{"id":422,"date":"2023-05-15T16:31:52","date_gmt":"2023-05-15T16:31:52","guid":{"rendered":"https:\/\/appsgeyser.io\/blog\/?p=422"},"modified":"2023-07-21T07:46:05","modified_gmt":"2023-07-21T07:46:05","slug":"converting-rows-to-columns-in-oracle-without-pivot","status":"publish","type":"post","link":"https:\/\/appsgeyser.io\/blog\/2023\/05\/15\/converting-rows-to-columns-in-oracle-without-pivot\/","title":{"rendered":"Converting Rows to Columns in Oracle Without PIVOT: 7 Effective Techniques"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"578\" height=\"272\" src=\"https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/1.png\" alt=\"\" class=\"wp-image-423\" srcset=\"https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/1.png 578w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/1-300x141.png 300w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/1-150x71.png 150w\" sizes=\"auto, (max-width: 578px) 100vw, 578px\" \/><\/figure>\n\n\n\n<p>In many real-world scenarios, database professionals need to convert rows to columns in order to present data in a more organized and meaningful manner. This process, often referred to as pivoting, helps in better visualization and analysis of data, allowing users to extract valuable insights.<\/p>\n\n\n\n<p>The PIVOT operator, introduced in Oracle 11g, simplifies the process of converting rows to columns. However, it has its limitations. For instance, it requires the target columns to be known beforehand, and it may not be suitable for dynamic column generation. In addition, the PIVOT operator is not available in earlier versions of Oracle, which means users of those versions must find alternative ways to achieve the same result.<\/p>\n\n\n\n<p>In this article, we have explored various methods for converting rows to columns in Oracle without using the PIVOT operator. We have discussed the following techniques:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>XMLAGG (Oracle 9i)<\/li>\n\n\n\n<li>LISTAGG and WITHIN GROUP (Oracle 11g)<\/li>\n\n\n\n<li>SYS_CONNECT_BY_PATH<\/li>\n\n\n\n<li>CROSS JOIN<\/li>\n\n\n\n<li>Analytic LAG-OVER Function<\/li>\n\n\n\n<li>CASE Statement<\/li>\n\n\n\n<li>Modeling Clause<\/li>\n<\/ul>\n\n\n\n<p>Understanding different techniques for data manipulation is essential for working with databases, as each method has its own strengths and limitations. Familiarity with multiple approaches enables you to choose the most suitable technique for your specific needs and optimize the performance of your queries.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">XMLAGG (Oracle 9i)<\/h2>\n\n\n\n<p>XMLAGG is an aggregation function available in Oracle 9i and later versions that allows you to aggregate XML fragments into a single XML document. The syntax for the XMLAGG function is as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">XMLAGG(XMLELEMENT(e, expression) [ORDER BY column_name])<\/mark><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>XMLELEMENT<\/strong>: A function that creates an XML element with a specified name and value.<\/li>\n\n\n\n<li><strong>e<\/strong>: The name of the XML element.<\/li>\n\n\n\n<li><strong>expression<\/strong>: The column or expression whose values you want to aggregate.<\/li>\n\n\n\n<li><strong>column_name (optional)<\/strong>: The column by which the aggregation order is determined.<\/li>\n<\/ul>\n\n\n\n<p>By using XMLAGG in combination with other functions such as XMLELEMENT and EXTRACT, you can achieve row-to-column conversion without using the PIVOT operator.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example<\/h3>\n\n\n\n<p>Suppose you have a table called &#8217;employees&#8217; with the following structure:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>id<\/strong><\/th><th><strong>department_id<\/strong><\/th><th><strong>employee_name<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>10<\/td><td>John<\/td><\/tr><tr><td>2<\/td><td>10<\/td><td>Jane<\/td><\/tr><tr><td>3<\/td><td>20<\/td><td>Michael<\/td><\/tr><tr><td>4<\/td><td>20<\/td><td>Sarah<\/td><\/tr><tr><td>5<\/td><td>30<\/td><td>Tom<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>To convert rows to columns and display employee names separated by commas for each department_id, you can use the XMLAGG function as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0department_id,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0RTRIM(XMLAGG(XMLELEMENT(e, employee_name || &#8216;,&#8217;)).EXTRACT(&#8216;\/\/text()&#8217;), &#8216;,&#8217;) AS employee_names<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0employees<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">GROUP BY<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0department_id;<\/mark><\/p>\n\n\n\n<p>The result would be:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>department_id<\/strong><\/th><th><strong>employee_names<\/strong><\/th><\/tr><\/thead><tbody><tr><td>10<\/td><td>John, Jane<\/td><\/tr><tr><td>20<\/td><td>Michael, Sarah<\/td><\/tr><tr><td>30<\/td><td>Tom<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>This example demonstrates how the XMLAGG function can be effectively used to convert rows to columns in Oracle 9i. It is particularly useful when you need to concatenate string values from multiple rows into a single column, separated by a specified delimiter.