In PostgreSQL, we can use the ANY() construct to perform searches against arrays. It returns a Boolean result, and so we can incorporate this into our searches to return just those rows that yield true or false, as the case may be.
There’s also a SOME() construct, which is a synonym for ANY().
In PostgreSQL, the array_upper() function returns the upper bound of the specified array dimension. We pass the array as well as the dimension, and it returns the upper bound accordingly.
In PostgreSQL, the array_lower() function returns the lower bound of the specified array dimension. We pass the array and the relevant dimension, and it returns the lower bound for that dimension.
In PostgreSQL the array_ndims() function returns the number of dimensions of an array. We pass the array to the function, and it returns an integer of the number of dimensions in the array.
This function is not to be confused with the array_dims() function, which returns a more detailed text representation of the dimensions in the array.
If you’re getting an error that starts with “sample size must be between…” when using the array_sample() function in PostgreSQL, it’s probably because your second argument is either a negative value, or it’s larger than the number of elements in the array.
The second argument must be no less than zero, and it can’t be any larger than the number of elements in the array.
To fix this error, be sure that your second argument is greater than zero and less than or equal to the number of elements in the array at the first argument.
In PostgreSQL we can use the array_dims() function to return information about the dimensions in an array. The function accepts the array in question, and it returns a text representation of the array’s dimensions.
This function is not to be confused with the array_ndims() function, which simply returns the number of dimensions in an array.
In PostgreSQL we can use the random_normal() function to generate a normally-distributed random number.
A normally-distributed random number is a random variable with a Gaussian distribution. This is said to be normally distributed, and is referred to as a normal deviate.
In PostgreSQL we have the ability to create variable-length multidimensional arrays and define columns as array types.
Here’s a quick overview of PostgreSQL arrays.
If you’re getting a PostgreSQL error that reads “function generate_subscripts(integer, integer) does not exist“, it’s probably because your first argument is not an array. This specific error message implies that the first argument is an integer, but we’d get a similar error when passing a numeric argument.
The first argument for this function must be an array.
To fix this error, be sure that your first argument to generate_subscripts() is an array.
If you’re getting an error that reads “invalid input syntax for type integer…” when using the array_sample() function in PostgreSQL, it’s probably because your second argument is not an integer.
The second argument for this function must be an integer.
To fix this error, be sure that your second argument to array_sample() is an integer.