{"id":476326,"date":"2023-08-09T07:28:31","date_gmt":"2023-08-09T07:28:31","guid":{"rendered":""},"modified":"2023-09-05T11:12:28","modified_gmt":"2023-09-05T11:12:28","slug":"columnstore-indexes-in-sql","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/columnstore-indexes-in-sql\/","title":{"rendered":"SQL&#039;de s\u00fctun deposu dizinleri"},"content":{"rendered":"<h2>girii\u015f<\/h2>\n<p>SQL&#039;deki Columnstore dizinleri, belirli senaryolarda sorgu performans\u0131n\u0131 ve veri s\u0131k\u0131\u015ft\u0131rmas\u0131n\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131rabilen \u00f6zel bir veritaban\u0131 \u00f6zelli\u011fidir. Veri ambar\u0131 ve analitik i\u015f y\u00fcklerinde b\u00fcy\u00fck hacimli verilerin i\u015flenmesiyle ilgili performans ve depolama zorluklar\u0131n\u0131 gidermek \u00fczere tasarland\u0131lar. Bu makalede SQL&#039;deki Columnstore dizinlerinin ge\u00e7mi\u015fi, i\u00e7 yap\u0131s\u0131, temel \u00f6zellikleri, t\u00fcrleri, kullan\u0131m\u0131 ve gelece\u011fe y\u00f6nelik perspektifleri ele al\u0131nacakt\u0131r.<\/p>\n<h2>Tarih ve K\u00f6ken<\/h2>\n<p>SQL&#039;deki Columnstore dizinleri ilk olarak Microsoft taraf\u0131ndan SQL Server 2012&#039;nin piyasaya s\u00fcr\u00fclmesiyle tan\u0131t\u0131ld\u0131. Columnstore dizinlerinin temelini olu\u015fturan s\u00fctunlu depolama kavram\u0131n\u0131n ge\u00e7mi\u015fi 1970&#039;lere kadar uzan\u0131yor. Ancak 2000&#039;li y\u0131llar\u0131n ortalar\u0131nda b\u00fcy\u00fck verinin artmas\u0131 ve daha iyi veri s\u0131k\u0131\u015ft\u0131rma ve sorgu performans\u0131na duyulan ihtiya\u00e7la birlikte pop\u00fclerlik kazand\u0131. Microsoft&#039;un Columnstore dizinlerini uygulamas\u0131 bu alanda \u00f6nemli bir ilerlemeye i\u015faret etti ve bu, onu bir\u00e7ok modern veritaban\u0131 y\u00f6netim sisteminde standart bir \u00f6zellik haline getirdi.<\/p>\n<h2>SQL&#039;deki Columnstore Dizinleri Hakk\u0131nda Ayr\u0131nt\u0131l\u0131 Bilgi<\/h2>\n<p>Columnstore dizini, verileri geleneksel sat\u0131r tabanl\u0131 depolama yerine s\u00fctunlara g\u00f6re d\u00fczenleyen ve saklayan bir teknolojidir. Sat\u0131r tabanl\u0131 depolamada, bir tablodaki veriler sat\u0131r sat\u0131r depolan\u0131r ve al\u0131n\u0131r. Bunun aksine, Columnstore dizinlerinde, her bir s\u00fctundaki veriler birlikte depolan\u0131r ve i\u015flenir; bu da analitik sorgular i\u00e7in geli\u015fmi\u015f s\u0131k\u0131\u015ft\u0131rma ve daha iyi performans sa\u011flar.<\/p>\n<p>Columnstore dizinleri, sorgular\u0131n b\u00fcy\u00fck miktarda veri ve toplama i\u00e7erdi\u011fi okuma yo\u011funluklu i\u015f y\u00fckleri i\u00e7in \u00e7ok uygundur. B\u00fcy\u00fck veri k\u00fcmelerinin taranmas\u0131n\u0131 ve i\u015flenmesini gerektiren raporlamay\u0131, veri ambar\u0131n\u0131 ve analitik sorgular\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde h\u0131zland\u0131rabilirler.<\/p>\n<h2>\u0130\u00e7 Yap\u0131 ve \u0130\u015fleyi\u015f<\/h2>\n<p>Columnstore dizininin i\u00e7 yap\u0131s\u0131 s\u00fctun b\u00f6l\u00fcmlerine ve s\u00f6zl\u00fcklere dayan\u0131r. S\u00fctun segmenti, her s\u00fctun i\u00e7in s\u0131k\u0131\u015ft\u0131r\u0131lm\u0131\u015f bir veri birimidir. Veri al\u0131m\u0131n\u0131 kolayla\u015ft\u0131rmak i\u00e7in minimum ve maksimum de\u011ferleri i\u00e7eren bir dizi meta verinin yan\u0131 s\u0131ra bir dizi de\u011ferden olu\u015fur.