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">LISTAGG and WITHIN GROUP (Oracle 11g)<\/h2>\n\n\n\n<p>LISTAGG is an aggregation function introduced in Oracle 11g that allows you to concatenate multiple rows of data into a single string, using a specified delimiter. The syntax for the LISTAGG function is as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">LISTAGG(expression, delimiter) WITHIN GROUP (ORDER BY column_name)<\/mark><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>expression<\/strong>: The column or expression whose values you want to concatenate.<\/li>\n\n\n\n<li><strong>delimiter<\/strong>: The separator to be used between the concatenated values.<\/li>\n\n\n\n<li><strong>column_name<\/strong>: The column by which the concatenation order is determined.<\/li>\n<\/ul>\n\n\n\n<p>The WITHIN GROUP clause is used in conjunction with LISTAGG to specify the order in which the rows are concatenated.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example<\/h3>\n\n\n\n<p>Suppose you have a table called &#8220;employees&#8221; with the following data:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>emp_id<\/strong><\/th><th><strong>dept_id<\/strong><\/th><th><strong>emp_name<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>10<\/td><td>John<\/td><\/tr><tr><td>2<\/td><td>10<\/td><td>Jane<\/td><\/tr><tr><td>3<\/td><td>20<\/td><td>Michael<\/td><\/tr><tr><td>4<\/td><td>20<\/td><td>Alice<\/td><\/tr><tr><td>5<\/td><td>30<\/td><td>Bob<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>If you want to display the employee names within each department as a single string, ordered by their names, you can use the LISTAGG function with the WITHIN GROUP clause:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT dept_id,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0LISTAGG(emp_name, &#8216;,&#8217;) WITHIN GROUP (ORDER BY emp_name) AS emp_names<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM employees<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">GROUP BY dept_id;<\/mark><\/p>\n\n\n\n<p>The result would look like this:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>dept_id<\/strong><\/th><th><strong>emp_names<\/strong><\/th><\/tr><\/thead><tbody><tr><td>10<\/td><td>John, Jane<\/td><\/tr><tr><td>20<\/td><td>Alice, Michael<\/td><\/tr><tr><td>30<\/td><td>Bob<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In this example, the LISTAGG function is used to concatenate the emp_name values within each department, separated by a comma. The WITHIN GROUP clause is used to order the emp_name values alphabetically before concatenating them.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">SYS_CONNECT_BY_PATH<\/h2>\n\n\n\n<p>SYS_CONNECT_BY_PATH is a hierarchical function in Oracle that returns the path of a column value from root to node, with the column values separated by a specified delimiter. It is used in conjunction with the CONNECT BY clause in hierarchical queries. The syntax for SYS_CONNECT_BY_PATH is as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SYS_CONNECT_BY_PATH(column_name, delimiter)<\/mark><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>column_name: The name of the column whose values you want to concatenate.<\/li>\n\n\n\n<li>delimiter: The delimiter separates the column values in the resulting path.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Example<\/h3>\n\n\n\n<p>Suppose we have the following EMPLOYEES table:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>ID<\/strong><\/th><th><strong>NAME<\/strong><\/th><th><strong>DEPARTMENT_ID<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>Alice<\/td><td>10<\/td><\/tr><tr><td>2<\/td><td>Bob<\/td><td>10<\/td><\/tr><tr><td>3<\/td><td>Carol<\/td><td>20<\/td><\/tr><tr><td>4<\/td><td>David<\/td><td>20<\/td><\/tr><tr><td>5<\/td><td>Eve<\/td><td>30<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>We want to convert the rows to columns, showing the employee names separated by commas for each department. Here&#8217;s how to use SYS_CONNECT_BY_PATH:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0DEPARTMENT_ID,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0SUBSTR(SYS_CONNECT_BY_PATH(NAME, &#8216;,&#8217;), 2) AS EMPLOYEE_NAMES<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0(<\/mark><\/p>\n\n\n\n<p>&nbsp;<mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">&nbsp;&nbsp;&nbsp;SELECT<\/mark><\/p>\n\n\n\n<p>&nbsp;<mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;NAME,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0DEPARTMENT_ID,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0ROW_NUMBER() OVER (PARTITION BY DEPARTMENT_ID ORDER BY NAME) AS SEQ,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0COUNT(*) OVER (PARTITION BY DEPARTMENT_ID) AS CNT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0EMPLOYEES<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0)<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">WHERE<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0SEQ = CNT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">START WITH<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0SEQ = 1<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">CONNECT BY<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0PRIOR SEQ + 1 = SEQ<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0AND PRIOR DEPARTMENT_ID = DEPARTMENT_ID;<\/mark><\/p>\n\n\n\n<p>The output would look like this:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>DEPARTMENT_ID<\/strong><\/th><th><strong>EMPLOYEE_NAMES<\/strong><\/th><\/tr><\/thead><tbody><tr><td>10<\/td><td>Alice, Bob<\/td><\/tr><tr><td>20<\/td><td>Carol, David<\/td><\/tr><tr><td>30<\/td><td>Eve<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In this example, SYS_CONNECT_BY_PATH is used to concatenate employee names for each department, separated by commas.