{"id":54918,"date":"2020-01-07T00:00:00","date_gmt":"2020-01-06T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/ispolzovanie-clickhouse-v-kachestve-zameny-elk-big-query-i-timescaledb"},"modified":"2020-02-18T14:02:58","modified_gmt":"2020-02-18T11:02:58","slug":"ispolzovanie-clickhouse-v-kachestve-zameny-elk-big-query-i-timescaledb","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/administrirovanie\/ispolzovanie-clickhouse-v-kachestve-zameny-elk-big-query-i-timescaledb","title":{"rendered":"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><noindex><a rel=\"nofollow\" href=\"https:\/\/clickhouse.yandex\/\">Clickhouse<\/a><\/noindex> \u2014 \u00ebsht\u00eb nj\u00eb sistem i menaxhimit t\u00eb bazave t\u00eb t\u00eb dh\u00ebnave kolumnar p\u00ebr p\u00ebrpunimin analitik n\u00eb linj\u00eb (OLAP) me kod t\u00eb hapur, i krijuar nga Yandex. P\u00ebrdoret nga Yandex, CloudFlare, VK.com, Badoo dhe sh\u00ebrbime t\u00eb tjera n\u00eb t\u00eb gjith\u00eb bot\u00ebn p\u00ebr t\u00eb ruajtur sasi t\u00eb m\u00ebdha t\u00eb dh\u00ebnash (me qindra mij\u00ebra rreshta t\u00eb futur n\u00eb sekond\u00eb ose petabay t\u00eb dh\u00ebnash t\u00eb ruajtur n\u00eb disk).<\/p>\n<p>N\u00eb nj\u00eb DBM t\u00eb zakonsh\u00ebm, si\u00e7 jan\u00eb MySQL, Postgres, MS SQL Server, t\u00eb dh\u00ebnat ruhen n\u00eb k\u00ebt\u00eb rend: <\/p>\n<p><img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/398f260de0152baf3cc11d884fa0d52d.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nN\u00eb k\u00ebt\u00eb m\u00ebnyr\u00eb, vlerat q\u00eb i p\u00ebrkasin nj\u00eb rreshti ruhen fizikisht af\u00ebr nj\u00ebra-tjetr\u00ebs. N\u00eb DBM-t\u00eb kolumnar, vlerat nga kolona t\u00eb ndryshme ruhen ndaras, dhe t\u00eb dh\u00ebnat e nj\u00eb kolone ruhen s\u00eb bashku:<\/p>\n<p><img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/938a2ee3d588ac866ec92bb3ea09c253.png\" style=\"display:block;margin: 0 auto;\" \/><noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<p>Shembuj t\u00eb DBM-ve kolumnar p\u00ebrfshijn\u00eb Vertica, Paraccel (Actian Matrix, Amazon Redshift), Sybase IQ, Exasol, Infobright, InfiniDB, MonetDB (VectorWise, Actian Vector), LucidDB, SAP HANA, Google Dremel, Google PowerDrill, Druid, kdb+.<\/p>\n<p>Kompania \u2013 mailforwarder <noindex><a rel=\"nofollow\" href=\"https:\/\/qwintry.com\/\">Qwintry<\/a><\/noindex> ka filluar t\u00eb p\u00ebrdor\u00eb Clickhouse n\u00eb vitin 2018 p\u00ebr p\u00ebrgatitjen e raporteve dhe \u00ebsht\u00eb impresionuar shum\u00eb nga thjesht\u00ebsia, shkall\u00ebzueshm\u00ebria, mb\u00ebshtetja p\u00ebr SQL dhe shpejt\u00ebsia e saj. Shpejt\u00ebsia e pun\u00ebs s\u00eb k\u00ebsaj DBM ishte af\u00ebr magjis\u00eb.<\/p>\n<h3>Thjesht\u00ebsia<\/h3>\n<p>\nClickhouse instalon n\u00eb Ubuntu me nj\u00eb komand\u00eb t\u00eb vetme. N\u00ebse e njihni SQL, mund t\u00eb filloni menj\u00ebher\u00eb t\u00eb p\u00ebrdorni Clickhouse p\u00ebr nevojat tuaja. Megjithat\u00eb, kjo nuk do t\u00eb thot\u00eb se mund t\u00eb ekzekutoni \"show create table\" n\u00eb MySQL dhe t\u00eb b\u00ebni kopipastimin e SQL n\u00eb Clickhouse. <\/p>\n<p>Krahasuar me MySQL, n\u00eb k\u00ebt\u00eb DBM ekzistojn\u00eb dallime t\u00eb r\u00ebnd\u00ebsishme n\u00eb llojet e t\u00eb dh\u00ebnave n\u00eb p\u00ebrkufizimet e skemave t\u00eb tabelave, prandaj, p\u00ebr t\u00eb punuar comforotb\u00eb me t\u00eb, do t'ju nevojitet pak koh\u00eb p\u00ebr t\u00eb modifikuar p\u00ebrkufizimet e skemave t\u00eb tabelave dhe p\u00ebr t\u00eb studiuar motor\u00ebt e tabelave.<\/p>\n<p>Clickhouse funksionon shk\u00eblqyesh\u00ebm pa ndonj\u00eb software shtes\u00eb, por n\u00ebse d\u00ebshironi t\u00eb p\u00ebrdorni replikimin, do t'ju duhet t\u00eb instaloni ZooKeeper. Analiza e performanc\u00ebs s\u00eb k\u00ebrkesave tregon rezultate t\u00eb shk\u00eblqyera \u2014 tabelat sistemike p\u00ebrmbajn\u00eb t\u00eb gjith\u00eb informacionin dhe t\u00eb gjitha t\u00eb dh\u00ebnat mund t\u00eb merren n\u00ebp\u00ebrmjet SQL-it t\u00eb vjet\u00ebr dhe t\u00eb m\u00ebrzitsh\u00ebm.