<\/p>\n<p>S\u00f6zl\u00fckler bir s\u00fctundaki yinelenen de\u011ferleri s\u0131k\u0131\u015ft\u0131rmak i\u00e7in kullan\u0131l\u0131r. S\u00f6zl\u00fck, ger\u00e7ek de\u011ferleri birden \u00e7ok kez depolamak yerine benzersiz de\u011ferleri ve bunlara kar\u015f\u0131l\u0131k gelen kimlikleri saklayarak depolama gereksinimlerini azalt\u0131r ve sorgu performans\u0131n\u0131 art\u0131r\u0131r.<\/p>\n<p>Columnstore dizini, b\u00fcy\u00fck veri k\u00fcmelerini verimli bir \u015fekilde taramak ve i\u015flemek i\u00e7in toplu i\u015fleme ad\u0131 verilen bir teknikten yararlan\u0131r. Ayn\u0131 anda birden fazla sat\u0131rda i\u015flem ger\u00e7ekle\u015ftirerek analitik sorgular\u0131n performans\u0131n\u0131 art\u0131r\u0131r.<\/p>\n<h2>SQL&#039;deki Columnstore Dizinlerinin Temel \u00d6zellikleri<\/h2>\n<ul>\n<li>\n<p><strong>Veri s\u0131k\u0131\u015ft\u0131rma<\/strong>: Columnstore dizinleri, s\u00fctunlu depolama formatlar\u0131 ve s\u00f6zl\u00fck tabanl\u0131 s\u0131k\u0131\u015ft\u0131rma teknikleri sayesinde veri depolama gereksinimlerini \u00f6nemli \u00f6l\u00e7\u00fcde azalt\u0131r.<\/p>\n<\/li>\n<li>\n<p><strong>Toplu Modda \u0130\u015fleme<\/strong>: Verileri sat\u0131r sat\u0131r yerine gruplar halinde i\u015fleme yetene\u011fi, b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in daha h\u0131zl\u0131 sorgu y\u00fcr\u00fct\u00fclmesine olanak tan\u0131r.<\/p>\n<\/li>\n<li>\n<p><strong>A\u015fa\u011f\u0131 A\u00e7\u0131lan Y\u00fcklemi<\/strong>: Columnstore dizinleri y\u00fcklem a\u015fa\u011f\u0131 itmeyi destekler; bu, sorgu iyile\u015ftiricinin verileri al\u0131nmadan \u00f6nce depolama d\u00fczeyinde filtreleyebilece\u011fi ve sorgu performans\u0131n\u0131 daha da art\u0131rabilece\u011fi anlam\u0131na gelir.<\/p>\n<\/li>\n<li>\n<p><strong>Vekt\u00f6rle\u015ftirilmi\u015f Y\u00fcr\u00fctme<\/strong>: T\u00fcm veri vekt\u00f6rleri \u00fczerindeki i\u015flemler e\u015f zamanl\u0131 olarak ger\u00e7ekle\u015ftirilir ve bu da sorgu y\u00fcr\u00fctme h\u0131zlar\u0131n\u0131n artmas\u0131n\u0131 sa\u011flar.<\/p>\n<\/li>\n<\/ul>\n<h2>SQL&#039;de Columnstore Dizin T\u00fcrleri<\/h2>\n<p>SQL&#039;de iki t\u00fcr Columnstore dizini vard\u0131r:<\/p>\n<ol>\n<li>\n<p><strong>K\u00fcmelenmi\u015f S\u00fctun Deposu Endeksi (CCI)<\/strong>:<\/p>\n<ul>\n<li>Her tabloda yaln\u0131zca bir CCI bulunabilir.<\/li>\n<li>Tablonun tamam\u0131 s\u0131k\u0131\u015ft\u0131r\u0131lm\u0131\u015f s\u00fctunlu formata d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr.<\/li>\n<li>B\u00fcy\u00fck veri depolama ve analitik i\u015f y\u00fckleri i\u00e7in idealdir.<\/li>\n<\/ul>\n<\/li>\n<li>\n<p><strong>K\u00fcmelenmemi\u015f S\u00fctun Deposu Dizini (NCCI)<\/strong>:<\/p>\n<ul>\n<li>Tek bir tabloda birden fazla NCCI olu\u015fturulabilir.<\/li>\n<li>Yaln\u0131zca se\u00e7ilen s\u00fctunlar s\u0131k\u0131\u015ft\u0131r\u0131lm\u0131\u015f s\u00fctunlu bi\u00e7ime d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr, geri kalan\u0131 sat\u0131r tabanl\u0131 bi\u00e7imde b\u0131rak\u0131l\u0131r.<\/li>\n<li>Belirli s\u00fctunlar\u0131n di\u011ferlerinden daha s\u0131k sorguland\u0131\u011f\u0131 senaryolar i\u00e7in uygundur.<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>A\u015fa\u011f\u0131da CCI ve NCCI aras\u0131ndaki farklar\u0131 \u00f6zetleyen bir tablo bulunmaktad\u0131r:<\/p>\n<table>\n<thead>\n<tr>\n<th>\u00d6zellik<\/th>\n<th>K\u00fcmelenmi\u015f S\u00fctun Deposu Endeksi (CCI)<\/th>\n<th>K\u00fcmelenmemi\u015f S\u00fctun Deposu Dizini (NCCI)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Tablo D\u00f6n\u00fc\u015f\u00fcm\u00fc<\/td>\n<td>Tablonun tamam\u0131 s\u00fctunlu formata d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr<\/td>\n<td>Yaln\u0131zca