def compile_cast(t, expr, scope, **kwargs):
op = expr.op()
if isinstance(op.to, dtypes.Interval):
if isinstance(op.arg.op(), ops.Literal):
return interval(op.arg.op().value, op.to.unit)
else:
raise com.UnsupportedArgumentError(
'Casting to intervals is only supported for literals '
'in the PySpark backend. {} not allowed.'.format(type(op.arg)))
if isinstance(op.to, dtypes.Array):
cast_type = ibis_array_dtype_to_spark_dtype(op.to)
else:
cast_type = ibis_dtype_to_spark_dtype(op.to)
src_column = t.translate(op.arg, scope)
return src_column.cast(cast_type)
def compile_elementwise_udf(t, expr, scope):
op = expr.op()
spark_output_type = ibis_dtype_to_spark_dtype(op._output_type)
spark_udf = pandas_udf(op.func, spark_output_type, PandasUDFType.SCALAR)
func_args = (t.translate(arg, scope) for arg in op.func_args)
return spark_udf(*func_args)
