{"id":1049,"date":"2020-06-11T09:00:00","date_gmt":"2020-06-11T06:00:00","guid":{"rendered":"https:\/\/www.dataplatform.gr\/?p=1049"},"modified":"2026-02-24T11:21:10","modified_gmt":"2026-02-24T08:21:10","slug":"pos-apothikeyontai-oi-vaseis-dedomenon-kai-ti-einai-ta-indexes","status":"publish","type":"post","link":"https:\/\/www.dataplatform.gr\/en\/pos-apothikeyontai-oi-vaseis-dedomenon-kai-ti-einai-ta-indexes\/","title":{"rendered":"How databases are stored and what indexes are"},"content":{"rendered":"<p>We have seen what a relational database is and that our entities are logical objects called tables.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">But how are they stored \u201cphysically\u201d in an RDBMS (relational database management system)?<\/h4>\n\n\n\n<p>Tables like objects are also stored on a hard disk.<\/p>\n\n\n\n<p>You call their information the most fragmented part of it <strong>page<\/strong> (page). Several pages together form one <strong>extent<\/strong>. <\/p>\n\n\n\n<p>It should be mentioned that in <strong>Oracle<\/strong> the page size is not constant, while in <strong>SQL Server<\/strong>  it is 8K. As also in <strong>Oracle <\/strong>a set of extents is called <strong>segment<\/strong>.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">What is query optimizer and execution plan?<\/h4>\n\n\n\n<p>By storing a huge amount of data on hard drives, the recovery of specific information becomes time-consuming with a high cost of resources.<\/p>\n\n\n\n<p>The <strong>RDBMS <\/strong>they have a tool that works like a GPS. <\/p>\n\n\n\n<p>It can find the paths to follow to get to the data and choose the fastest way with the least cost.<\/p>\n\n\n\n<p>This tool is called <strong>query optimizer<\/strong> and its corresponding map is called <strong>execution plan<\/strong>.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">What are indexes and statistics?<\/h4>\n\n\n\n<p>The main allies of the query optimizer are the <strong>indexes<\/strong> and <strong>statistics<\/strong>. As Index we define a storage structure on the hard disk associated with a table or view. <\/p>\n\n\n\n<p>Statistics are a set of statistical information for a table or view such as number of records, average length of each field, how many fields are empty (null), etc.<\/p>\n\n\n\n<p>As changes are made to the database, the data on disk changes. So these two structures need maintenance. The indexes <strong>defragmentation\/rebuild<\/strong> and statistics <strong>update<\/strong>.<\/p>\n\n\n\n<p>The tables \/ views that have changes over 10% and their statistics have not been updated are called <strong>stale<\/strong>.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"646\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/1-ind-1024x646.png\" alt=\"\" class=\"wp-image-1052\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/1-ind-1024x646.png 1024w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/1-ind-300x189.png 300w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/1-ind-768x485.png 768w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/1-ind.png 1155w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Diagram of how the database data is stored, on a &quot;physical&quot; medium.<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">What is the difference between clustered and non-clustered indexes?<\/h2>\n\n\n\n<p><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Clustered index<\/h4>\n\n\n\n<p><strong>Clustered index<\/strong> is the index that has its data in order based on the field defined, usually the <strong>primary key<\/strong> (it is the default behavior in SQL Server) and there can only be one per entity. <\/p>\n\n\n\n<p>Tables \/ views that do not have a clustered index are called <strong>heap. <\/strong>By using them the data is physically stored on the disk not randomly but in order. <\/p>\n\n\n\n<p>For example, in a table that had the identity number defined as a primary key, those numbers starting with A would be in neighboring blocks. <\/p>\n\n\n\n<p>So it would be very easy for the RDBMS to answer a query like bring me as many citizens whose ID starts with A. <\/p>\n\n\n\n<p>As a result, when we talk about a clustered index, we are talking about the way the actual data of the records are stored on the hard disk.<\/p>\n\n\n\n<p>The key fields of indexes, whether clustered or non-clustered, are usually organized with its architecture <a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/B%2B_tree\" target=\"_blank\">b+ tree<\/a>. This is so that they are faster and easier to access.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Non-clustered index<\/h4>\n\n\n\n<p><strong>Non-clustered index<\/strong> unlike clustered indexes they are separate from the entity record data and function like an index.<\/p>\n\n\n\n<p>They contain one or several fields (eg Surname, First Name) that we have defined to be created. Through pointers (row locators) they point to the line where the entire record of the table\/view is located or to the primary key of the clustered index if it is not a heap. <\/p>\n\n\n\n<p>For example if we create a non-clustered index on the Name field of the customer table. We will be able to easily bring customers whose name is Kostas or whose name starts with K.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"745\" height=\"630\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/2-ind.png\" alt=\"\" class=\"wp-image-1053\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/2-ind.png 745w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/2-ind-300x254.png 300w\" sizes=\"auto, (max-width: 745px) 100vw, 745px\" \/><figcaption class=\"wp-element-caption\">Example of a table with a Clustered Index that also has two Non-Clustered.