se\u00e7ilen s\u00fctunlar d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr<\/td>\n<\/tr>\n<tr>\n<td>\u0130ndeks Say\u0131s\u0131<\/td>\n<td>Tablo ba\u015f\u0131na yaln\u0131zca bir CCI&#039;ya izin verilir<\/td>\n<td>Bir tabloda birden fazla NCCI olu\u015fturulabilir<\/td>\n<\/tr>\n<tr>\n<td>Sorgu Performans\u0131<\/td>\n<td>Tam s\u00fctunlu depolama nedeniyle genellikle daha h\u0131zl\u0131<\/td>\n<td>Sorgu performans\u0131 s\u00fctun se\u00e7imine ba\u011fl\u0131d\u0131r<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Kullan\u0131m, Zorluklar ve \u00c7\u00f6z\u00fcmler<\/h2>\n<p>Columnstore dizinleri, b\u00fcy\u00fck \u00f6l\u00e7ekli veri i\u015flemeyi i\u00e7eren analitik sorgular i\u00e7in olduk\u00e7a faydal\u0131d\u0131r. Ancak s\u0131k s\u0131k k\u00fc\u00e7\u00fck \u00f6l\u00e7ekli i\u015flemler ve g\u00fcncellemeler i\u00e7eren OLTP (\u00c7evrimi\u00e7i \u0130\u015flem \u0130\u015fleme) i\u015f y\u00fckleri i\u00e7in uygun olmayabilirler. Bu t\u00fcr senaryolarda geleneksel sat\u0131r tabanl\u0131 dizinler daha iyi performans g\u00f6sterir.<\/p>\n<p>Columnstore dizinleriyle ilgili zorluklar \u015funlar\u0131 i\u00e7erir:<\/p>\n<ul>\n<li>\n<p><strong>Performans Ekleme ve G\u00fcncelleme<\/strong>: Columnstore dizinleri, en iyi performans i\u00e7in verilerin toplu olarak y\u00fcklenmesini gerektirdi\u011finden, sat\u0131r tabanl\u0131 dizinlere k\u0131yasla daha yava\u015f ekleme ve g\u00fcncelleme performans\u0131na sahip olabilir.<\/p>\n<\/li>\n<li>\n<p><strong>Delta Ma\u011fazas\u0131<\/strong>: G\u00fcncellemeleri verimli bir \u015fekilde y\u00f6netmek i\u00e7in SQL Server, kaydedilmemi\u015f veriler i\u00e7in periyodik olarak ana Columnstore ile birle\u015ftirilen bir Delta Deposu tutar. Bu i\u015flem, birle\u015ftirme s\u0131ras\u0131nda sorgu performans\u0131n\u0131 etkileyebilir.<\/p>\n<\/li>\n<\/ul>\n<p>Bu zorluklar\u0131n \u00e7\u00f6z\u00fcmleri \u015funlar\u0131 i\u00e7erir:<\/p>\n<ul>\n<li>\n<p><strong>Toplu G\u00fcncellemeler<\/strong>: G\u00fcncellemelerin daha b\u00fcy\u00fck gruplar halinde ger\u00e7ekle\u015ftirilmesi, Delta Store birle\u015ftirmelerinin s\u0131kl\u0131\u011f\u0131n\u0131 azaltarak performans\u0131 art\u0131rabilir.<\/p>\n<\/li>\n<li>\n<p><strong>Veri Segmentasyonu<\/strong>: Verileri daha k\u00fc\u00e7\u00fck birimlere ay\u0131rmak, ekleme ve g\u00fcncelleme i\u015flemlerinin daha h\u0131zl\u0131 yap\u0131lmas\u0131na yard\u0131mc\u0131 olabilir.<\/p>\n<\/li>\n<\/ul>\n<h2>\u00d6zellikler ve Kar\u015f\u0131la\u015ft\u0131rmalar<\/h2>\n<p>Columnstore dizinlerini benzer veritaban\u0131 \u00f6zellikleriyle kar\u015f\u0131la\u015ft\u0131ral\u0131m:<\/p>\n<table>\n<thead>\n<tr>\n<th>\u00d6zellik<\/th>\n<th>S\u00fctun Deposu Dizinleri<\/th>\n<th>Rowstore Dizinleri<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Depolama Format\u0131<\/td>\n<td>S\u00fctunlu depolama<\/td>\n<td>Sat\u0131r tabanl\u0131 depolama<\/td>\n<\/tr>\n<tr>\n<td>S\u0131k\u0131\u015ft\u0131rma<\/td>\n<td>Y\u00fcksek s\u0131k\u0131\u015ft\u0131rma oranlar\u0131<\/td>\n<td>Daha d\u00fc\u015f\u00fck s\u0131k\u0131\u015ft\u0131rma oranlar\u0131<\/td>\n<\/tr>\n<tr>\n<td>Sorgu Performans\u0131<\/td>\n<td>Analitik sorgular i\u00e7in daha h\u0131zl\u0131<\/td>\n<td>OLTP sorgular\u0131 i\u00e7in daha h\u0131zl\u0131<\/td>\n<\/tr>\n<tr>\n<td>Performans Ekleme ve G\u00fcncelleme<\/td>\n<td>Bireysel g\u00fcncellemeler i\u00e7in daha yava\u015f<\/td>\n<td>Bireysel g\u00fcncellemeler i\u00e7in daha h\u0131zl\u0131<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Perspektifler ve Gelece\u011fin Teknolojileri<\/h2>\n<p>Veriler katlanarak b\u00fcy\u00fcmeye devam ettik\u00e7e Columnstore dizinleri modern veritabanlar\u0131n\u0131n \u00f6nemli bir bile\u015feni olmaya devam edecek. Gelecekteki geli\u015fmeler, g\u00fcncellemelerle ilgili zorluklar\u0131n \u00fcstesinden gelmeye ve daha verimli s\u0131k\u0131\u015ft\u0131rma algoritmalar\u0131 sa\u011flamaya odaklanabilir.