<\/p>\n<h3>Performanca<\/h3>\n<ul>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/clickhouse.yandex\/benchmark.html#%5B%2522100000000%2522,%5B%2522ClickHouse%2522,%2522Vertica%2522,%2522MySQL%2522%5D,%5B%25220%2522,%25221%2522%5D%5D\">Benchmark<\/a><\/noindex> p\u00ebr krahasimin e Clickhouse me Vertica dhe MySQL n\u00eb nj\u00eb server me konfigurimin: dy socket\u00eb Intel\u00ae Xeon\u00ae CPU E5-2650 v2 @ 2.60GHz; 128 GiB RAM; md RAID-5 n\u00eb 8 disqe 6TB SATA, ext4.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.altinity.com\/blog\/2017\/6\/20\/clickhouse-vs-redshift\">Benchmark<\/a><\/noindex> p\u00ebr krahasimin e Clickhouse me ruajtjen e t\u00eb dh\u00ebnave n\u00eb re Amazon RedShift.<\/li>\n<li>Pjes\u00eb nga blogu <noindex><a rel=\"nofollow\" href=\"https:\/\/blog.cloudflare.com\/how-cloudflare-analyzes-1m-dns-queries-per-second\/\">Cloudflare p\u00ebr performanc\u00ebn e Clickhouse<\/a><\/noindex>:<\/li>\n<\/ul>\n<p>\n<img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/b6ef9fbad8e8c864a227bcffd97ec0fe.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nBaza e t\u00eb dh\u00ebnave ClickHouse ka nj\u00eb dizajn shum\u00eb t\u00eb thjesht\u00eb - t\u00eb gjitha nyjat n\u00eb kluster kan\u00eb funksionalitet t\u00eb nj\u00ebjt\u00eb dhe p\u00ebrdorin vet\u00ebm ZooKeeper p\u00ebr koordinim. Ne nd\u00ebrtuam nj\u00eb kluster t\u00eb vog\u00ebl me disa nyje dhe ekzekutuam teste, gjat\u00eb t\u00eb cilave zbuluam se sistemi ka nj\u00eb performanc\u00eb mjaftimpresive q\u00eb i p\u00ebrgjigjet avantazheve t\u00eb deklaruara n\u00eb benchmark\u00eb t\u00eb bazave t\u00eb t\u00eb dh\u00ebnave analitike. Ne vendos\u00ebm t\u00eb shqyrtojm\u00eb m\u00eb n\u00eb detaje konceptin q\u00eb q\u00ebndron pas ClickHouse. Pengesa e par\u00eb p\u00ebr hulumtimet ishte mungesa e mjeteve dhe numri i vog\u00ebl i komunitetit ClickHouse, ndaj ne thelluam n\u00eb dizajnin e k\u00ebsaj baze t\u00eb dh\u00ebnash p\u00ebr t\u00eb kuptuar se si funksionon.<\/p>\n<p>ClickHouse nuk mb\u00ebshtet marrjen e t\u00eb dh\u00ebnave direkt nga Kafka, pasi \u00ebsht\u00eb thjesht nj\u00eb baz\u00eb t\u00eb dh\u00ebnash, prandaj ne shkruam nj\u00eb sh\u00ebrbim adaptues t\u00eb vetin n\u00eb gjuh\u00ebn Go. Ai lexonte mesazhet e koduara Cap\u2019n Proto nga Kafka, i transformonte ato n\u00eb TSV dhe i futte n\u00eb ClickHouse n\u00eb grupe p\u00ebrmes HTTP-interface. M\u00eb von\u00eb, ne e riprogramuam k\u00ebt\u00eb sh\u00ebrbim p\u00ebr t\u00eb p\u00ebrdorur bibliotek\u00ebn Go s\u00eb bashku me nd\u00ebrfaqen ton\u00eb t\u00eb ClickHouse p\u00ebr t\u00eb rritur performanc\u00ebn. Gjat\u00eb vler\u00ebsimit t\u00eb performanc\u00ebs s\u00eb pranimit t\u00eb grupeve, ne zbuluam di\u00e7ka t\u00eb r\u00ebnd\u00ebsishme - u zbulua se performanca e ClickHouse varet shum\u00eb nga madh\u00ebsia e grupit, dometh\u00ebn\u00eb nga numri i rreshtave q\u00eb futen nj\u00ebher\u00ebsh. P\u00ebr t\u00eb kuptuar pse ndodh kjo, ne hulumtuam se si ClickHouse ruan t\u00eb dh\u00ebnat.<\/p>\n<p>Motori kryesor, n\u00eb fakt, familja e motor\u00ebve p\u00ebr tabela, t\u00eb p\u00ebrdorur nga ClickHouse p\u00ebr ruajtjen e t\u00eb dh\u00ebnave, \u00ebsht\u00eb MergeTree. Ky motor \u00ebsht\u00eb konceptualisht i ngjash\u00ebm me algoritmin LSM, i aplikuar n\u00eb Google BigTable ose Apache Cassandra, megjithat\u00eb, shmang nd\u00ebrtimin e nj\u00eb tabele t\u00eb p\u00ebrkohshme dhe shkruan t\u00eb dh\u00ebnat drejtp\u00ebrdrejt n\u00eb disk. Kjo i jep atij nj\u00eb kapacitet t\u00eb shk\u00eblqyer t\u00eb shkruarjes, pasi \u00e7do grup i futur renditet vet\u00ebm sipas \u201c\u00e7el\u00ebsit primar\u201d, kompresonohet dhe shkruhet n\u00eb disk p\u00ebr t\u00eb formuar nj\u00eb segment. <\/p>\n<p>Mungesa e tabel\u00ebs s\u00eb memories ose nj\u00eb koncepti t\u00eb k\u00ebtij lloji t\u00eb \"freskis\u00eb\" s\u00eb t\u00eb dh\u00ebnave gjithashtu do t\u00eb thot\u00eb se ato mund t\u00eb shtohen vet\u00ebm, sistemi nuk mb\u00ebshtet ndryshimin ose fshirjen. Aktualisht, m\u00ebnyra e vetme p\u00ebr t\u00eb fshir\u00eb t\u00eb dh\u00ebna \u00ebsht\u00eb t\u00eb fshihen ato sipas muajve kalendarik\u00eb, pasi segmentet kurr\u00eb nuk kalojn\u00eb kufirin e muajit. Ekipa e ClickHouse po punon aktivisht p\u00ebr ta