Use decimal precision metadata when reading from parquet files (#9162)

Closes #8354.

Authors:
  - Ashwin Srinath (https://github.com/shwina)

Approvers:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

URL: #9162

python/cudf/cudf/_lib/parquet.pyx

@@ -185,22 +185,13 @@ cpdef read_parquet(filepaths_or_buffers, columns=None, row_groups=None,
 
     update_struct_field_names(df, c_out_table.metadata.schema_info)
 
-    if df.empty and meta is not None:
-        cols_dtype_map = {}
-        for col in meta['columns']:
-            cols_dtype_map[col['name']] = col['numpy_type']
-
-        if not column_names:
-            column_names = [o['name'] for o in meta['columns']]
-            if not is_range_index and index_col in cols_dtype_map:
-                column_names.remove(index_col)
-
-        for col in column_names:
-            meta_dtype = cols_dtype_map.get(col, None)
-            df._data[col] = cudf.core.column.column_empty(
-                row_count=0,
-                dtype=cudf.dtype(meta_dtype)
-            )
+    # update the decimal precision of each column
+    if meta is not None:
+        for col, col_meta in zip(column_names, meta["columns"]):
+            if isinstance(df._data[col].dtype, cudf.Decimal64Dtype):
+                df._data[col].dtype.precision = (
+                    col_meta["metadata"]["precision"]
+                )
 
     # Set the index column
     if index_col is not None and len(index_col) > 0:

python/cudf/cudf/tests/test_parquet.py

@@ -2047,3 +2047,29 @@ def test_parquet_writer_nulls_pandas_read(tmpdir, pdf):
     got = pd.read_parquet(fname)
     nullable = True if num_rows > 0 else False
     assert_eq(gdf.to_pandas(nullable=nullable), got)
+
+
+def test_parquet_decimal_precision(tmpdir):
+    df = cudf.DataFrame({"val": ["3.5", "4.2"]}).astype(
+        cudf.Decimal64Dtype(5, 2)
+    )
+    assert df.val.dtype.precision == 5
+
+    fname = tmpdir.join("decimal_test.parquet")
+    df.to_parquet(fname)
+    df = cudf.read_parquet(fname)
+    assert df.val.dtype.precision == 5
+
+
+def test_parquet_decimal_precision_empty(tmpdir):
+    df = (
+        cudf.DataFrame({"val": ["3.5", "4.2"]})
+        .astype(cudf.Decimal64Dtype(5, 2))
+        .iloc[:0]
+    )
+    assert df.val.dtype.precision == 5
+
+    fname = tmpdir.join("decimal_test.parquet")
+    df.to_parquet(fname)
+    df = cudf.read_parquet(fname)
+    assert df.val.dtype.precision == 5