**Spark >= 2.3**

It is possible to disable some optimizations using `asNondeterministic`

method:

```
import org.apache.spark.sql.expressions.UserDefinedFunction
val f: UserDefinedFunction = ???
val fNonDeterministic: UserDefinedFunction = f.asNondeterministic
```

Please make sure you understand the guarantees before using this option.

**Spark < 2.3**

Function which is passed to udf should be deterministic (with possible exception of SPARK-20586) and nullary functions calls can be replaced by constants. If you want to generate random numbers use on of the built-in functions:

`rand`

–*Generate a random column with independent and identically distributed (i.i.d.) samples from U[0.0, 1.0].*`randn`

–*Generate a column with independent and identically distributed (i.i.d.) samples from the standard normal distribution.*

and transform the output to obtain required distribution for example:

```
(rand * Integer.MAX_VALUE).cast("bigint").cast("string")
```