b\u00ebr\u00eb k\u00ebt\u00eb funksion t\u00eb konfiguruesh\u00ebm. Nga ana tjet\u00ebr, kjo e b\u00ebn regjistrimin dhe bashkimin e segmenteve pa konflikte, prandaj kapaciteti i pranimit rritet n\u00eb m\u00ebnyr\u00eb lineare me numrin e shtesave paralele derisa t\u00eb ndodhi ngopja e I\/O ose b\u00ebrthamave. <br \/>\nMegjithat\u00eb, kjo situat\u00eb gjithashtu do t\u00eb thot\u00eb se sistemi nuk \u00ebsht\u00eb i p\u00ebrshtatsh\u00ebm p\u00ebr grupe t\u00eb vogla, prandaj sh\u00ebrbimet Kafka dhe injektor\u00ebt p\u00ebrdoren p\u00ebr buferim. P\u00ebr m\u00eb tep\u00ebr, ClickHouse vazhdon t\u00eb kryej\u00eb bashkimin e segmenteve n\u00eb sfond, k\u00ebshtu q\u00eb shum\u00eb pjes\u00eb t\u00eb vogla informacioni do t\u00eb bashkohen dhe do t\u00eb regjistrohen m\u00eb shum\u00eb her\u00eb, duke rritur k\u00ebshtu intensitetin e regjistrimit. Megjithat\u00eb, tep\u00ebr shum\u00eb pjes\u00eb t\u00eb pap\u00ebrputhshme do t\u00eb shkaktojn\u00eb nj\u00eb ngadal\u00ebsim agresiv t\u00eb shtesave derisa bashkimi t\u00eb vazhdoj\u00eb. Ne kemi zbuluar se kompromisi m\u00eb i mir\u00eb midis pranimit t\u00eb t\u00eb dh\u00ebnave n\u00eb koh\u00eb reale dhe performanc\u00ebs s\u00eb pranimit \u00ebsht\u00eb pranimi n\u00eb tabel\u00eb i nj\u00eb numri t\u00eb kufizuar t\u00eb shtesave n\u00eb sekond\u00eb.<\/p>\n<p>\u00c7el\u00ebsi p\u00ebr performanc\u00ebn e leximit t\u00eb tabelave \u00ebsht\u00eb indeksimi dhe pozita e t\u00eb dh\u00ebnave n\u00eb disk. Pavar\u00ebsisht se sa e shpejt\u00eb \u00ebsht\u00eb p\u00ebrpunimi, kur motorit i duhet t\u00eb skanoj\u00eb terabajt t\u00eb t\u00eb dh\u00ebnave nga disku dhe t\u00eb p\u00ebrdor\u00eb vet\u00ebm nj\u00eb pjes\u00eb t\u00eb tyre, do t\u00eb marr\u00eb koh\u00eb. ClickHouse \u00ebsht\u00eb nj\u00eb depo kolonesh, k\u00ebshtu q\u00eb secili segment p\u00ebrmban nj\u00eb skedar p\u00ebr secil\u00ebn kolon\u00eb me vlera t\u00eb renditura p\u00ebr \u00e7do rresht. K\u00ebshtu, kolona t\u00eb t\u00ebra q\u00eb nuk jan\u00eb t\u00eb pranishme n\u00eb k\u00ebrkes\u00eb mund t\u00eb shp\u00ebtohen fillimisht, dhe pastaj disa qeliza mund t\u00eb procesohen paralelisht me ekzekutimin e vectorizuar. P\u00ebr t\u00eb shmangur skanimin e plot\u00eb, \u00e7do segment ka nj\u00eb skedar t\u00eb vog\u00ebl indeksi. <\/p>\n<p>Duke pastruar se t\u00eb gjitha kolonat jan\u00eb renditur sipas '\u00e7el\u00ebsit primar', skedari i indeksit p\u00ebrmban vet\u00ebm etiketa (rreshtat e kapura) t\u00eb \u00e7do N-rreshti, p\u00ebr t\u00eb qen\u00eb n\u00eb gjendje t'i ruajm\u00eb ato n\u00eb memorie edhe p\u00ebr tabela shum\u00eb t\u00eb m\u00ebdha. P\u00ebr shembull, mund t\u00eb vendosim cil\u00ebsimet e parazgjedhura p\u00ebr 't\u00eb etiketuar \u00e7do 8192-rresht', at\u00ebher\u00eb 'indeksimi i varf\u00ebr' i nj\u00eb tabele me 1 trilion rreshta, e cila leht\u00eb vendoset n\u00eb memorie, do t\u00eb marr\u00eb vet\u00ebm 122,070 karaktere. <\/p>\n<h3>Zhvillimi i sistemit<\/h3>\n<p>\nZhvillimi dhe p\u00ebrmir\u00ebsimi i Clickhouse mund t\u00eb ndiqet n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/yandex\/ClickHouse\/pulse\">Github repo<\/a><\/noindex> dhe t\u00eb sigurohemi q\u00eb procesi i 'rritjes' po ndodh me pasoja mbres\u00ebl\u00ebn\u00ebse. <\/p>\n<p><img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/19211da28e42178d26dff7623689df71.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<\/p>\n<h3>Popullariteti<\/h3>\n<p>\nDuket se popullariteti i Clickhouse po rritet eksponencialisht, ve\u00e7an\u00ebrisht n\u00eb komunitetin rusishtfol\u00ebs. Konferenca e vitit t\u00eb kaluar High Load 2018 (Mosk\u00eb, 8-9 n\u00ebntor 2018) tregoi se monst\u00ebr si vk.com dhe Badoo po p\u00ebrdorin Clickhouse, me t\u00eb cilin futin t\u00eb dh\u00ebna (p.sh., loge) nga dhjet\u00ebra mij\u00ebra server\u00eb nj\u00ebkoh\u00ebsisht. N\u00eb nj\u00eb video 40-minut\u00ebshe <noindex><a rel=\"nofollow\" href=\"https:\/\/www.youtube.com\/watch?v=pbbcMcrQoXw\">Yuri Nasretdinov nga ekipi i VKontakte tregon se si b\u00ebhet kjo.<\/a><\/noindex>S\u00eb shpejti do t\u00eb publikojm\u00eb transkriptin n\u00eb Habr p\u00ebr t\u00eb leht\u00ebsuar pun\u00ebn me materialin.