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">CROSS JOIN<\/h2>\n\n\n\n<p>A CROSS JOIN, also known as a Cartesian join, is a technique in SQL that combines each row of one table with each row of another table, resulting in a Cartesian product of the two tables. The syntax for CROSS JOIN is:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT *<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM table1<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">CROSS JOIN table2;<\/mark><\/p>\n\n\n\n<p>It is used when you want to create a combination of every row from two or more tables, without any condition. The CROSS JOIN can be used to pivot rows to columns in certain scenarios, by creating a derived table with the desired columns and then joining it to the original table.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example<\/h3>\n\n\n\n<p>Suppose we have the following table, ITEMS:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>ITEM_ID<\/strong><\/th><th><strong>ITEM1<\/strong><\/th><th><strong>ITEM2<\/strong><\/th><th><strong>ITEM3<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>A<\/td><td>B<\/td><td>C<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>We want to convert the rows to columns, showing each item value in a separate row. Here&#8217;s how to use CROSS JOIN:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0ITEM_ID,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0PIVOTER.ITEM_LABEL,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0CASE<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0WHEN PIVOTER.ITEM_LABEL = &#8216;ITEM1&#8217; THEN ITEM1<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0WHEN PIVOTER.ITEM_LABEL = &#8216;ITEM2&#8217; THEN ITEM2<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0WHEN PIVOTER.ITEM_LABEL = &#8216;ITEM3&#8217; THEN ITEM3<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0END AS ITEM_VALUE<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0ITEMS<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">CROSS JOIN<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0(<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0SELECT &#8216;ITEM1&#8217; AS ITEM_LABEL FROM DUAL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0UNION ALL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0SELECT &#8216;ITEM2&#8217; AS ITEM_LABEL FROM DUAL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0UNION ALL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0SELECT &#8216;ITEM3&#8217; AS ITEM_LABEL FROM DUAL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0) PIVOTER;<\/mark><\/p>\n\n\n\n<p>The output would look like this:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>ITEM_ID<\/strong><\/th><th><strong>ITEM_LABEL<\/strong><\/th><th><strong>ITEM_VALUE<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>ITEM1<\/td><td>A<\/td><\/tr><tr><td>1<\/td><td>ITEM2<\/td><td>B<\/td><\/tr><tr><td>1<\/td><td>ITEM3<\/td><td>C<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In this example, the CROSS JOIN is used to create a derived table with the desired column labels (ITEM1, ITEM2, and ITEM3) and then join it to the original ITEMS table. The CASE statement is used to display the corresponding item values in a single column.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Analytic LAG-OVER Function<\/h2>\n\n\n\n<p>LAG is an analytic function in Oracle that allows you to access data from a previous row in the result set, relative to the current row. The LAG function can be used with the OVER() clause to specify the order and partition of the data. The syntax for the LAG function is:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\"><code>LAG (expression, offset, default_value) OVER (<\/code><\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\"><code>\u00a0\u00a0\u00a0\u00a0PARTITION BY partition_expression<\/code><\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\"><code>\u00a0\u00a0\u00a0\u00a0ORDER BY order_expression<\/code><\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\"><code>)<\/code><\/mark><\/p>\n\n\n\n<p><strong>expression<\/strong> is the value to be fetched from the previous row, <strong>offset<\/strong> is the number of rows back from the current row, and <strong>default_value<\/strong> is the value returned when the offset goes beyond the available rows. The PARTITION BY and ORDER BY clauses inside the OVER() function are optional.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example<\/h3>\n\n\n\n<p>Consider the following&nbsp;<strong>sales<\/strong>&nbsp;table with columns&nbsp;<strong>product_id<\/strong>,&nbsp;<strong>sales_date<\/strong>, and&nbsp;<strong>quantity<\/strong>:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>product_id<\/strong><\/th><th><strong>sales_date<\/strong><\/th><th><strong>quantity<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>2022-01-01<\/td><td>10<\/td><\/tr><tr><td>1<\/td><td>2022-01-15<\/td><td>12<\/td><\/tr><tr><td>1<\/td><td>2022-02-05<\/td><td>8<\/td><\/tr><tr><td>2<\/td><td>2022-01-10<\/td><td>15<\/td><\/tr><tr><td>2<\/td><td>2022-02-03<\/td><td>20<\/td><\/tr><tr><td>3<\/td><td>2022-01-18<\/td><td>5<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>If you want to display the current sale along with the previous sale date and quantity for each product, you can use the LAG function