Category: 01. Aggregate Function

In Oracle, window functions offer a powerful way to perform aggregate calculations without collapsing rows into a single result. Unlike traditional aggregate functions that group data, window functions maintain the original dataset while providing aggregated values based on specified partitions. The syntax is: SELECT column_name, aggregate_function() OVER (PARTITION BY column_name) FROM table_name;. For example:

When working with large datasets, performance becomes a critical concern, especially when using aggregate functions. Aggregate operations can be resource-intensive, leading to longer query execution times. To optimize performance, indexing relevant columns is recommended, as it allows the database engine to access data more efficiently. Additionally, minimizing the dataset before applying aggregate functions can significantly…

Using the DISTINCT keyword with the COUNT() function allows users to count unique values in a specified column. This can be especially useful when analyzing categorical data or identifying the diversity of entries. The syntax is as follows: SELECT COUNT(DISTINCT column_name) FROM table_name WHERE condition;. For example, to count the number of unique job titles…

The HAVING clause is used to filter the results of aggregated queries after the GROUP BY clause has been applied. It enables users to set conditions on aggregated values, making it possible to refine results based on calculations. The syntax for HAVING is: SELECT column_name, aggregate_function(column_name) FROM table_name GROUP BY column_name HAVING condition;. For example,…

The GROUP BY clause is a powerful SQL feature that allows users to summarize data by specific categories before applying aggregate functions. By grouping rows that share common attributes, it enables more detailed analysis. The syntax for using GROUP BY is straightforward: SELECT column_name, aggregate_function(column_name) FROM table_name GROUP BY column_name;. For example, to calculate the…

One of the key aspects of aggregate functions in Oracle is their handling of NULL values. All aggregate functions, except for COUNT(*), ignore NULL entries. This behavior is important as it ensures that calculations are based solely on valid data. For example, when using SUM(), any NULL values in the column are excluded from the…

The MAX() function retrieves the largest value in a specified column. It is commonly used to identify the highest scores, maximum sales figures, or peak performance indicators. The syntax for MAX() is similar to that of other aggregate functions: SELECT MAX(column_name) FROM table_name WHERE condition;. For instance, to find the highest salary in a company,…

The MIN() function is used to retrieve the smallest value from a specified column in a dataset. This function is particularly useful for identifying the lowest scores, minimum sales, or least significant performance indicators. The syntax is simple: SELECT MIN(column_name) FROM table_name WHERE condition;. For example, to find the lowest salary among employees, you would…

The COUNT() function counts the number of rows that meet specific criteria in a dataset. It is versatile and can be used in different forms: COUNT(*) counts all rows, including NULLs, while COUNT(column_name) counts only non-NULL values. The syntax is as follows: SELECT COUNT(*) FROM table_name WHERE condition;. For instance, to count the total number…

The AVG() function computes the average (mean) of numeric values in a specified column. This function is invaluable for understanding trends in datasets, particularly when analyzing performance or financial metrics. The syntax for AVG() is similar to that of SUM(): SELECT AVG(column_name) FROM table_name WHERE condition;. For example, to find the average salary of employees…