<\/p>\n<h3>Fushat e aplikimit<\/h3>\n<p>\nPas nj\u00eb kohe t\u00eb kaluar n\u00eb k\u00ebrkime, mendoj se ekzistojn\u00eb fusha ku ClickHouse mund t\u00eb jet\u00eb e dobishme ose t\u00eb z\u00ebvend\u00ebsoj\u00eb plot\u00ebsisht zgjidhje t\u00eb tjera m\u00eb tradicionale dhe t\u00eb njohura, si MySQL, PostgreSQL, ELK, Google Big Query, Amazon RedShift, TimescaleDB, Hadoop, MapReduce, Pinot dhe Druid. M\u00eb posht\u00eb po paraqesim detajet p\u00ebr p\u00ebrdorimin e ClickHouse p\u00ebr modernizimin ose z\u00ebvend\u00ebsimin e plot\u00eb t\u00eb bazave t\u00eb t\u00eb dh\u00ebnave t\u00eb m\u00ebsip\u00ebrme. <\/p>\n<h3>Zgjerimi i mund\u00ebsive t\u00eb MySQL dhe PostgreSQL<\/h3>\n<p>\nS\u00eb fundmi kemi z\u00ebvend\u00ebsuar pjes\u00ebrisht MySQL me ClickHouse p\u00ebr platform\u00ebn e buletineve informative <noindex><a rel=\"nofollow\" href=\"https:\/\/www.mautic.org\/\">Mautic newsletter<\/a><\/noindex>Problemi ishte se MySQL p\u00ebr shkak t\u00eb nj\u00eb dizajni t\u00eb padishet regjistronte secil\u00ebn let\u00ebr t\u00eb d\u00ebrguar dhe \u00e7do lidhje n\u00eb k\u00ebt\u00eb let\u00ebr me nj\u00eb hash base64, duke krijuar nj\u00eb tabel\u00eb t\u00eb madhe MySQL (email_stats). Pas d\u00ebrgimit t\u00eb 10 milion\u00ebve email-e p\u00ebr abonent\u00ebt e sh\u00ebrbimit, kjo tabel\u00eb zinte 150 GB hap\u00ebsir\u00eb skedar\u00ebsh, dhe MySQL filloi t\u00eb 'ngadal\u00ebsohej' n\u00eb pyetje t\u00eb thjeshta. P\u00ebr t\u00eb rregulluar problemin e hap\u00ebsir\u00ebs s\u00eb skedar\u00ebve, ne p\u00ebrdor\u00ebm me sukses kompresimin e tabel\u00ebs InnoDB, e cila e zvog\u00ebloi at\u00eb me 4 her\u00eb. Megjithat\u00eb, prap\u00eb nuk ka kuptim t\u00eb ruash m\u00eb shum\u00eb se 20-30 milion email-e n\u00eb MySQL vet\u00ebm p\u00ebr t\u00eb lexuar historin\u00eb, pasi \u00e7do k\u00ebrkes\u00eb e thjesht\u00eb, q\u00eb p\u00ebr ndonj\u00eb arsye duhet t\u00eb kryej\u00eb nj\u00eb skanim t\u00eb plot\u00eb, \u00e7on n\u00eb swap dhe nj\u00eb ngarkes\u00eb t\u00eb madhe n\u00eb I\/O, mbi t\u00eb cil\u00ebn rregullisht merrnim paralajm\u00ebrime nga Zabbix.<\/p>\n<p><img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/11b3ee4b1a8b7c9457bd3871bd12049f.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nClickhouse p\u00ebrdor dy algoritme kompresimi q\u00eb reduktojn\u00eb volumin e t\u00eb dh\u00ebnave me rreth <noindex><a rel=\"nofollow\" href=\"https:\/\/www.altinity.com\/blog\/2017\/11\/21\/compression-in-clickhouse\">3-4 her\u00eb<\/a><\/noindex>, por n\u00eb k\u00ebt\u00eb rast t\u00eb ve\u00e7ant\u00eb t\u00eb dh\u00ebnat ishin ve\u00e7an\u00ebrisht 't\u00eb kompresueshme'. <\/p>\n<p><img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/d192502073d57967620aa07da0bbfa0c.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<\/p>\n<h3>Z\u00ebvend\u00ebsimi i ELK<\/h3>\n<p>\nDuke u bazuar n\u00eb p\u00ebrvoj\u00ebn time, staku ELK (ElasticSearch, Logstash dhe Kibana, n\u00eb k\u00ebt\u00eb rast ElasticSearch) k\u00ebrkon shum\u00eb m\u00eb shum\u00eb burime p\u00ebr t\u00eb funksionuar sesa \u00ebsht\u00eb e nevojshme p\u00ebr t\u00eb ruajtur log-et. ElasticSearch \u00ebsht\u00eb nj\u00eb motor i shk\u00eblqyer n\u00ebse ke nevoj\u00eb p\u00ebr nj\u00eb k\u00ebrkim t\u00eb plot\u00ebtekstual n\u00eb log-e (dhe un\u00eb nuk mendoj se realisht e ke nevoj\u00ebn), por m\u00eb intereson se si de facto u b\u00eb standardi i motorit p\u00ebr menaxhimin e log-eve. Performanca e saj e pranimit e kombinuar me Logstash na krijonte probleme edhe n\u00eb ngarkesa relativisht t\u00eb vogla dhe k\u00ebrkonte shtimin e gjithnj\u00eb e m\u00eb shum\u00eb memorie t\u00eb p\u00ebrkohshme dhe hap\u00ebsir\u00eb disku. Si nj\u00eb DB, Clickhouse \u00ebsht\u00eb m\u00eb i mir\u00eb se ElasticSearch p\u00ebr shkak t\u00eb arsyeve t\u00eb m\u00ebposhtme:<\/p>\n<ul>\n<li>Mb\u00ebshtetje p\u00ebr dialektin SQL;<\/li>\n<li>Nj\u00eb shkall\u00eb m\u00eb e mir\u00eb kompresimi t\u00eb dh\u00ebnash t\u00eb ruajtura;<\/li>\n<li>Mb\u00ebshtetje p\u00ebr k\u00ebrkimin me shprehje t\u00eb rregullta Regex n\u00eb vend t\u00eb k\u00ebrkimit t\u00eb plot\u00ebtekstual;<\/li>\n<li>Planifikim m\u00eb t\u00eb p\u00ebrmir\u00ebsuar t\u00eb pyetjeve dhe performanc\u00eb m\u00eb t\u00eb lart\u00eb t\u00eb p\u00ebrgjithshme.