 5%:<\/p>\n

Dogodek<\/strong><\/p>\n

\u010cakanja<\/strong><\/p>\n

Skupni \u010das \u010dakanja (sekunde)<\/strong><\/p>\n

Povpre\u010dno \u010dakanje<\/strong><\/p>\n

% DB \u010dasa<\/strong><\/p>\n

Razred \u010dakanja<\/strong><\/p>\n

DB CPU<\/p>\n

<\/p>\n

115.2K<\/p>\n

<\/p>\n

70.4<\/p>\n

<\/p>\n

SQL*Net ve\u010d podatkov iz dblink<\/p>\n

670,196<\/p>\n

5471.5<\/p>\n

8.16ms<\/p>\n

3.3<\/p>\n

Mre\u017ea<\/p>\n

cell enojno blokovno fizi\u010dno branje<\/p>\n

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

3827.6<\/p>\n

676.07us<\/p>\n

2.3<\/p>\n

Uporabni\u0161ki I\/O<\/p>\n

Sinhrono ASM balansiranje<\/p>\n

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

3481.3<\/p>\n

800.30us<\/p>\n

2.1<\/p>\n

Drugo<\/p>\n

cell multiblock fizi\u010dno branje<\/p>\n

759,885<\/p>\n

2252<\/p>\n

2.96ms<\/p>\n

1.4<\/p>\n

Uporabni\u0161ki I\/O<\/p>\n

direktno pot branje<\/p>\n

374,368<\/p>\n

1811.3<\/p>\n

4.84ms<\/p>\n

1.1<\/p>\n

Uporabni\u0161ki I\/O<\/p>\n

SQL*Net sporo\u010dilo iz dblink<\/p>\n

7,983<\/p>\n

1725<\/p>\n

216.08ms<\/p>\n

1.1<\/p>\n

Mre\u017ea<\/p>\n

cell pametno branje tabel<\/p>\n

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

1260.7<\/p>\n

1.25ms<\/p>\n

0.8<\/p>\n

Uporabni\u0161ki I\/O<\/p>\n

direktno pot branje temp<\/p>\n

520,211<\/p>\n

808.4<\/p>\n

1.55ms<\/p>\n

0.5<\/p>\n

Uporabni\u0161ki I\/O<\/p>\n

enq: TM — contention<\/p>\n

652<\/p>\n

795.8<\/p>\n

1220.55ms<\/p>\n

0.5<\/p>\n

Aplikacija<\/p>\n

Iz tak\u0161ne AWR statistike pogosto potegnejo take zaklju\u010dke:<\/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

Oba ta izhoda sta neto\u010dna, celo ve\u010d, zmedeta razumevanje ideje, ki je vgrajena v Exadata Software. Exadata ne zagotavlja samo hitrega vnosa in izhoda, deluje bistveno druga\u010de v primerjavi s klasi\u010dno arhitekturo \u201estre\u017enik + shranjevanje\u201c. \u010ce se baza podatkov res \u201eekzadati\u201c \u2014 se SQL-logika prenese na sistem shranjevanja. Shranjevanje servere<\/a> z zahvaljujo\u010d vrsti posebnih mehanizmov (predvsem Exadata Storage Indexes, a ne samo to) sama najde potrebne podatke in jih po\u0161lje stre\u017enikom DB. To po\u010dnejo dovolj u\u010dinkovito, zato je dele\u017e zna\u010dilnih Exadata-\u010dakanj v skupnem \u010dasu odziva majhen. <\/p>\n

Kako se bo ta dele\u017e spremenil zunaj Exadata? Kako bo to vplivalo na zmogljivost baze podatkov kot celote? Najbolj\u0161i odgovor na ta vpra\u0161anja bo dala testiranja. Na primer, \u010dakanje na \u201ecell smart table scan\u201c zunaj Exadata se lahko spremeni v tako te\u017eak Table Full Scan, da bo vnos in izhod vzel ves \u010das odziva in zmogljivost se bo drasti\u010dno poslab\u0161ala. Zato je napa\u010dno pri analizi AWR upo\u0161tevati skupni odstotek \u010dakanj Exadata kot prispevek njene magije k zmogljivosti in \u0161e posebej uporabiti ta odstotek za napovedovanje zmogljivosti zunaj Exadata. Da bi razumeli, kako zelo \u201eekzadati\u201c je delo baze, je treba preu\u010diti statistike AWR sekcije \u201cInstance Activity Stats\u201d (tja je veliko statistik s pomenljivimi imeni) in jih med seboj primerjati.<\/p>\n

Da bi razumeli, kako bo baza podatkov delovala zunaj Exadata, je najbolje ustvariti klon baze iz varnostne kopije na ciljni arhitekturi in analizirati zmogljivost tega klona pod obremenitvijo. Tak\u0161no prilo\u017enost imajo obi\u010dajno lastniki Exadata.<\/p>\n

Avtor: Aleksiej Strujenko, vodja oddelka za Baze podatkov v \u201eInfososistemah Jet\u201c<\/em><\/p>\n

Izvor: 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\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: kako zelo \u201eekzadati\u201c je delo baze podatkov? | ProHoster","description":"S tem kratkim zapisom bi rad razblinil eno zmedo, povezano z analizo AWR baz podatkov, ki delujejo na Oracle Exadata.","canonical_url":"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/awr-naskolko-ekzadatitsya-rabota-bazy-dannyh","robots":"max-image-preview:large","keywords":"","webmasterTools":{"miscellaneous":""},"schema":null,"og:locale":"sl_SI","og:site_name":"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b","og:type":"article","og:title":"\ud83e\udd47AWR: \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 \u0431\u0430\u0437\u044b \u0434\u0430\u043d\u043d\u044b\u0445? 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