{"id":89498,"date":"2020-07-23T13:42:07","date_gmt":"2020-07-23T11:42:07","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql"},"modified":"2020-07-23T13:42:07","modified_gmt":"2020-07-23T11:42:07","slug":"testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql","title":{"rendered":"Testiranje performansi analiti\u010dkih upita u PostgreSQL, ClickHouse i clickhousedb_fdw (PostgreSQL)","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>V tej \u0161tudiji sem \u017eelel raziskati, kak\u0161ne izbolj\u0161ave zmogljivosti lahko dose\u017eem z uporabo podatkovnega vira ClickHouse namesto PostgreSQL. Zavedam se prednosti zmogljivosti, ki jih ponuja ClickHouse. Ali bodo te prednosti ohranjene, \u010de dostopam do ClickHouse iz PostgreSQL preko zunanje podatkovne obloge (FDW)? <\/p>\n<p><noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<p>Raziskovane baze podatkov so PostgreSQL v11, clickhousedb_fdw in baza podatkov ClickHouse. Na koncu bomo iz PostgreSQL v11 izvajali razli\u010dne SQL poizvedbe, ki bodo usmerjene preko na\u0161ega clickhousedb_fdw v bazo podatkov ClickHouse. Nato bomo videli, kako se zmogljivost FDW primerja z enakimi poizvedbami, ki jih izvajamo v nativnem PostgreSQL in nativnem ClickHouse.<\/p>\n<p><\/p>\n<h3 id=\"baza-dannyh-clickhouse\">Baza podatkov Clickhouse<\/h3>\n<p><\/p>\n<p>ClickHouse je sistem za upravljanje baz podatkov na osnovi kolon, s odprto kodo, ki lahko dose\u017ee zmogljivost od 100 do 1000-krat hitreje kot tradicionalni pristopi k bazam podatkov, sposoben obdelovati ve\u010d kot milijardo vrstic v manj kot sekundi.<\/p>\n<p><\/p>\n<h3 id=\"clickhousedb_fdw\">Clickhousedb_fdw<\/h3>\n<p><\/p>\n<p>clickhousedb_fdw je zunanja podatkovna obloga za bazo podatkov ClickHouse, oziroma FDW, in je projekt z odprto kodo, ki ga podpira Percona. <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/Percona-Lab\/clickhousedb_fdw\">Tukaj je povezava do repozitorija projekta na GitHubu<\/a><\/noindex>.<\/p>\n<p><\/p>\n<p><noindex><a rel=\"nofollow\" href=\"https:\/\/www.percona.com\/blog\/2019\/03\/29\/postgresql-access-clickhouse-one-of-the-fastest-column-dbmss-with-clickhousedb_fdw\/\">Marca sem napisal blog, ki vam pove ve\u010d o na\u0161em FDW<\/a><\/noindex>.<\/p>\n<p><\/p>\n<p>Kot boste videli, to omogo\u010da FDW za ClickHouse, ki omogo\u010da SELECT from in INSERT INTO baz podatkov ClickHouse s stre\u017enika PostgreSQL v11.<\/p>\n<p><\/p>\n<p>FDW podpira napredne funkcije, kot so agregati in zdru\u017eevanje. To znatno pove\u010da zmogljivost z uporabo virov oddaljenega stre\u017enika za te virov potro\u0161ne operacije.<\/p>\n<p><\/p>\n<h3 id=\"benchmark-environment\">Benchmark okolje<\/h3>\n<p><\/p>\n<ul>\n<li>Supermicro stre\u017enik:\n<ul>\n<li>Intel&reg; Xeon&reg; CPU E5-2683 v3 @ 2.00GHz<\/li>\n<li>2 vti\u010dnice \/ 28 jeder \/ 56 niti<\/li>\n<li>Pomnilnik: 256GB RAM<\/li>\n<li>Shranjevanje: Samsung SM863 1.9TB Enterprise SSD<\/li>\n<li>Datote\u010dni sistem: ext4\/xfs<\/li>\n<\/ul>\n<\/li>\n<li>OS: Linux smblade01 4.15.0-42-generic #45~16.04.1-Ubuntu<\/li>\n<li>PostgreSQL: razli\u010dica 11<\/li>\n<\/ul>\n<p><\/p>\n<h3 id=\"benchmark-tests\">Benchmark testi<\/h3>\n<p><\/p>\n<p>Namesto da bi uporabili neko podatkovno mno\u017eico, generirano z napravo, smo za ta test uporabili podatke 'Zmogljivost po \u010dasu, obve\u0161\u010deni o \u010dasu dela operaterja' od leta 1987 do 2018. Do podatkov lahko dostopate <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/Percona-Lab\/ontime-airline-performance\/blob\/master\/download.sh\">z na\u0161im skriptom, ki je tukaj na voljo<\/a><\/noindex>.