<\/li>\n<\/ul>\n<p>\nAktualisht, problemi m\u00eb i madh q\u00eb del kur krahasohet ClickHouse me ELK \u00ebsht\u00eb mungesa e zgjidhjeve p\u00ebr ngarkimin e log-eve, si dhe mungesa e dokumentacionit dhe udh\u00ebzuesve mbi k\u00ebt\u00eb tem\u00eb. Megjithat\u00eb, \u00e7do p\u00ebrdorues mund t\u00eb konfiguroj\u00eb ELK me udh\u00ebzimin e Digital Ocean, q\u00eb \u00ebsht\u00eb shum\u00eb e r\u00ebnd\u00ebsishme p\u00ebr nj\u00eb implementim t\u00eb shpejt\u00eb t\u00eb teknologjive t\u00eb tilla. Aty ka nj\u00eb motor DB, por ende nuk ka Filebeat p\u00ebr ClickHouse. Po, aty \u00ebsht\u00eb pranuar. <noindex><a rel=\"nofollow\" href=\"https:\/\/www.fluentd.org\/\">fluentd<\/a><\/noindex> dhe sistemi p\u00ebr pun\u00ebn me logjet <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/flant\/loghouse\">loghouse<\/a><\/noindex>, ekziston nj\u00eb mjet <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/Altinity\/clicktail\">clicktail<\/a><\/noindex> p\u00ebr t\u00eb futur n\u00eb ClickHouse t\u00eb dh\u00ebnat e skedar\u00ebve t\u00eb logjeve, por gjith\u00e7ka k\u00ebrkon m\u00eb shum\u00eb koh\u00eb. Megjithat\u00eb, ClickHouse mbetet lider p\u00ebr shkak t\u00eb thjesht\u00ebsis\u00eb s\u00eb tij, prandaj edhe fillestar\u00ebt e instalojn\u00eb leht\u00ebsisht dhe fillojn\u00eb p\u00ebrdorimin e plot\u00eb brenda 10 minutash. <\/p>\n<p>Duke preferuar zgjidhjet minimalistike, p\u00ebrpiqem t\u00eb p\u00ebrdor FluentBit, nj\u00eb mjet p\u00ebr shkarkimin e njohjeve me nj\u00eb p\u00ebrdorim shum\u00eb t\u00eb vog\u00ebl memorie, s\u00eb bashku me ClickHouse, duke u munduar t\u00eb shmang p\u00ebrdorimin e Kafka-s. Megjithat\u00eb, do t\u00eb ishin t\u00eb nevojshme t\u00eb p\u00ebrmir\u00ebsohen disa t\u00eb papajtueshm\u00ebri t\u00eb vogla, si <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/fluent\/fluent-bit\/issues\/848\">problemet me formatin e dat\u00ebs<\/a><\/noindex>, para se t\u00eb mund t\u00eb b\u00ebhet pa nj\u00eb sloj proksi q\u00eb konverton t\u00eb dh\u00ebnat nga FluentBit n\u00eb ClickHouse.<\/p>\n<p>Si nj\u00eb alternativ\u00eb p\u00ebr Kibana, mund t\u00eb p\u00ebrdoret ClickHouse si backend <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/Vertamedia\/clickhouse-grafana\">N\u00ebse tashm\u00eb e dini se \u00e7far\u00eb \u00ebsht\u00eb analiza e grupeve dhe se si ta b\u00ebni n\u00eb SQL, kaloni menj\u00ebher\u00eb n\u00eb seksionin e fundit.<\/a><\/noindex>. Sa kam kuptuar, k\u00ebt\u00eb mund t\u00eb krijoj\u00eb probleme n\u00eb performanc\u00eb gjat\u00eb renderimit t\u00eb nj\u00eb sasie t\u00eb madhe t\u00eb t\u00eb dh\u00ebnave, ve\u00e7an\u00ebrisht me versionet m\u00eb t\u00eb vjetra t\u00eb Grafana. N\u00eb Qwintry ende nuk e kemi provuar k\u00ebt\u00eb, por ankesat p\u00ebr k\u00ebt\u00eb d\u00ebrgohen her\u00eb pas here n\u00eb kanalin e suportit t\u00eb ClickHouse n\u00eb Telegram. <\/p>\n<h3>Z\u00ebvend\u00ebsimi i Google Big Query dhe Amazon RedShift (zgjidhje p\u00ebr kompani t\u00eb m\u00ebdha)<\/h3>\n<p>\nOpsioni ideal p\u00ebr t\u00eb p\u00ebrdorur BigQuery \u00ebsht\u00eb t\u00eb ngarkoni 1 TB t\u00eb dh\u00ebnash JSON dhe t\u00eb kryeni k\u00ebrkesa analitike mbi to. Big Query \u00ebsht\u00eb nj\u00eb produkt i shk\u00eblqyer, shkall\u00ebzimi i t\u00eb cilit \u00ebsht\u00eb i v\u00ebshtir\u00eb p\u00ebr t'u n\u00ebnvlersuar. Ky \u00ebsht\u00eb nj\u00eb softuer shum\u00eb m\u00eb i nd\u00ebrlikuar se ClickHouse, q\u00eb funksionon n\u00eb nj\u00eb klas\u00ebr t\u00eb brendsh\u00ebm, por nga perspektiva e klientit ka shum\u00eb ngjashm\u00ebri me ClickHouse. BigQuery mund t\u00eb b\u00ebhet shpejt <\/p>\n<p>ClickHouse \u00ebsht\u00eb zgjedhja m\u00eb e mir\u00eb kur ju b\u00ebni shum\u00eb k\u00ebrkesa p\u00ebrpunuese t\u00eb kushtueshme. Sa m\u00eb shum\u00eb k\u00ebrkesa SELECT t\u00eb b\u00ebni \u00e7do dit\u00eb \u2014 aq m\u00eb shum\u00eb ka kuptim t\u00eb z\u00ebvend\u00ebsoni Big Query me ClickHouse, sepse nj\u00eb z\u00ebvend\u00ebsim i till\u00eb do t'ju kursej\u00eb mij\u00ebra dollar\u00eb n\u00ebse b\u00ebhet fjal\u00eb p\u00ebr disa terabajt t\u00eb dh\u00ebnash t\u00eb p\u00ebrpunuara. Kjo nuk i referohet t\u00eb dh\u00ebnave t\u00eb ruajtura, p\u00ebrpunimi i t\u00eb cilave n\u00eb Big Query \u00ebsht\u00eb relativisht i lir\u00eb.