[FEA] Add binop operators that match Spark's expected NaN behavior

[razajafri]

Describe the bug Spark expects Nans to perform differently from other languages. Currently, cudf isn't behaving how we expect it to behave as per spark

Steps/Code to reproduce bug

TEST_F(BinaryOperationIntegrationTest, Greater_Scalar_Vector_Nan) {
  auto lhs = cudf::make_numeric_scalar(cudf::data_type(cudf::FLOAT32));
  auto s = 
    static_cast< cudf::experimental::scalar_type_t<float>* >(lhs.get());
  s->set_value(NAN);
  cudf::test::fixed_width_column_wrapper<float> rhs{{INFINITY, 1.02, 5.0, NAN, -43.2, -INFINITY}};
  using TypeOut = cudf::experimental::bool8;
  using GREATER = cudf::library::operation::Greater<TypeOut, float, float>;
  cudf::test::fixed_width_column_wrapper<TypeOut> expected{true, true, true, false, true, true};
  auto out = cudf::experimental::binary_operation(
      *lhs, rhs, cudf::experimental::binary_operator::GREATER,
      data_type(experimental::type_to_id<TypeOut>()));  
  cudf::test::expect_columns_equal(expected, out->view());
}

TEST_F(BinaryOperationIntegrationTest, Equal_Scalar_Vector_Nan) {
  auto lhs = cudf::make_numeric_scalar(cudf::data_type(cudf::FLOAT32));
  auto s = 
    static_cast< cudf::experimental::scalar_type_t<float>* >(lhs.get());
  s->set_value(NAN);
  cudf::test::fixed_width_column_wrapper<float> rhs{{INFINITY, 1.02, 5.0, NAN, -43.2, -INFINITY}};
  using TypeOut = cudf::experimental::bool8;
  using LESS = cudf::library::operation::Less<TypeOut, float, float>;
  cudf::test::fixed_width_column_wrapper<TypeOut> expected{false, false, false, true, false, false};
  auto out = cudf::experimental::binary_operation(
      *lhs, rhs, cudf::experimental::binary_operator::EQUAL,
      data_type(experimental::type_to_id<TypeOut>()));  
  cudf::test::expect_columns_equal(expected, out->view());
}

The above tests fail with the following error

[ RUN      ] BinaryOperationIntegrationTest.Greater_Scalar_Vector_Nan
../tests/utilities/column_utilities.cu:237: Failure
      Expected: differences.size()
      Which is: 5
To be equal to: size_t{0}
      Which is: 0
first difference: lhs[0] = 1, rhs[0] = 0
[  FAILED  ] BinaryOperationIntegrationTest.Greater_Scalar_Vector_Nan (1 ms)
[ RUN      ] BinaryOperationIntegrationTest.Equal_Scalar_Vector_Nan
../tests/utilities/column_utilities.cu:237: Failure
      Expected: differences.size()
      Which is: 1
To be equal to: size_t{0}
      Which is: 0
first difference: lhs[3] = 1, rhs[3] = 0
[  FAILED  ] BinaryOperationIntegrationTest.Equal_Scalar_Vector_Nan (240 ms)

Here is the output from the Java unit test displaying the entire column output

  @Test
  void testNanFloatsComparisons() {
    try (ColumnVector floats = ColumnVector.fromBoxedFloats(Float.POSITIVE_INFINITY, 1.02f, 5.0f, Float.NaN, -43.2f, Float.NEGATIVE_INFINITY);
        Scalar nan = Scalar.fromFloat(Float.NaN);
        ColumnVector floatsGreatherThanNan = floats.greaterThan(nan);
        ColumnVector floatsLessThan = floats.lessThan(nan);
        ColumnVector floatsEquals = floats.equalTo(nan)) {
      HostColumnVector floatsGreaterThan_h = floatsGreatherThanNan.copyToHost();
      HostColumnVector floatsLessThan_h = floatsLessThan.copyToHost();
      HostColumnVector floatsEqualTo_h = floatsEquals.copyToHost();
      for(int i = 0 ; i < floatsGreaterThan_h.getRowCount() ; i++) {
        System.out.printf(""| %b | %b | %b |\n"", floatsGreaterThan_h.getBoolean(i), floatsLessThan_h.getBoolean(i), floatsEqualTo_h.getBoolean(i));
      }
    }
  }

+-------+-------+-------+
| gt    |  lt   |  eq   |
+-------+-------+-------+
| false | false | false |
| false | false | false |
| false | false | false |
| false | false | false |
| false | false | false |
| false | false | false |
+-------+-------+-------+

Expected behavior The above tests should pass

Additional context The above tests are for float32 but similar test should pass for float64

[harrism]

So that readers don't have to compile and run your tests just to think about this bug, please print out the values you get in out for each test and paste them here. Please include what spark expects as well.

[razajafri]

Thanks for looking @harrism. I have updated the bug with the test output. I will update it further with the entire output in the AM

[jrhemstad]

It would be a lot easier to understand the issue if the expected/actual behavior were summarized in a table. Can you please fill in the Actual column?

NaN > x

x	Expected	Actual
INFINITY	true	false
1.02	true	false
5.0	true	false
NaN	false	false
-43.2	true	false
-INFINITY	true	false

NaN == x	x	Expected	Actual
INFINITY	false	false
1.02	false	false
5.0	false	false
NaN	true	false
-43.2	false	false
-INFINITY	false	false

[shwina]

Pandas behaviour in the above cases:

In [8]: x = pd.Series([np.inf, 1.02, 5.0, np.nan, -43.2, -np.inf])

In [9]: np.nan > x
Out[9]:
0    False
1    False
2    False
3    False
4    False
5    False
dtype: bool

In [10]: np.nan == x
Out[10]:
0    False
1    False
2    False
3    False
4    False
5    False
dtype: bool

In [11]: np.nan != x
Out[11]:
0    True
1    True
2    True
3    True
4    True
5    True
dtype: bool

This looks to be inline with the IEE 754 standard.

[jrhemstad]

Seeing as though Spark's behavior is non-conformant with IEEE 754, I'm going to label this as a feature request rather than a bug. Supporting this behavior in libcudf will require adding new binop operators that support the non-conformant behavior, like SPARK_MAX/SPARK_MIN.

[razajafri]

@jrhemstad I have updated the table.

[razajafri]

@jrhemstad is this still valid? considering we have decided to abide by the NaN behavior set by IEEE 754

[jrhemstad]

@jrhemstad is this still valid? considering we have decided to abide by the NaN behavior set by IEEE 754

Thanks for the reminder.

Per conversation in https://github.com/rapidsai/cudf/issues/4760, this should be implemented via composition of other libcudf features. Closing.