notimplemented for partitioned as well

python/cudf/cudf/io/parquet.py

@@ -813,6 +813,11 @@ def _parquet_to_frame(
             **kwargs,
         )
 
+    if nrows is not None or skip_rows is not None:
+        raise NotImplementedError(
+            "nrows/skip_rows is not supported when reading a partitioned parquet dataset"
+        )
+
     partition_meta = None
     partitioning = (dataset_kwargs or {}).get("partitioning", None)
     if hasattr(partitioning, "schema"):
@@ -842,12 +847,6 @@ def _parquet_to_frame(
                 key_paths,
                 *args,
                 row_groups=key_row_groups,
-                # TODO: is this still right?
-                # Also, do we still care?
-                # partition_keys uses pyarrow dataset
-                # (which we can't use anymore after pyarrow is gone)
-                nrows=nrows,
-                skip_rows=skip_rows,
                 **kwargs,
             )
         )

python/cudf/cudf/tests/test_parquet.py

@@ -1970,6 +1970,26 @@ def test_parquet_partitioned(tmpdir_factory, cols, filename):
                 assert fn == filename
 
 
+@pytest.mark.parametrize("kwargs", [{"nrows": 1}, {"skip_rows": 1}])
+def test_parquet_partitioned_notimplemented(tmpdir_factory, kwargs):
+    # Checks that write_to_dataset is wrapping to_parquet
+    # as expected
+    pdf_dir = str(tmpdir_factory.mktemp("pdf_dir"))
+    size = 100
+    pdf = pd.DataFrame(
+        {
+            "a": np.arange(0, stop=size, dtype="int64"),
+            "b": np.random.choice(list("abcd"), size=size),
+            "c": np.random.choice(np.arange(4), size=size),
+        }
+    )
+    pdf.to_parquet(pdf_dir, index=False, partition_cols=["b"])
+
+    # Check that cudf and pd return the same read
+    with pytest.raises(NotImplementedError):
+        cudf.read_parquet(pdf_dir, **kwargs)
+
+
 @pytest.mark.parametrize("return_meta", [True, False])
 def test_parquet_writer_chunked_partitioned(tmpdir_factory, return_meta):
     pdf_dir = str(tmpdir_factory.mktemp("pdf_dir"))