<\/p>\n<p><\/p>\n<p>Velikost baze podatkov je 85 GB, ki vsebuje eno tabelo z 109 stolpci.<\/p>\n<p><\/p>\n<h4 id=\"benchmark-queries\">Benchmark poizvedbe<\/h4>\n<p><\/p>\n<p>Tukaj so poizvedbe, ki sem jih uporabil za primerjavo ClickHouse, clickhousedb_fdw in PostgreSQL.<\/p>\n<p><\/p>\n<p><strong>Q#<\/strong><br \/>\n<strong>Poizvedba vsebuje agregate in Group By<\/strong><\/p>\n<p>Q1<br \/>\nSELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year &gt;= 2000 AND Year &lt;= 2008 GROUP BY DayOfWeek ORDER BY c DESC;<\/p>\n<p>Q2<br \/>\nIZBERI DanTedna, \u0161tevilo(*) AS c IZ ontime KJER DepDelay&gt;10 IN Leto &gt;= 2000 IN Leto &lt;= 2008 SKUPAJ PO DanTedna NARO\u010cI PO c DESC;<\/p>\n<p>Q3<br \/>\nIZBERI Izvor, \u0161tevilo(*) AS c IZ ontime KJER DepDelay&gt;10 IN Leto &gt;= 2000 IN Leto &lt;= 2008 SKUPAJ PO Izvor NARO\u010cI PO c DESC OMEJITI 10;<\/p>\n<p>Q4<br \/>\nIZBERI Prevoznik, \u0161tevilo(<em>) IZ ontime KJER DepDelay&gt;10 IN Leto = 2007 SKUPAJ PO Prevoznik NARO\u010cI PO \u0161tevilo(<\/em>) DESC;<\/p>\n<p>Q5<br \/>\nIZBERI a.Prevoznik, c, c2, c<em>1000\/c2 kot c3 IZ ( IZBERI Prevoznik, \u0161tevilo(<\/em>) AS c IZ ontime KJER DepDelay&gt;10 IN Leto=2007 SKUPAJ PO Prevoznik ) a NOTRANJI JOIN ( IZBERI Prevoznik,\u0161tevilo(*) AS c2 IZ ontime KJER Leto=2007 SKUPAJ PO Prevoznik)b ON a.Prevoznik=b.Prevoznik NARO\u010cI PO c3 DESC;<\/p>\n<p>Q6<br \/>\nIZBERI a.Prevoznik, c, c2, c<em>1000\/c2 kot c3 IZ ( IZBERI Prevoznik, \u0161tevilo(<\/em>) AS c IZ ontime KJER DepDelay&gt;10 IN Leto &gt;= 2000 IN Leto &lt;= 2008 SKUPAJ PO Prevoznik) a NOTRANJI JOIN ( IZBERI Prevoznik, \u0161tevilo(*) AS c2 IZ ontime KJER Leto &gt;= 2000 IN Leto &lt;= 2008 SKUPAJ PO Prevoznik ) b ON a.Prevoznik=b.Prevoznik NARO\u010cI PO c3 DESC;<\/p>\n<p>Q7<br \/>\nIZBERI Prevoznik, povpre\u010dje(DepDelay) * 1000 AS c3 IZ ontime KJER Leto &gt;= 2000 IN Leto &lt;= 2008 SKUPAJ PO Prevoznik;<\/p>\n<p>Q8<br \/>\nIZBERI Leto, povpre\u010dje(DepDelay) IZ ontime SKUPAJ PO Leto;<\/p>\n<p>Q9<br \/>\nizberi Leto, \u0161tevilo(*) kot c1 IZ ontime SKUPAJ PO Leto;<\/p>\n<p>Q10<br \/>\nIZBERI povpre\u010dje(cnt) IZ (IZBERI Leto,Mesec, \u0161tevilo(*) AS cnt IZ ontime KJER DepDel15=1 SKUPAJ PO Leto,Mesec) a;<\/p>\n<p>Q11<br \/>\nizberi povpre\u010dje(c1) IZ (izberi Leto,Mesec, \u0161tevilo(*) kot c1 IZ ontime SKUPAJ PO Leto,Mesec) a;<\/p>\n<p>Q12<br \/>\nIZBERI ImeIzvirnegaMesta, ImeDestinacijskegaMesta, \u0161tevilo(*) AS c IZ ontime SKUPAJ PO ImeIzvirnegaMesta, ImeDestinacijskegaMesta NARO\u010cI PO c DESC OMEJITI 10;<\/p>\n<p>Q13<br \/>\nIZBERI ImeIzvirnegaMesta, \u0161tevilo(*) AS c IZ ontime SKUPAJ PO ImeIzvirnegaMesta NARO\u010cI PO c DESC OMEJITI 10;<\/p>\n<p><strong>Poizvedba vsebuje zdru\u017eitve<\/strong><\/p>\n<p>Q14<br \/>\nIZBERI a.Leto, c1\/c2 IZ ( izberi Leto, \u0161tevilo(<em>)<\/em>1000 kot c1 IZ ontime KJER DepDelay&gt;10 SKUPAJ PO Leto) a NOTRANJI JOIN (izberi Leto, \u0161tevilo(*) kot c2 IZ ontime SKUPAJ PO Leto ) b ON a.Leto=b.Leto NARO\u010cI PO a.Leto;<\/p>\n<p>Q15<br \/>\nIZBERI a.