<\/p>\n<h2>SQL&#039;de Proxy Sunucular\u0131 ve Columnstore Dizinleri<\/h2>\n<p>OneProxy taraf\u0131ndan sa\u011flanan proxy sunucular\u0131, Columnstore dizinlerini kullanarak SQL Server da\u011f\u0131t\u0131mlar\u0131n\u0131n performans\u0131n\u0131 art\u0131rabilir. Kurulu\u015flar, SQL sorgular\u0131n\u0131 proxy sunucular arac\u0131l\u0131\u011f\u0131yla y\u00f6nlendirerek baz\u0131 i\u015flem y\u00fck\u00fcn\u00fc hafifletebilir ve uzak istemciler i\u00e7in yan\u0131t s\u00fcrelerini potansiyel olarak iyile\u015ftirebilir. Ayr\u0131ca OneProxy&#039;nin y\u00fck dengeleme yetenekleri, sorgular\u0131n e\u015fit \u015fekilde da\u011f\u0131t\u0131lmas\u0131na yard\u0131mc\u0131 olarak kaynak kullan\u0131m\u0131n\u0131 optimize edebilir.<\/p>\n<h2>\u0130lgili Ba\u011flant\u0131lar<\/h2>\n<p>SQL&#039;deki Columnstore dizinleri hakk\u0131nda daha fazla bilgi i\u00e7in a\u015fa\u011f\u0131daki kaynaklara bak\u0131n:<\/p>\n<ul>\n<li><a href=\"https:\/\/docs.microsoft.com\/en-us\/sql\/relational-databases\/indexes\/columnstore-indexes-overview?view=sql-server-ver15\" target=\"_new\" rel=\"noopener nofollow\">Columnstore Dizinlerinde Microsoft Dok\u00fcmanlar\u0131<\/a><\/li>\n<li><a href=\"https:\/\/www.sqlservercentral.com\/steps\/columnstore-indexes-introduction\" target=\"_new\" rel=\"noopener nofollow\">SQL Server Central: Columnstore Dizinlerine Giri\u015f<\/a><\/li>\n<li><a href=\"https:\/\/www.red-gate.com\/hub\/product-learning\/sql-prompt\/development-and-testing-benefits-of-data-compression-in-sql-server\" target=\"_new\" rel=\"noopener nofollow\">SQL Server&#039;da Veri S\u0131k\u0131\u015ft\u0131rma<\/a><\/li>\n<\/ul>","protected":false},"featured_media":467910,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476326","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Columnstore Indexes in SQL: An Overview<\/mark>","faq_items":[{"question":"What are Columnstore indexes in SQL, and how do they work?","answer":"<p>Columnstore indexes in SQL are a database feature that organizes and stores data in a columnar format rather than the traditional row-based storage. This arrangement allows for improved data compression and faster query performance for analytical workloads. Data within each column is stored and processed together, leveraging batch processing techniques. The indexes consist of column segments and dictionaries, which facilitate efficient data retrieval and compression.<\/p>"},{"question":"What is the history behind the origin of Columnstore indexes in SQL?","answer":"<p>Columnstore indexes in SQL were first introduced by Microsoft with the release of SQL Server 2012. The concept of columnar storage has been around since the 1970s, but it gained popularity in the mid-2000s with the rise of big data and the need for better data compression and query performance. Microsoft's implementation marked a significant advancement in this area, making it a standard feature in modern database management systems.