as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT\u00a0<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0product_id,<\/mark>\u00a0<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0sales_date,<\/mark>\u00a0<\/p>\n\n\n\n<p>&nbsp;<mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">&nbsp;&nbsp;&nbsp;quantity,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0LAG(sales_date, 1) OVER (PARTITION BY product_id ORDER BY sales_date) AS prev_sales_date,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0LAG(quantity, 1) OVER (PARTITION BY product_id ORDER BY sales_date) AS prev_quantity<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM\u00a0<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0sales;<\/mark><\/p>\n\n\n\n<p>The result of this query would be:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>product_id<\/strong><\/th><th><strong>sales_date<\/strong><\/th><th><strong>quantity<\/strong><\/th><th><strong>prev_sales_date<\/strong><\/th><th><strong>prev_quantity<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>2022-01-01<\/td><td>10<\/td><td>(null)<\/td><td>(null)<\/td><\/tr><tr><td>1<\/td><td>2022-01-15<\/td><td>12<\/td><td>2022-01-01<\/td><td>10<\/td><\/tr><tr><td>1<\/td><td>2022-02-05<\/td><td>8<\/td><td>2022-01-15<\/td><td>12<\/td><\/tr><tr><td>2<\/td><td>2022-01-10<\/td><td>15<\/td><td>(null)<\/td><td>(null)<\/td><\/tr><tr><td>2<\/td><td>2022-02-03<\/td><td>20<\/td><td>2022-01-10<\/td><td>15<\/td><\/tr><tr><td>3<\/td><td>2022-01-18<\/td><td>5<\/td><td>(null)<\/td><td>(null)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In this example, the LAG function is used to access the sales_date and quantity values from the previous row for each product, as specified by the PARTITION BY and ORDER BY clauses.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">CASE Statement<\/h2>\n\n\n\n<p>The CASE statement is a flexible and powerful SQL construct that can be used for a variety of purposes. One of its applications is to convert rows to columns, effectively pivoting the data. By using the CASE statement, you can create a crosstab-like result, where you can conditionally aggregate and display data based on specific conditions.<\/p>\n\n\n\n<p>The syntax for the CASE statement is:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">CASE<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0WHEN condition1 THEN result1<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0WHEN condition2 THEN result2<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u2026<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0ELSE resultN<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">END<\/mark><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example<\/h3>\n\n\n\n<p>Consider the following&nbsp;<strong>survey_responses<\/strong>&nbsp;table with columns&nbsp;<strong>response_id<\/strong>,&nbsp;<strong>question_id<\/strong>, and&nbsp;<strong>answer<\/strong>:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>response_id<\/strong><\/th><th><strong>question_id<\/strong><\/th><th><strong>answer<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>1<\/td><td>A<\/td><\/tr><tr><td>1<\/td><td>2<\/td><td>B<\/td><\/tr><tr><td>1<\/td><td>3<\/td><td>C<\/td><\/tr><tr><td>2<\/td><td>1<\/td><td>B<\/td><\/tr><tr><td>2<\/td><td>2<\/td><td>C<\/td><\/tr><tr><td>2<\/td><td>3<\/td><td>A<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>If you want to display each response&#8217;s answers as columns for each question, you can use the CASE statement as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0response_id,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0MAX(CASE WHEN question_id = 1 THEN answer ELSE NULL END) AS question_1,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0MAX(CASE WHEN question_id = 2 THEN answer ELSE NULL END) AS question_2,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0MAX(CASE WHEN question_id = 3 THEN answer ELSE NULL END) AS question_3<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0survey_responses<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">GROUP BY<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0response_id;<\/mark><\/p>\n\n\n\n<p>The result of this query would be:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>response_id<\/strong><\/th><th><strong>question_1<\/strong><\/th><th><strong>question_2<\/strong><\/th><th><strong>question_3<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>A<\/td><td>B<\/td><td>C<\/td><\/tr><tr><td>2<\/td><td>B<\/td><td>C<\/td><td>A<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In this example, the CASE statement is used to pivot the data by aggregating the answers for each question and displaying them as separate columns.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Modeling Clause<\/h2>\n\n\n\n<p>The MODEL clause is an advanced SQL feature available in Oracle, which allows you to perform complex data manipulation and transformation tasks using a multidimensional array-like structure. By defining dimensions, measures, and rules, you can apply complex calculations, data transformations, and even pivoting operations. It is a powerful and flexible method for converting rows to columns.