cherry-pick

tests/integration/test_writes/test_writes.py

@@ -789,25 +789,3 @@ def test_hive_catalog_storage_descriptor(
     assert len(tbl.scan().to_arrow()) == 3
     # check if spark can read the table
     assert spark.sql("SELECT * FROM hive.default.test_storage_descriptor").count() == 3
-
-
-@pytest.mark.integration
-@pytest.mark.parametrize("format_version", [1, 2])
-def test_python_writes_special_character_column_with_spark_reads(
-    spark: SparkSession, session_catalog: Catalog, format_version: int
-) -> None:
-    identifier = "default.python_writes_special_character_column_with_spark_reads"
-    column_name_with_special_character = "letter/abc"
-    TEST_DATA_WITH_SPECIAL_CHARACTER_COLUMN = {
-        column_name_with_special_character: ['a', None, 'z'],
-    }
-    pa_schema = pa.schema([
-        (column_name_with_special_character, pa.string()),
-    ])
-    arrow_table_with_special_character_column = pa.Table.from_pydict(TEST_DATA_WITH_SPECIAL_CHARACTER_COLUMN, schema=pa_schema)
-    tbl = _create_table(session_catalog, identifier, {"format-version": format_version}, schema=pa_schema)
-
-    tbl.overwrite(arrow_table_with_special_character_column)
-    spark_df = spark.sql(f"SELECT * FROM {identifier}").toPandas()
-    pyiceberg_df = tbl.scan().to_pandas()
-    assert spark_df.equals(pyiceberg_df)