\"Leto\", c1\/c2 IZ ( izberi \"Leto\", \u0161tevilo(<em>)<\/em>1000 kot c1 IZ fontime KJER \"DepDelay\"&gt;10 SKUPAJ PO \"Leto\") a NOTRANJI JOIN (izberi \"Leto\", \u0161tevilo(*) kot c2 IZ fontime SKUPAJ PO \"Leto\" ) b ON a.\"Leto\"=b.\"Leto\";<\/p>\n<p><\/p>\n<p><em>Tabela-1: Poizvedbe uporabljene v benchmarku<\/em><\/p>\n<p><\/p>\n<h4 id=\"query-executions\">Izvr\u0161itve poizvedb<\/h4>\n<p><\/p>\n<p>Tukaj so rezultati posameznih poizvedb, izvedenih v razli\u010dnih nastavitvah baze podatkov: PostgreSQL z indeksi in brez njih, lastni ClickHouse in clickhousedb_fdw. \u010cas je prikazan v milisekundah.<\/p>\n<p><\/p>\n<p><strong>Q#<\/strong><br \/>\n<strong>PostgreSQL<\/strong><br \/>\n<strong>PostgreSQL (Indeksirani)<\/strong><br \/>\n<strong>ClickHouse<\/strong><br \/>\n<strong>clickhousedb_fdw<\/strong><\/p>\n<p>Q1<br \/>\n27920<br \/>\n19634<br \/>\n23<br \/>\n57<\/p>\n<p>Q2<br \/>\n35124<br \/>\n17301<br \/>\n50<br \/>\n80<\/p>\n<p>Q3<br \/>\n34046<br \/>\n15618<br \/>\n67<br \/>\n115<\/p>\n<p>Q4<br \/>\n31632<br \/>\n7667<br \/>\n25<br \/>\n37<\/p>\n<p>Q5<br \/>\n47220<br \/>\n8976<br \/>\n27<br \/>\n60<\/p>\n<p>Q6<br \/>\n58233<br \/>\n24368<br \/>\n55<br \/>\n153<\/p>\n<p>Q7<br \/>\n30566<br \/>\n13256<br \/>\n52<br \/>\n91<\/p>\n<p>Q8<br \/>\n38309<br \/>\n60511<br \/>\n112<br \/>\n179<\/p>\n<p>Q9<br \/>\n20674<br \/>\n37979<br \/>\n31<br \/>\n81<\/p>\n<p>Q10<br \/>\n34990<br \/>\n20102<br \/>\n56<br \/>\n148<\/p>\n<p>Q11<br \/>\n30489<br \/>\n51658<br \/>\n37<br \/>\n155<\/p>\n<p>Q12<br \/>\n39357<br \/>\n33742<br \/>\n186<br \/>\n1333<\/p>\n<p>Q13<br \/>\n29912<br \/>\n30709<br \/>\n101<br \/>\n384<\/p>\n<p>Q14<br \/>\n54126<br \/>\n39913<br \/>\n124<br \/>\n1364212<\/p>\n<p>Q15<br \/>\n97258<br \/>\n30211<br \/>\n245<br \/>\n259<\/p>\n<p><\/p>\n<p><em>Tabela-1: \u010cas, potreben za izvr\u0161itev poizvedb uporabljene v benchmarku<\/em><\/p>\n<p><\/p>\n<p>Ogled rezultatov<\/p>\n<p><\/p>\n<p>Graf prikazuje \u010das izvr\u0161itve poizvedbe v milisekundah, os X prikazuje \u0161tevilko poizvedbe iz zgornjih tabel, os Y pa prikazuje \u010das izvr\u0161itve v milisekundah. Rezultati ClickHouse in podatki, pridobljeni iz postgres z uporabo clickhousedb_fdw, so prikazani. Iz tabele je razvidno, da obstaja ogromna razlika med PostgreSQL in ClickHouse, a minimalna razlika med ClickHouse in clickhousedb_fdw.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Testiranje performansi analiti\u010dkih upita u PostgreSQL, ClickHouse i clickhousedb_fdw (PostgreSQL)\" src=\"\/wp-content\/uploads\/2020\/07\/e084243ea7b327f30de5cb78339d3d3a.png\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Ta graf prikazuje razliko med ClickhouseDB in clickhousedb_fdw. Pri ve\u010dini poizvedb niso tako visoke stro\u0161ke FDW in so komaj opazne, razen pri Q12. Ta poizvedba vklju\u010duje zdru\u017eitve in klavzulo ORDER BY. Zaradi klavzule ORDER BY SKUPINA\/BY in ORDER BY se do ClickHouse ne opusti.