SQL ranking functions are used to assign a rank or position to each row within a specific partition or result set based on a specified criteria. They can be very useful for analyzing data and identifying patterns or trends. Here are the most commonly used SQL ranking functions:
ROW_NUMBER() – This function assigns a unique sequential number to each row in a result set, starting from 1. It is often used to create a unique identifier for each row.
RANK() – This function assigns a rank to each row based on the specified criteria, with ties receiving the same rank. For example, if there are two rows with the same value, they will both receive the same rank and the next row will receive a rank that is two greater.
DENSE_RANK() – This function is similar to RANK(), but it does not leave any gaps in the ranking sequence. Ties receive the same rank, but the next rank is incremented by 1. For example, if there are two rows with the same value, they will both receive the same rank and the next row will receive a rank that is one greater.
NTILE() – This function divides the rows into a specified number of groups or buckets based on the specified criteria. For example, if there are 100 rows and you specify 4 buckets, each bucket will contain 25 rows.
PERCENT_RANK() – This function calculates the percentile rank of each row within the result set based on the specified criteria. It returns a value between 0 and 1, with 0 being the lowest rank and 1 being the highest rank.
CUME_DIST() – This function calculates the cumulative distribution of each row within the result set based on the specified criteria. It returns a value between 0 and 1, with 0 being the lowest distribution and 1 being the highest distribution.
Overall, SQL ranking functions are very powerful tools for analyzing and understanding data in a structured way. By using these functions, you can easily identify patterns, trends, and outliers within your data set.
