Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17626
`udf(x, y) = 1` is deterministic no matter whether x or y is deterministic
or not, is because x, y are not used, in other words they don't affect the
result of the udf.
The result of `udf(x, y) = x + y` is deterministic or not, depending on
whether x and y are deterministic too. The result of `udf(rand(), rand())` is
not deterministic, for example.
I think `ScalaUDAF` is a bit different to `ScalaUDF`, because we don't push
down an aggregate function. But we will push down a `ScalaUDF` if it is
deterministic. Pushing down it might cause unexpected results.
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