[WIP] Allocate validity masks on output arrays of groupbys

python/cudf/dataframe/column.py

@@ -106,15 +106,10 @@ def __init__(self, data, mask=None, null_count=None):
                 nnz = _gdf.count_nonzero_mask(self._mask.mem,
                                               size=len(self))
                 null_count = len(self) - nnz
-                if null_count == 0:
-                    self._mask = None
             else:
                 null_count = 0
 
         assert 0 <= null_count <= len(self)
-        if null_count == 0:
-            # Remove mask if null_count is zero
-            self._mask = None
 
         self._null_count = null_count
 

python/cudf/groupby/groupby.py

@@ -14,6 +14,8 @@
 from libgdf_cffi import ffi, libgdf
 from librmm_cffi import librmm as rmm
 
+from .utils import make_mask
+
 
 class Groupby(object):
     """Groupby object returned by cudf.DataFrame.groupby().
@@ -109,11 +111,18 @@ def _apply_agg(self, agg_type, result, add_col_values,
                 out_col_values = ffi.NULL
 
             if agg_type == "count":
-                out_col_agg_series = Series(
-                    Buffer(rmm.device_array(col_agg.size, dtype=np.int64)))
+                out_col_agg_series = Series.from_masked_array(
+                    data=rmm.device_array(col_agg.size, dtype=np.int64),
+                    mask=make_mask(col_agg.size)
+                )
             else:
-                out_col_agg_series = Series(Buffer(rmm.device_array(
-                    col_agg.size, dtype=self._df[val_col]._column.data.dtype)))
+                out_col_agg_series = Series.from_masked_array(
+                    data=rmm.device_array(
+                        col_agg.size,
+                        dtype=self._df[val_col]._column.data.dtype
+                    ),
+                    mask=make_mask(col_agg.size)
+                )
 
             out_col_agg = out_col_agg_series._column.cffi_view
 

python/cudf/utils/cudautils.py

@@ -181,7 +181,8 @@ def gpu_fill_value(data, value):
 def fill_value(arr, value):
     """Fill *arr* with value
     """
-    gpu_fill_value.forall(arr.size)(arr, value)
+    if arr.size > 0:
+        gpu_fill_value.forall(arr.size)(arr, value)
 
 
 @cuda.jit
@@ -373,9 +374,10 @@ def gpu_fill_masked(value, validity, out):
 
 def fillna(data, mask, value):
     out = rmm.device_array_like(data)
-    out.copy_to_device(data)
-    configured = gpu_fill_masked.forall(data.size)
-    configured(value, mask, out)
+    if out.size > 0:
+        out.copy_to_device(data)
+        configured = gpu_fill_masked.forall(data.size)
+        configured(value, mask, out)
     return out