<\/p>\n\n\n\n<p>The basic syntax for the MODEL clause is:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT \u2026<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM \u2026<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">WHERE \u2026<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">MODEL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0[DIMENSION BY (dimension_columns)]<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0[MEASURES (measure_columns)]<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0[RULES (rule_definitions)];<\/mark><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Example<\/h2>\n\n\n\n<p>Consider the following sales table with columns product_id, year, and sales_amount:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>product_id<\/strong><\/th><th><strong>year<\/strong><\/th><th><strong>sales_amount<\/strong><\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td>2020<\/td><td>1000<\/td><\/tr><tr><td>1<\/td><td>2021<\/td><td>1100<\/td><\/tr><tr><td>2<\/td><td>2020<\/td><td>900<\/td><\/tr><tr><td>2<\/td><td>2021<\/td><td>950<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>If you want to display the sales amount for each product as columns, you can use the MODEL clause as follows:<\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">SELECT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0year,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0product_1_sales,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0product_2_sales<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0(SELECT<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0year,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0product_id,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0sales_amount<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0FROM<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0sales)<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">MODEL<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0DIMENSION BY (year)<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0MEASURES (sales_amount,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a00 AS product_1_sales,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a00 AS product_2_sales)<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0RULES (product_1_sales[ANY] = CASE WHEN product_id = 1 THEN sales_amount[CV()] ELSE NULL END,<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0product_2_sales[ANY] = CASE WHEN product_id = 2 THEN sales_amount[CV()] ELSE NULL END)<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">ORDER BY<\/mark><\/p>\n\n\n\n<p><mark style=\"background-color:#000000\" class=\"has-inline-color has-background-color\">\u00a0\u00a0\u00a0\u00a0year;<\/mark><\/p>\n\n\n\n<p>The result of this query would be:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th><strong>year<\/strong><\/th><th><strong>product_1_sales<\/strong><\/th><th><strong>product_2_sales<\/strong><\/th><\/tr><\/thead><tbody><tr><td>2020<\/td><td>1000<\/td><td>900<\/td><\/tr><tr><td>2021<\/td><td>1100<\/td><td>950<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In this example, the MODEL clause is used to pivot the data by defining dimensions (year) and measures (sales_amount, product_1_sales, product_2_sales). The RULES section then defines the calculations and conditions for the new columns, effectively converting rows to columns.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p>We encourage you to explore other SQL features and techniques that Oracle offers, as they can help you solve a wide range of data manipulation and transformation tasks. Continuously learning and expanding your SQL knowledge will improve your overall proficiency in working with databases.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"559\" src=\"https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2-1024x559.png\" alt=\"Pivot Table feature in dbForge Studio for Oracle\" class=\"wp-image-424\" srcset=\"https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2-1024x559.png 1024w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2-300x164.png 300w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2-768x420.png 768w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2-1536x839.png 1536w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2-150x82.png 150w, https:\/\/appsgeyser.io\/blog\/wp-content\/uploads\/2023\/05\/2.png 1600w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">(Pivot Table feature in dbForge Studio for Oracle)<\/figcaption><\/figure>\n\n\n\n<p>It is important to note that it is best to try to use the PIVOT operator whenever possible, as it is designed specifically for this purpose and can simplify your queries. To learn more about the PIVOT operator and how to use it in Oracle, you can read the <a href=\"https:\/\/www.devart.com\/dbforge\/oracle\/studio\/pivot-table-oracle.html\">Oracle PIVOT &#8211; Rows to Columns<\/a>&nbsp;article.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In many real-world scenarios, database professionals need to convert rows to columns in order to present data in a more organized and meaningful manner. This process, often referred to as pivoting, helps in better visualization and analysis of data, allowing users to extract valuable insights. The PIVOT operator, introduced in Oracle 11g, simplifies the process [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":423,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[114],"tags":[],"class_list":["post-422","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-general"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Convert Rows to Columns Without PIVOT in Oracle - Best 7 Ways<\/title>\n<meta name=\"description\" content=\"Discover 7 techniques to convert rows to columns in Oracle databases without using the PIVOT operator. 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