1. A method for optimizing an order of execution of multiple join operations based on at least a first data column and a second data column in a database system having multiple processing units, the method comprising: providing, by one or more processors, at least a first partitioning of the first data column, wherein said at least the first partitioning splits the first data column into a plurality of first subsets of rows, each of the first subsets of rows being correlated with a distinct processing unit from the multiple processing units, wherein each of the first subsets of rows are handled by processing units that differ from one another; providing, by one or more processors, at least a second partitioning of the second data column, wherein said at least the second partitioning splits the second data column into a plurality of second subsets of rows, each of the second subsets of rows being correlated with a distinct processing unit from the multiple processing units, wherein each of the second subsets of rows are handled by processing units that differ from one another; estimating, by one or more processors, cardinalities of sub-tables derived by a respective joining of a subset of rows of the first data column and a subset of rows of the second data column which are processed by a same processing unit from the multiple processing units, wherein the cardinalities of the sub-tables describe a quantity of rows in the sub-tables, and wherein the cardinalities of the sub-tables derived by the respective joining of the subset of rows of the first data column and the subset of rows of the second data column are estimated according to: F ⁡ ( a , b ) = ∑ i = 0 n - 1 ⁢ ( max ⁡ ( ∫ x i x i + 1 ⁢ f ⁡ ( x ) ⁢ dx , 0 ) u 1 i * max ⁡ ( ∫ x i x i + 1 ⁢ g ⁡ ( x ) ⁢ dx , 0 ) u 2 i ) * max ⁡ ( u 1 i , u 2 i ) where x 0 =a; x n =b; x i ∈[a,b]; f(x) is a density distribution function of a first data column R; g(x) is a density distribution function of a second data column S; a, b are a starting row and end row of respective columns R and S which are incorporated into a join; U 1 i is a number of unique values of the first data column R in a respective interval i; U 2 i is a number of unique values of the second data column S in the respective interval i; F(a,b) is an estimated number of rows of a resulting joined table T by joining the first and second data columns R, S in an interval [a,b]; max ⁡ ( ∫ x i x i + 1 ⁢ f ⁡ ( x ) ⁢ dx , 0 ) u 1 i represents an average number of rows per unique value in an [x i ;x i+1 ]-section for the first data column R; max ⁡ ( ∫ x i x i + 1 ⁢ g ⁡ ( x ) ⁢ dx , 0 ) u 2 i represents an average number of rows per unique value in the [x i ;x i+1 ]-section for the second data column S; and max (U 1 i ,U 2 i ) is used to derive a maximum value of numbers of unique values contained in [x i ;x i+1 ]-sequences of the first and second data columns R, S; and optimizing, by one or more processors, an order of execution of multiple join operations based on the estimated cardinalities of the sub-tables, wherein optimizing the order of execution of the multiple join operations avoids intermediate data skew by joining sub-tables having quantities of rows that have a same value.