<\/figcaption><\/figure>\n\n\n\n<p>Through the example we see that the real table (with Clustered Index) is in order according to the customer code which is the field where the index is created. <\/p>\n\n\n\n<p>In the two Non-Clustered the data is ordered by a different field, one by phone and the other by name. <\/p>\n\n\n\n<p>However, if in any of them we need extra information outside of the Non-Clustered Index of eg Surname. A key should be made <strong>lookup<\/strong> to the client table to fetch the value for each of them.<\/p>\n\n\n\n<p> This is usually a time consuming process towards the base.<\/p>\n\n\n\n<p>In the event that we want our data to be in order (<strong>sorted<\/strong>) with a field, but also contains information from the rest of the data in the table without lookup, then we make this field <strong>include<\/strong>. <\/p>\n\n\n\n<p>For example in the Non-Clustered Index in the Name we add (<strong>include<\/strong>) as information the adjective.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"306\" height=\"221\" src=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/3-ind.png\" alt=\"\" class=\"wp-image-1055\" srcset=\"https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/3-ind.png 306w, https:\/\/www.dataplatform.gr\/wp-content\/uploads\/2020\/06\/3-ind-300x217.png 300w\" sizes=\"auto, (max-width: 306px) 100vw, 306px\" \/><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\">What is the drawback?<\/h4>\n\n\n\n<p>In closing, it should be mentioned why, since indexes are useful, not to make many non-clustered indexes in most fields or not to include all records.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Every time you perform a transaction on the table \/ view, its indexes are also updated. Which means <strong>delays<\/strong> in carrying out the transactions.<\/li>\n\n\n\n<li><strong>More disk space<\/strong>: a non-clustered index that has included all the fields of the table, its size will be approximately the size of the entire table \/ clustered index.<\/li>\n\n\n\n<li><strong>Memory pressure on RAM<\/strong>: the more we have, the more information you will collect crammed into memory (<strong>cache buffer pool<\/strong>). Which means a greater demand on memory, the lack of which leads to poor performance.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Sources:<\/h2>\n\n\n\n<p><a href=\"https:\/\/docs.microsoft.com\/en-us\/sql\/relational-databases\/statistics\/statistics?view=sql-server-ver15\" target=\"_blank\" rel=\"noreferrer noopener\">Microsoft Statistics<\/a><\/p>\n\n\n\n<p><a href=\"https:\/\/docs.microsoft.com\/en-us\/sql\/relational-databases\/indexes\/clustered-and-nonclustered-indexes-described?view=sql-server-ver15\" target=\"_blank\" rel=\"noreferrer noopener\">Microsoft Clustered and Nonclustered Indexes Described<\/a><\/p>\n\n\n\n<p><a href=\"https:\/\/docs.oracle.com\/cd\/B19306_01\/server.102\/b14220\/logical.htm\" target=\"_blank\" rel=\"noreferrer noopener\">Oracle Data Blocks, Extents, and Segments<\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>We have seen what a relational database is and that our entities are logical objects called tables. But how are they stored \u201cphysically\u201d in an RDBMS (relational database management system)? Tables like objects are also stored on a hard disk. Their information as the most fragmented part of it is called a page [...]<\/p>","protected":false},"author":1,"featured_media":688,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,15,16],"tags":[29,49,5,6],"class_list":["post-1049","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-databases","category-ms-sqlserver","category-oracle-db","tag-databases","tag-indexes","tag-oracle-database","tag-sqlserver"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>\u03a0\u03ce\u03c2 \u03b1\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bf\u03b9 \u03b2\u03ac\u03c3\u03b5\u03b9\u03c2 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03b1 indexes - DataPlatform.gr<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.dataplatform.gr\/en\/pos-apothikeyontai-oi-vaseis-dedomenon-kai-ti-einai-ta-indexes\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u03a0\u03ce\u03c2 \u03b1\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bf\u03b9 \u03b2\u03ac\u03c3\u03b5\u03b9\u03c2 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03b1 indexes - DataPlatform.gr\" \/>\n<meta property=\"og:description\" content=\"\u0388\u03c7\u03bf\u03c5\u03bc\u03b5 \u03b4\u03b5\u03b9 \u03c4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b9\u03b1 \u03c3\u03c7\u03b5\u03c3\u03b9\u03b1\u03ba\u03ae \u03b2\u03ac\u03c3\u03b7 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd (relational database) \u03ba\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03bf\u03b9 \u03bf\u03bd\u03c4\u03cc\u03c4\u03b7\u03c4\u03ad\u03c2 \u03bc\u03b1\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ac \u03b1\u03bd\u03c4\u03b9\u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03b1 \u03c0\u03bf\u03c5 \u03bf\u03bd\u03bf\u03bc\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03af\u03bd\u03b1\u03ba\u03b5\u03c2. \u03a0\u03ce\u03c2 \u03cc\u03bc\u03c9\u03c2 \u03b1\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03bf\u03bd\u03c4\u03b1\u03b9 &#8220;\u03c6\u03c5\u03c3\u03b9\u03ba\u03ac&#8221; \u03c3\u03b5 \u03ad\u03bd\u03b1 RDBMS (\u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03b4\u03b9\u03b1\u03c7\u03b5\u03af\u03c1\u03b9\u03c3\u03b7\u03c2 \u03c3\u03c7\u03b5\u03c3\u03b9\u03b1\u03ba\u03ce\u03bd \u03b2\u03ac\u03c3\u03b5\u03c9\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd); \u039f\u03b9 \u03c0\u03af\u03bd\u03b1\u03ba\u03b5\u03c2 \u03c3\u03b1\u03bd objects \u03b1\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b9 \u03b1\u03c5\u03c4\u03ac \u03c3\u03b5 \u03ad\u03bd\u03b1 \u03c3\u03ba\u03bb\u03b7\u03c1\u03cc \u03b4\u03af\u03c3\u03ba\u03bf. 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