{"id":6976,"date":"2023-05-02T00:00:00","date_gmt":"2023-05-02T04:00:00","guid":{"rendered":"https:\/\/www.sisense.com\/generate-series-in-redshift-and-mysql\/"},"modified":"2024-09-23T15:21:58","modified_gmt":"2024-09-23T19:21:58","slug":"generate-series-in-redshift-and-mysql","status":"publish","type":"post","link":"https:\/\/www.sisense.com\/blog\/generate-series-in-redshift-and-mysql\/","title":{"rendered":"Generate series in Redshift and MySQL"},"content":{"rendered":"<p><\/p>\r\n<p>A lot of charts and tables are time series, and the queries behind them are often easier when you can join and aggregate against a list of dates. Not having a complete list of dates causes gaps in the results, changing them in a misleading way:<\/p>\r\n<figure class=\"wp-block-image fancybox\"><img decoding=\"async\" class=\"wp-image-74257\" src=\"https:\/\/cdn.sisense.com\/wp-content\/uploads\/Daily-reports.png\" alt=\"Daily reports\" \/><\/figure>\r\n<p>Postgres has a great function for generating a list of dates and making a list of the last 60 days with <a href=\"https:\/\/www.postgresql.org\/docs\/9.3\/functions-srf.html\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">generate_series<\/a> is easy:<\/p>\r\n<pre class=\"wp-block-code\"><code>select now()::date - generate_series(0, 59)<\/code><\/pre>\r\n<p>Accomplishing the same thing in Redshift and MySQL requires a little more work.<\/p>\r\n<h2>Date series from a numbers table<\/h2>\r\n<p>The simplest alternative to generate_series is to create a table containing a continuous list of numbers, starting at 0, and select from that table. (If you have a table with a sequential id column and never delete rows from it, you can just select the id column from that table instead of creating a new numbers table).<\/p>\r\n<pre class=\"wp-block-code\"><code>select n from numbers;<\/code><\/pre>\r\n<p>Returns this list of rows: 0, 1, 2, 3\u2026<\/p>\r\n<p>Now that you have a numbers table, convert each number into a date:<\/p>\r\n<h2>Redshift:<\/h2>\r\n<pre class=\"wp-block-code\"><code>select (getdate()::date - n)::date from numbers<\/code><\/pre>\r\n<p><strong>MySQL:<\/strong><\/p>\r\n<pre class=\"wp-block-code\"><code>select date_sub(date(now()), interval n day) from numbers<\/code><\/pre>\r\n<p>A numbers table is more convenient than a dates table since it never needs to be refreshed with new dates.<\/p>\r\n<h2>Redshift: Date series using window functions<\/h2>\r\n<p>If you don\u2019t have the option to create a numbers table, you can build one on the fly using a window function. All you need is a table that has at least as many rows as the number of dates desired. Using a window function, number the rows in any table to get a list of numbers, and then convert that to a list of dates:<\/p>\r\n<pre class=\"wp-block-code\"><code>select row_number() over (order by true) as n\r\nfrom users limit 60<\/code><\/pre>\r\n<p>And now creating the list of dates directly:<\/p>\r\n<pre class=\"wp-block-code\"><code>select (\r\n    getdate()::date - row_number() over (order by true)\r\n  )::date as n\r\nfrom users limit 60<\/code><\/pre>\r\n<h2>MySQL: Date series using variables<\/h2>\r\n<p>With variables in MySQL, we can generate a numbers table by treating a select statement as a for loop:<\/p>\r\n<pre class=\"wp-block-code\"><code>set @n:=-1;\r\nselect (select @n:= @n+1) n\r\nfrom users limit 60<\/code><\/pre>\r\n<p>Now that we\u2019ve made a list of dates, aggregating and joining data from other tables for time series charts is a breeze!<\/p>\r\n<p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n<\/p>","protected":false},"excerpt":{"rendered":"<p>A lot of charts and tables are time series, and the queries behind them are often easier when you can join and aggregate against a list of dates. Not having a complete list of dates causes gaps in the results,&#8230;<\/p>\n","protected":false},"author":4,"featured_media":7181,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[44],"tags":[472],"application":[46],"buyer-role":[],"buyer-stage":[],"department":[],"industry":[],"topic":[],"class_list":["post-6976","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech-talk","tag-data-team","application-bi-analytics-teams"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v23.5 (Yoast SEO v23.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Generate Series in Redshift and MySQL | Sisense<\/title>\n<meta name=\"description\" content=\"A lot of charts and tables are time series. 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