<\/p>\n<p><\/p>\n<p>V tabeli 2 vidimo skok \u010dasa pri poizvedbah Q12 in Q13. Ponovno, to je posledica uporabe ukaza ORDER BY. Da bi to potrdil, sem izvedel poizvedbe Q-14 in Q-15 z ukazom ORDER BY in brez njega. Brez ukaza ORDER BY je \u010das zaklju\u010dka 259 ms, medtem ko je s tem ukazom 1364212. Za odpravljanje napak pri tej poizvedbi sem razlo\u017eil oboje, tukaj so rezultati razlage.<\/p>\n<p><\/p>\n<p>Q15: Brez klavzule ORDER BY<\/p>\n<p><\/p>\n<pre><code class=\"plaintext\">bm=# EXPLAIN VERBOSE SELECT a.&quot;Year&quot;, c1\/c2 \n     FROM (SELECT &quot;Year&quot;, count(*)*1000 AS c1 FROM fontime WHERE &quot;DepDelay&quot; &gt; 10 GROUP BY &quot;Year&quot;) a\n     INNER JOIN(SELECT &quot;Year&quot;, count(*) AS c2 FROM fontime GROUP BY &quot;Year&quot;) b ON a.&quot;Year&quot;=b.&quot;Year&quot;;<\/code><\/pre>\n<p><\/p>\n<p>Q15: Poizvedba brez klavzule ORDER BY<\/p>\n<p><\/p>\n<pre><code class=\"plaintext\">QUERY PLAN                                                      \nHash Join  (cost=2250.00..128516.06 rows=50000000 width=12)  \nOutput: fontime.&quot;Year&quot;, (((count(*) * 1000)) \/ b.c2)  \nInner Unique: true   Hash Cond: (fontime.&quot;Year&quot; = b.&quot;Year&quot;)  \n-&gt;  Foreign Scan  (cost=1.00..-1.00 rows=100000 width=12)        \nOutput: fontime.&quot;Year&quot;, ((count(*) * 1000))        \nRelations: Aggregate on (fontime)        \nRemote SQL: SELECT &quot;Year&quot;, (count(*) * 1000) FROM &quot;default&quot;.ontime WHERE ((&quot;DepDelay&quot; &gt; 10)) GROUP BY &quot;Year&quot;  \n-&gt;  Hash  (cost=999.00..999.00 rows=100000 width=12)        \nOutput: b.c2, b.&quot;Year&quot;        \n-&gt;  Subquery Scan on b  (cost=1.00..999.00 rows=100000 width=12)              \nOutput: b.c2, b.&quot;Year&quot;              \n-&gt;  Foreign Scan  (cost=1.00..-1.00 rows=100000 width=12)                    \nOutput: fontime_1.&quot;Year&quot;, (count(*))                    \nRelations: Aggregate on (fontime)                    \nRemote SQL: SELECT &quot;Year&quot;, count(*) FROM &quot;default&quot;.ontime GROUP BY &quot;Year&quot;(16 rows)<\/code><\/pre>\n<p><\/p>\n<p>Q14: Poizvedba z ukazom ORDER BY<\/p>\n<p><\/p>\n<pre><code class=\"plaintext\">bm=# EXPLAIN VERBOSE SELECT a.&quot;Year&quot;, c1\/c2 FROM(SELECT &quot;Year&quot;, count(*)*1000 AS c1 FROM fontime WHERE &quot;DepDelay&quot; &gt; 10 GROUP BY &quot;Year&quot;) a \n     INNER JOIN(SELECT &quot;Year&quot;, count(*) as c2 FROM fontime GROUP BY &quot;Year&quot;) b  ON a.&quot;Year&quot;= b.&quot;Year&quot; \n     ORDER BY a.&quot;Year&quot;;<\/code><\/pre>\n<p><\/p>\n<p>Q14: Poizvedbeni na\u010drt z ukazom ORDER BY<\/p>\n<p><\/p>\n<pre><code class=\"plaintext\">QUERY PLAN \nMerge Join\u00a0 (cost=2.00..628498.02 rows=50000000 width=12)\u00a0\u00a0 \nOutput: fontime.&quot;Year&quot;, (((count(*) * 1000)) \/ (count(*)))\u00a0\u00a0 \nInner Unique: true\u00a0\u00a0 Merge Cond: (fontime.&quot;Year&quot; = fontime_1.&quot;Year&quot;)\u00a0\u00a0 \n-&gt;\u00a0 GroupAggregate\u00a0 (cost=1.00..499.01 rows=1 width=12)\u00a0 \u00a0 \u00a0 \u00a0 \nOutput: fontime.