<\/p>\n<p>N\u00eb nj\u00eb artikull nga bashk\u00ebthemeluesi i kompanis\u00eb Altinity, Aleksand\u00ebr Zaitsev <noindex><a rel=\"nofollow\" href=\"https:\/\/www.altinity.com\/blog\/2017\/10\/23\/migration-to-clickhouse\">\"Kalimi n\u00eb ClickHouse\"<\/a><\/noindex> flitet p\u00ebr avantazhet e k\u00ebsaj migrimi t\u00eb DBMS.<\/p>\n<h3>Z\u00ebvend\u00ebsimi i TimescaleDB<\/h3>\n<p>\nTimescaleDB \u00ebsht\u00eb nj\u00eb zgjerim i PostgreSQL, i cili optimizon pun\u00ebn me radh\u00ebt e koh\u00ebs n\u00eb nj\u00eb baz\u00eb t\u00eb zakonshme t\u00eb dh\u00ebnash.<noindex><a rel=\"nofollow\" href=\"https:\/\/docs.timescale.com\/v1.0\/introduction\">https:\/\/docs.timescale.com\/v1.0\/introduction<\/a><\/noindex>, <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/zabbix\/blog\/458530\/\">https:\/\/habr.com\/ru\/company\/zabbix\/blog\/458530\/<\/a><\/noindex>). <\/p>\n<p>Megjith\u00ebse ClickHouse nuk \u00ebsht\u00eb nj\u00eb konkurrues serioz n\u00eb ni\u00e7en e radh\u00ebve t\u00eb koh\u00ebs, struktura e koloneve dhe ekzekutimi vektorial i k\u00ebrkesave e b\u00ebjn\u00eb at\u00eb shum\u00eb m\u00eb t\u00eb shpejt\u00eb se TimescaleDB n\u00eb shumic\u00ebn e rasteve p\u00ebr p\u00ebrpunimin analitik. N\u00eb k\u00ebt\u00eb kuptim, performanca e pranimit t\u00eb t\u00eb dh\u00ebnave me paketa n\u00eb ClickHouse \u00ebsht\u00eb rreth 3 her\u00eb m\u00eb e lart\u00eb, p\u00ebrve\u00e7 k\u00ebsaj, p\u00ebrdor ai 20 her\u00eb m\u00eb pak hap\u00ebsir\u00eb disk, gj\u00eb q\u00eb \u00ebsht\u00eb v\u00ebrtet e r\u00ebnd\u00ebsishme p\u00ebr p\u00ebrpunimin e volumeve t\u00eb m\u00ebdha t\u00eb t\u00eb dh\u00ebnave historike.<noindex><a rel=\"nofollow\" href=\"https:\/\/www.altinity.com\/blog\/ClickHouse-for-time-series\">https:\/\/www.altinity.com\/blog\/ClickHouse-for-time-series<\/a><\/noindex>.<\/p>\n<p>N\u00eb ndryshim nga ClickHouse, m\u00ebnyra e vetme p\u00ebr t\u00eb kursyer pak hap\u00ebsir\u00eb disku n\u00eb TimescaleDB \u00ebsht\u00eb p\u00ebrdorimi i ZFS ose sistemeve t\u00eb ngjashme t\u00eb skedar\u00ebve.<\/p>\n<p>P\u00ebrdit\u00ebsimet e ardhshme t\u00eb ClickHouse, me siguri do t\u00eb sjellin kompresimin delta, e cila do ta b\u00ebj\u00eb at\u00eb edhe m\u00eb t\u00eb p\u00ebrshtatsh\u00ebm p\u00ebr p\u00ebrpunimin dhe ruajtjen e t\u00eb dh\u00ebnave t\u00eb radh\u00ebve t\u00eb koh\u00ebs. TimescaleDB mund t\u00eb b\u00ebhet nj\u00eb zgjedhje m\u00eb e mir\u00eb se ClickHouse 'i past\u00ebr' n\u00eb rastet e m\u00ebposhtme:<\/p>\n<ul>\n<li>instalime t\u00eb vogla me nj\u00eb memorie shum\u00eb t\u00eb vog\u00ebl (&lt;3 GB);<\/li>\n<li>nj\u00eb num\u00ebr i madh INSERT-esh t\u00eb vogla q\u00eb nuk d\u00ebshironi t'i bufferoni n\u00eb fragmente t\u00eb m\u00ebdha;<\/li>\n<li>konsistenc\u00eb, uniformitet dhe k\u00ebrkesa A\u0421ID m\u00eb t\u00eb mira;<\/li>\n<li>mb\u00ebshtetje p\u00ebr PostGIS;<\/li>\n<li>bashkimi me tabelat ekzistuese t\u00eb PostgreSQL, pasi n\u00eb thelb Timescale DB \u00ebsht\u00eb PostgreSQL.<\/li>\n<\/ul>\n<p><\/p>\n<h3>Konkurrenca me sistemi Hadoop dhe MapReduce.<\/h3>\n<p>\nHadoop dhe produkte t\u00eb tjera MapReduce mund t\u00eb kryejn\u00eb shum\u00eb llogaritje komplekse, por zakonisht funksionojn\u00eb me vonesa t\u00eb m\u00ebdha. ClickHouse e zgjidh k\u00ebt\u00eb problem duke procesuar terabajt\u00eb e t\u00eb dh\u00ebnave dhe duke ofruar rezultate pothuajse menj\u00ebher\u00eb. K\u00ebshtu, ClickHouse \u00ebsht\u00eb shum\u00eb m\u00eb efikas p\u00ebr kryerjen e hetimeve analitike t\u00eb shpejta dhe interaktive, q\u00eb duhet t\u00eb t\u00ebrheq\u00eb specialist\u00ebt e p\u00ebrpunimit t\u00eb t\u00eb dh\u00ebnave.<\/p>\n<h3>Konkurrenca me Pinot dhe Druid.