<\/p>"},{"question":"How do Clustered Columnstore Indexes (CCI) differ from Non-Clustered Columnstore Indexes (NCCI)?","answer":"<p>Clustered Columnstore Indexes (CCI) convert the entire table into a columnar format, allowing only one CCI per table. On the other hand, Non-Clustered Columnstore Indexes (NCCI) allow multiple indexes on a single table and only convert selected columns into a columnar format. CCI tends to have faster query performance due to complete columnar storage, while NCCI's performance depends on the selection of columns.<\/p>"},{"question":"What are the key features of Columnstore indexes in SQL?","answer":"<p>Some key features of Columnstore indexes include:<\/p><ul><li>High data compression ratios, leading to reduced storage requirements.<\/li><li>Batch mode processing for faster execution of large analytical queries.<\/li><li>Predicate pushdown, allowing for filtering data at the storage level before retrieval.<\/li><li>Vectorized execution for improved query execution speeds.<\/li><\/ul>"},{"question":"What are the main challenges faced with Columnstore indexes?","answer":"<p>While Columnstore indexes offer significant benefits for analytical queries, they can present challenges, such as slower insert and update performance. This is due to the need for bulk loading data for optimal performance. Additionally, the maintenance of a Delta Store for uncommitted data can impact query performance during merges.<\/p>"},{"question":"How can organizations overcome the challenges of Columnstore indexes?","answer":"<p>To improve insert and update performance, organizations can opt for batch updates, performing updates in larger batches. Segmenting data into smaller units can also aid in faster insert and update operations.<\/p>"},{"question":"How can OneProxy's proxy servers enhance SQL Server deployments with Columnstore indexes?","answer":"<p>OneProxy's proxy servers can optimize SQL Server deployments using Columnstore indexes by offloading some processing overhead and potentially improving response times for remote clients. Additionally, OneProxy's load balancing capabilities help distribute queries evenly, optimizing resource usage and enhancing overall performance.<\/p>"},{"question":"What is the future outlook for Columnstore indexes in SQL?","answer":"<p>Columnstore indexes are expected to remain a crucial component of modern databases as data continues to grow exponentially. Future advancements may focus on addressing challenges related to updates and providing even more efficient compression algorithms.<\/p>"},{"question":"Where can I find more information about Columnstore indexes in SQL?","answer":"<p>For more in-depth insights on Columnstore indexes in SQL, you can refer to the following resources:<\/p><ul><li>Microsoft Docs on Columnstore Indexes: <a href=\"https:\/\/docs.microsoft.com\/en-us\/sql\/relational-databases\/indexes\/columnstore-indexes-overview?view=sql-server-ver15\" target=\"_new\">Link<\/a><\/li><li>SQL Server Central: Introduction to Columnstore Indexes: <a href=\"https:\/\/www.sqlservercentral.com\/steps\/columnstore-indexes-introduction\" target=\"_new\">Link<\/a><\/li><li>Data Compression in SQL Server: <a href=\"https:\/\/www.red-gate.com\/hub\/product-learning\/sql-prompt\/development-and-testing-benefits-of-data-compression-in-sql-server\" target=\"_new\">Link<\/a><\/li><\/ul>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476326","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476326\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/467910"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476326"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}