&quot;Year&quot;, (count(*) * 1000)\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \nGroup Key: fontime.&quot;Year&quot;\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \n-&gt;\u00a0 Foreign Scan on public.fontime\u00a0 (cost=1.00..-1.00 rows=100000 width=4)\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \nRemote SQL: SELECT &quot;Year&quot; FROM &quot;default&quot;.ontime WHERE ((&quot;DepDelay&quot; &gt; 10)) \n            ORDER BY &quot;Year&quot; ASC\u00a0\u00a0 \n-&gt;\u00a0 GroupAggregate\u00a0 (cost=1.00..499.01 rows=1 width=12)\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \nOutput: fontime_1.&quot;Year&quot;, count(*)\u00a0\u00a0 \u00a0 \u00a0 \u00a0 Group Key: fontime_1.&quot;Year&quot;\u00a0\u00a0 \u00a0 \u00a0 \u00a0 \n-&gt;\u00a0 Foreign Scan on public.fontime fontime_1\u00a0 (cost=1.00..-1.00 rows=100000 width=4)\u00a0\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \nRemote SQL: SELECT &quot;Year&quot; FROM &quot;default&quot;.ontime ORDER BY &quot;Year&quot; ASC(16 rows)<\/code><\/pre>\n<p><\/p>\n<p>Izlaz<\/p>\n<p><\/p>\n<p>Rezultati teh eksperimentov ka\u017eejo, da ClickHouse ponuja resni\u010dno dobro zmogljivost, medtem ko clickhousedb_fdw prina\u0161a prednosti zmogljivosti ClickHouse iz PostgreSQL. \u010ceprav pri uporabi clickhousedb_fdw obstajajo dolo\u010deni stro\u0161ki, so ti zanemarljivi in primerljivi z zmogljivostjo, dose\u017eeno pri naravnem zagonu v bazi podatkov ClickHouse. To tudi potrjuje, da fdw v PostgreSQL zagotavlja izjemne rezultate.<\/p>\n<p><\/p>\n<p>Telegram skupina za Clickhouse <noindex><a rel=\"nofollow\" href=\"https:\/\/t.me\/clickhouse_ru\">https:\/\/t.me\/clickhouse_ru<\/a><\/noindex><br \/>\nTelegram skupina za PostgreSQL <noindex><a rel=\"nofollow\" href=\"https:\/\/t.me\/pgsql\">https:\/\/t.me\/pgsql<\/a><\/noindex><\/p>\n<p>Izvor: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/511992\/\">habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0412 \u044d\u0442\u043e\u043c \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0438 \u044f \u0445\u043e\u0442\u0435\u043b \u043f\u043e\u0441\u043c\u043e\u0442\u0440\u0435\u0442\u044c, \u043a\u0430\u043a\u0438\u0435 \u0443\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u043d\u043e \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a \u0434\u0430\u043d\u043d\u044b\u0445 ClickHouse, \u0430 \u043d\u0435 PostgreSQL. \u042f \u0437\u043d\u0430\u044e, \u043a\u0430\u043a\u0438\u0435 \u043f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0438 ClickHouse \u044f \u043f\u043e\u043b\u0443\u0447\u0430\u044e. \u0411\u0443\u0434\u0443\u0442 \u043b\u0438 \u044d\u0442\u0438 \u043f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0441\u043e\u0445\u0440\u0430\u043d\u0435\u043d\u044b, \u0435\u0441\u043b\u0438 \u044f \u043f\u043e\u043b\u0443\u0447\u0443 \u0434\u043e\u0441\u0442\u0443\u043f \u043a ClickHouse \u0438\u0437 PostgreSQL \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0432\u043d\u0435\u0448\u043d\u0435\u0439 \u043e\u0431\u043e\u043b\u043e\u0447\u043a\u0438 \u0434\u0430\u043d\u043d\u044b\u0445 (FDW)? \u0418\u0441\u0441\u043b\u0435\u0434\u0443\u0435\u043c\u044b\u043c\u0438 \u0441\u0440\u0435\u0434\u0430\u043c\u0438 \u0431\u0430\u0437 \u0434\u0430\u043d\u043d\u044b\u0445 \u044f\u0432\u043b\u044f\u044e\u0442\u0441\u044f PostgreSQL v11, clickhousedb_fdw [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":89499,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-89498","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.4 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0438 \u044f \u0445\u043e\u0442\u0435\u043b \u043f\u043e\u0441\u043c\u043e\u0442\u0440\u0435\u0442\u044c, \u043a\u0430\u043a\u0438\u0435 \u0443\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u043d\u043e \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a \u0434\u0430\u043d\u043d\u044b\u0445 ClickHouse, \u0430 \u043d\u0435 PostgreSQL.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.4\" \/>\n\t\t<meta property=\"og:locale\" content=\"sl_SI\" \/>\n\t\t<meta property=\"og:site_name\" content=\"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\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"\ud83e\udd47\u0422\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u0432 PostgreSQL, ClickHouse \u0438 clickhousedb_fdw (PostgreSQL) | ProHoster\" \/>\n\t\t<meta property=\"og:description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0438 \u044f \u0445\u043e\u0442\u0435\u043b \u043f\u043e\u0441\u043c\u043e\u0442\u0440\u0435\u0442\u044c, \u043a\u0430\u043a\u0438\u0435 \u0443\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u043d\u043e \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a \u0434\u0430\u043d\u043d\u044b\u0445 ClickHouse, \u0430 \u043d\u0435 PostgreSQL.\" \/>\n\t\t<meta property=\"og:url\" content=\"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql\" \/>\n\t\t<meta property=\"og:image\" content=\"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg\" \/>\n\t\t<meta property=\"og:image:secure_url\" content=\"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg\" \/>\n\t\t<meta property=\"og:image:width\" content=\"350\" \/>\n\t\t<meta property=\"og:image:height\" content=\"350\" \/>\n\t\t<meta property=\"article:published_time\" content=\"2020-07-23T11:42:07+00:00\" \/>\n\t\t<meta property=\"article:modified_time\" content=\"2020-07-23T11:42:07+00:00\" \/>\n\t\t<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/prohoster\" \/>\n\t\t<meta property=\"article:author\" content=\"https:\/\/www.facebook.com\/prohoster\" \/>\n\t\t<!-- All in One SEO -->\n\n","aioseo_head_json":{"title":"\ud83e\udd47Testiranje zmogljivosti analiti\u010dnih poizvedb v PostgreSQL, ClickHouse in clickhousedb_fdw (PostgreSQL) | ProHoster","description":"V tej \u0161tudiji sem \u017eelel raziskati, kak\u0161na izbolj\u0161anja zmogljivosti lahko dobimo, \u010de uporabimo vir podatkov ClickHouse namesto PostgreSQL.","canonical_url":"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql","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\udd47\u0422\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u0432 PostgreSQL, ClickHouse \u0438 clickhousedb_fdw (PostgreSQL) | ProHoster","og:description":"\u0412 \u044d\u0442\u043e\u043c \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0438 \u044f \u0445\u043e\u0442\u0435\u043b \u043f\u043e\u0441\u043c\u043e\u0442\u0440\u0435\u0442\u044c, \u043a\u0430\u043a\u0438\u0435 \u0443\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u043d\u043e \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a \u0434\u0430\u043d\u043d\u044b\u0445 ClickHouse, \u0430 \u043d\u0435 PostgreSQL.","og:url":"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/testirovanie-proizvoditelnosti-analiticheskih-zaprosov-v-postgresql-clickhouse-i-clickhousedb_fdw-postgresql","og:image":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:secure_url":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:width":350,"og:image:height":350,"article:published_time":"2020-07-23T11:42:07+00:00","article:modified_time":"2020-07-23T11:42:07+00:00","article:publisher":"https:\/\/www.facebook.com\/prohoster","article:author":"https:\/\/www.facebook.com\/prohoster"},"aioseo_meta_data":{"post_id":"89498","title":null,"description":null,"keywords":null,"keyphrases":null,"primary_term":null,"canonical_url":null,"og_title":null,"og_description":null,"og_object_type":"default","og_image_type":"default","og_image_url":null,"og_image_width":null,"og_image_height":null,"og_image_custom_url":null,"og_image_custom_fields":null,"og_video":null,"og_custom_url":null,"og_article_section":null,"og_article_tags":null,"twitter_use_og":false,"twitter_card":"default","twitter_image_type":"default","twitter_image_url":null,"twitter_image_custom_url":null,"twitter_image_custom_fields":null,"twitter_title":null,"twitter_description":null,"schema":{"blockGraphs":[],"customGraphs":[],"default":{"data":{"Article":[],"Course":[],"Dataset":[],"FAQPage":[],"Movie":[],"Person":[],"Product":[],"ProductReview":[],"Car":[],"Recipe":[],"Service":[],"SoftwareApplication":[],"WebPage":[]},"graphName":"","isEnabled":true},"graphs":[]},"schema_type":null,"schema_type_options":null,"pillar_content":false,"robots_default":true,"robots_noindex":false,"robots_noarchive":false,"robots_nosnippet":false,"robots_nofollow":false,"robots_noimageindex":false,"robots_noodp":false,"robots_notranslate":false,"robots_max_snippet":null,"robots_max_videopreview":null,"robots_max_imagepreview":"large","priority":null,"frequency":null,"local_seo":null,"seo_analyzer_scan_date":null,"breadcrumb_settings":null,"limit_modified_date":false,"reviewed_by":null,"ai":null,"created":"2021-02-28 13:10:17","updated":"2022-10-10 22:45:45","focus_keyword":null,"additional_keywords":null,"truseo_locale":null},"gt_translate_keys":[{"key":"link","format":"url"}],"_links":{"self":[{"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/posts\/89498","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/comments?post=89498"}],"version-history":[{"count":0,"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/posts\/89498\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/media\/89499"}],"wp:attachment":[{"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/media?parent=89498"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/categories?post=89498"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/prohoster.info\/sl\/wp-json\/wp\/v2\/tags?post=89498"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}