<\/h3>\n<p>\nKonkurrent\u00ebt m\u00eb t\u00eb af\u00ebrt t\u00eb ClickHouse jan\u00eb produktet open source me struktur\u00eb kolone dhe t\u00eb shkall\u00ebzuar linearisht Pinot dhe Druid. Nj\u00eb krahasim i shk\u00eblqyer i k\u00ebtyre sistemeve \u00ebsht\u00eb publikuar n\u00eb artikullin <noindex><a rel=\"nofollow\" href=\"https:\/\/medium.com\/@leventov\/comparison-of-the-open-source-olap-systems-for-big-data-ClickHouse-druid-and-pinot-8e042a5ed1c7\">Roman Leventov<\/a><\/noindex> nga 1 shkurt 2018. <\/p>\n<p><img decoding=\"async\" alt=\"P\u00ebrdorimi i Clickhouse si z\u00ebvend\u00ebsim p\u00ebr ELK, Big Query dhe TimescaleDB\" src=\"\/wp-content\/uploads\/2020\/01\/fe58814aa97b287b70c2f724b72b448a.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nKy artikull k\u00ebrkon p\u00ebrdit\u00ebsim \u2013 ai thekson se ClickHouse nuk mb\u00ebshtet operacionet UPDATE dhe DELETE, gj\u00eb q\u00eb nuk \u00ebsht\u00eb krejt\u00ebsisht e sakt\u00eb p\u00ebr versionet e fundit.<\/p>\n<p>Nuk kemi mjaftuesh\u00ebm p\u00ebrvoj\u00eb n\u00eb pun\u00ebn me k\u00ebto DBMS, por m\u00eb shum\u00eb se gjith\u00e7ka m\u00eb shqet\u00ebson kompleksiteti i infrastruktur\u00ebs s\u00eb p\u00ebrdorur p\u00ebr t\u00eb nisur Druid dhe Pinot \u2014 \u00ebsht\u00eb nj\u00eb grumbull \u00abpjes\u00ebsh n\u00eb l\u00ebvizje\u00bb, t\u00eb rrethuar nga Java nga t\u00eb gjitha an\u00ebt.<\/p>\n<p>Druid dhe Pinot jan\u00eb projekte inkubator t\u00eb Apache, ecuria e t\u00eb cil\u00ebve ndiqet n\u00eb detaje nga Apache n\u00eb faqet e projekteve t\u00eb tyre n\u00eb GitHub. Pinot doli n\u00eb inkubator n\u00eb tetor 2018, nd\u00ebrsa Druid lindi 8 muaj m\u00eb her\u00ebt - n\u00eb shkurt.<\/p>\n<p>Mungesa e informacionit rreth m\u00ebnyr\u00ebs si funksionon AFS m\u00eb jep disa pyetje, ndoshta t\u00eb gabuara. M\u00eb intereson, a e kan\u00eb v\u00ebn\u00eb re autor\u00ebt e Pinot se Fondacioni Apache \u00ebsht\u00eb m\u00eb i predispozuar ndaj Druid, dhe a e ka shkaktuar kjo marr\u00ebdh\u00ebnie me konkurentin ndjenj\u00ebn e xhelozis\u00eb? A do t\u00eb ngadal\u00ebsohet zhvillimi i Druid dhe do t\u00eb p\u00ebrshpejtohet ai i Pinot, n\u00ebse sponsor\u00ebt q\u00eb mb\u00ebshtesin t\u00eb parin, papritmas interesohen p\u00ebr t\u00eb dytin?<\/p>\n<h3>Disavantazhet e ClickHouse<\/h3>\n<p>\nPjekuria: \u00ebsht\u00eb e qart\u00eb se kjo ende \u00ebsht\u00eb nj\u00eb teknologji interesante, por n\u00eb \u00e7do rast, nuk ka asgj\u00eb t\u00eb ngjashme n\u00eb DBMS-t\u00eb e tjera kolonuese. <\/p>\n<p>Insertet e vogla funksionojn\u00eb keq me shpejt\u00ebsi t\u00eb lart\u00eb: insertet duhet t\u00eb ndahen n\u00eb copa t\u00eb m\u00ebdha, sepse performanca e insert\u00ebve t\u00eb vogla zvog\u00eblohet proporcionalisht me numrin e kolonave n\u00eb secil\u00ebn rresht. K\u00ebshtu ruhet t\u00eb dh\u00ebnat n\u00eb disk n\u00eb ClickHouse - secila kolone do t\u00eb thot\u00eb 1 skedar ose m\u00eb shum\u00eb, prandaj p\u00ebr t\u00eb futur 1 rresht q\u00eb p\u00ebrmban 100 kolona, duhet t\u00eb hapet dhe shkruhet t\u00eb pakt\u00ebn 100 skedar\u00eb. Kjo \u00ebsht\u00eb arsyeja pse \u00ebsht\u00eb e nevojshme nj\u00eb nd\u00ebrmjet\u00ebs p\u00ebr tamponimin e insert\u00ebve (n\u00ebse vet\u00eb klienti nuk ofron tamponimin) - zakonisht kjo \u00ebsht\u00eb Kafka ose ndonj\u00eb sistem menaxhimi t\u00eb radh\u00ebve. Mund t\u00eb p\u00ebrdoret gjithashtu motorri Buffer table, p\u00ebr t\u00eb kopjuar m\u00eb von\u00eb copa t\u00eb m\u00ebdha t\u00eb t\u00eb dh\u00ebnave n\u00eb tabelat MergeTree.<\/p>\n<p>Lidhjet e tabelave jan\u00eb t\u00eb kufizuara nga memorie e serverit, por t\u00eb pakt\u00ebn, ato ekzistojn\u00eb atje! P\u00ebr shembull, Druid dhe Pinot nuk kan\u00eb fare lidhje t\u00eb tilla, sepse ato jan\u00eb t\u00eb v\u00ebshtira p\u00ebr t'u realizuar direkt n\u00eb sistemet e shp\u00ebrndara, t\u00eb cilat nuk mb\u00ebshtesin zhvendosjen e copave t\u00eb m\u00ebdha t\u00eb t\u00eb dh\u00ebnave midis nyjeve. <\/p>\n<h3>P\u00ebrfundimet<\/h3>\n<p>\nN\u00eb vitet e ardhshme, ne planifikojm\u00eb t\u00eb p\u00ebrdorim gjer\u00ebsisht ClickHouse n\u00eb Qwintry, pasi kjo baz\u00eb t\u00eb dh\u00ebnash ofron nj\u00eb balanc\u00eb t\u00eb shk\u00eblqyer midis performanc\u00ebs, kostove t\u00eb ulta, shkall\u00ebzueshm\u00ebris\u00eb dhe thjesht\u00ebsis\u00eb. Jam pothuajse i sigurt se ajo do t\u00eb filloj\u00eb t\u00eb p\u00ebrhapej shpejt, sapo komuniteti ClickHouse t\u00eb gjej\u00eb m\u00eb shum\u00eb m\u00ebnyra p\u00ebr ta p\u00ebrdorur n\u00eb instalime t\u00eb vogla dhe mesatare.