Sequence expression can overflow

Spark has a (long-standing) overflow bug in the sequence expression.

Consider the following operations:

spark.sql("CREATE TABLE foo (l LONG);")
spark.sql(s"INSERT INTO foo VALUES (${Long.MaxValue});")
spark.sql("SELECT sequence(0, l) FROM foo;").collect()

The result of these operations will be:

Array[org.apache.spark.sql.Row] = Array([WrappedArray()])

an unintended consequence of overflow.

The sequence is applied to values 0 and Long.MaxValue with a step size of 1 which uses a length computation defined here. In this calculation, with start = 0, stop = Long.MaxValue, and step = 1, the calculated len overflows to Long.MinValue. The computation, in binary looks like:

{{0111111111111111111111111111111111111111111111111111111111111111 -}}

{{0000000000000000000000000000000000000000000000000000000000000000}}

{{------------------------------------------------------------------      0111111111111111111111111111111111111111111111111111111111111111 /}}

{{0000000000000000000000000000000000000000000000000000000000000001}}

{{------------------------------------------------------------------                0111111111111111111111111111111111111111111111111111111111111111 +}}

{{0000000000000000000000000000000000000000000000000000000000000001}}

{{------------------------------------------------------------------      1000000000000000000000000000000000000000000000000000000000000000}}

The following check passes as the negative Long.MinValue is still <= MAX_ROUNDED_ARRAY_LENGTH. The following cast to toInt uses this representation and truncates the upper bits resulting in an empty length of 0.

Other overflows are similarly problematic.