Correlation is a statistical relationship between two variables such that when one variable changes, it leads to a change in the other variable. Correlation analysis measures the extent to which the two variables are correlated.

If an increase in one variable leads to an increase in another, it is called a positive correlation. If an increase in one variable leads to a decrease in the other, it is a negative correlation.

Spark supports two correlation algorithms: Pearson and Spearman. Pearson algorithm works with two continuous variables, such as a person's height and weight or house size and house price. Spearman deals with one continuous and one categorical variable, for example, zip code and house price.