<\/p>\n<h3>Pak reklam\u00eb \ud83d\ude42<\/h3>\n<p>\nFaleminderit q\u00eb po q\u00ebndroni me ne. Ju p\u00eblqen artikujt tan\u00eb? Doni t\u00eb shihni m\u00eb shum\u00eb materiale interesante? Na mb\u00ebshtesni duke b\u00ebr\u00eb nj\u00eb porosi ose duke rekomanduar tek miqt\u00eb tuaj, <noindex><a rel=\"nofollow\" href=\"https:\/\/ua-hosting.company\/cloudvps\/nl\">VPS cloud p\u00ebr zhvillues nga $4.99<\/a><\/noindex>, <b>nj\u00eb analog unik i server\u00ebve entry-level q\u00eb e kemi shpikur p\u00ebr Ju:<\/b> <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/company\/ua-hosting\/blog\/347386\/\">E gjith\u00eb e v\u00ebrteta n\u00eb lidhje me VPS (KVM) E5-2697 v3 (6 B\u00ebrthama) 10GB DDR4 480GB SSD 1Gbps nga $19 ose si ta ndajm\u00eb sakt\u00ebsisht serverin?<\/a><\/noindex> (opcionet me RAID1 dhe RAID10, deri n\u00eb 24 b\u00ebrthama dhe deri n\u00eb 40GB DDR4 jan\u00eb t\u00eb disponueshme).<\/p>\n<p><b>Dell R730xd dyfish m\u00eb i lir\u00eb n\u00eb qend\u00ebr t\u00eb t\u00eb dh\u00ebnave Equinix Tier IV n\u00eb Amsterdam?<\/b> Vet\u00ebm te ne <b><noindex><a rel=\"nofollow\" href=\"https:\/\/ua-hosting.company\/serversnl\">2 x Intel TetraDeca-Core Xeon 2x E5-2697v3 2.6GHz 14C 64GB DDR4 4x960GB SSD 1Gbps 100 TB nga $199<\/a><\/noindex> n\u00eb Holand\u00eb! <b>Dell R420 \u2014 2x E5-2430 2.2Ghz 6C 128GB DDR3 2x960GB SSD 1Gbps 100TB \u2014 nga $99!<\/b><\/b> Lexoni rreth <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/company\/ua-hosting\/blog\/329618\/\">Si t\u00eb nd\u00ebrtoni nj\u00eb infrastruktur\u00eb t\u00eb klas\u00ebs korporative me p\u00ebrdorimin e server\u00ebve Dell R730xd E5-2650 v4 me \u00e7mim 9000 euro p\u00ebr pak para?<\/a><\/noindex><br \/>\n<br \/>Burimi: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/ua-hosting\/blog\/483112\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>Clickhouse \u2014 \u044d\u0442\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432\u0430\u044f \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u0431\u0430\u0437\u0430\u043c\u0438 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043e\u043d\u043b\u0430\u0439\u043d \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 (OLAP) \u0441 \u043e\u0442\u043a\u0440\u044b\u0442\u044b\u043c \u0438\u0441\u0445\u043e\u0434\u043d\u044b\u043c \u043a\u043e\u0434\u043e\u043c, \u0441\u043e\u0437\u0434\u0430\u043d\u043d\u0430\u044f \u042f\u043d\u0434\u0435\u043a\u0441\u043e\u043c. \u0415\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442 \u042f\u043d\u0434\u0435\u043a\u0441, CloudFlare, VK.com, Badoo \u0438 \u0434\u0440\u0443\u0433\u0438\u0435 \u0441\u0435\u0440\u0432\u0438\u0441\u044b \u043f\u043e \u0432\u0441\u0435\u043c\u0443 \u043c\u0438\u0440\u0443 \u0434\u043b\u044f \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u043e\u0431\u044a\u0435\u043c\u043e\u0432 \u0434\u0430\u043d\u043d\u044b\u0445 (\u0432\u0441\u0442\u0430\u0432\u043a\u0430 \u0442\u044b\u0441\u044f\u0447 \u0441\u0442\u0440\u043e\u043a \u0432 \u0441\u0435\u043a\u0443\u043d\u0434\u0443 \u0438\u043b\u0438 \u043f\u0435\u0442\u0430\u0431\u0430\u0439\u0442\u044b \u0434\u0430\u043d\u043d\u044b\u0445, \u0445\u0440\u0430\u043d\u044f\u0449\u0438\u0445\u0441\u044f \u043d\u0430 \u0434\u0438\u0441\u043a\u0435). \u0412 \u043e\u0431\u044b\u0447\u043d\u043e\u0439, \u00ab\u0441\u0442\u0440\u043e\u043a\u043e\u0432\u043e\u0439\u00bb \u0421\u0423\u0411\u0414, \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-54918","post","type-post","status-publish","format-standard","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"Clickhouse \u2014 \u044d\u0442\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432\u0430\u044f \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u0431\u0430\u0437\u0430\u043c\u0438 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043e\u043d\u043b\u0430\u0439\u043d \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 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