SNOW-3156626: force using 128mb string when overwriting an iceberg table

CHANGELOG.md

@@ -4,9 +4,12 @@
 
 ### Snowpark Python API Updates
 
+#### New Features
+
 #### Bug Fixes
 
 - Fixed a bug in `Session.client_telemetry` that trace does not have snowflake style trace id.
+- Fixed a bug when saving a fdn table into an iceberg table in overwrite mode, error is raised because `StringType` is saved in wrong length.
 - Fixed a bug in `ai_complete` where `model_parameters` and `response_format` values containing single quotes would generate malformed SQL.
 
 ## 1.47.0 (2026-03-05)

src/snowflake/snowpark/_internal/analyzer/analyzer_utils.py

@@ -1994,11 +1994,13 @@ def drop_table_if_exists_statement(table_name: str) -> str:
     return DROP + TABLE + IF + EXISTS + table_name
 
 
-def attribute_to_schema_string(attributes: List[Attribute]) -> str:
+def attribute_to_schema_string(
+    attributes: List[Attribute], is_iceberg: Optional[bool] = False
+) -> str:
     return COMMA.join(
         attr.name
         + SPACE
-        + convert_sp_to_sf_type(attr.datatype, attr.nullable)
+        + convert_sp_to_sf_type(attr.datatype, attr.nullable, is_iceberg=is_iceberg)
         + (NOT_NULL if not attr.nullable else EMPTY_STRING)
         for attr in attributes
     )

src/snowflake/snowpark/_internal/analyzer/snowflake_plan.py

@@ -1336,9 +1336,10 @@ def save_as_table(
         # in save as table. So we rename ${number} with COL{number}.
         hidden_column_pattern = r"\"\$(\d+)\""
         column_definition = None
+        is_iceberg = iceberg_config is not None
         if child_attributes is not None:
             column_definition_with_hidden_columns = attribute_to_schema_string(
-                child_attributes or []
+                child_attributes or [], is_iceberg=is_iceberg
             )
             column_definition = re.sub(
                 hidden_column_pattern,

src/snowflake/snowpark/_internal/type_utils.py

@@ -107,6 +107,8 @@
     except ImportError:
         ResultMetadataV2 = ResultMetadata
 
+_MAX_ICEBERG_STRING_SIZE = 134217728
+
 
 def convert_metadata_to_sp_type(
     metadata: Union[ResultMetadata, "ResultMetadataV2"],
@@ -318,7 +320,9 @@ def convert_sf_to_sp_type(
     )
 
 
-def convert_sp_to_sf_type(datatype: DataType, nullable_override=None) -> str:
+def convert_sp_to_sf_type(
+    datatype: DataType, nullable_override=None, is_iceberg: Optional[bool] = False
+) -> str:
     if context._is_snowpark_connect_compatible_mode:
         if isinstance(datatype, _IntegralType) and datatype._precision is not None:
             return f"NUMBER({datatype._precision}, 0)"
@@ -341,6 +345,8 @@ def convert_sp_to_sf_type(datatype: DataType, nullable_override=None) -> str:
     # We regard NullType as String, which is required when creating
     # a dataframe from local data with all None values
     if isinstance(datatype, StringType):
+        if is_iceberg:
+            return f"STRING({_MAX_ICEBERG_STRING_SIZE})"
         if datatype.length:
             return f"STRING({datatype.length})"
         return "STRING"

tests/integ/scala/test_dataframe_writer_suite.py

@@ -223,13 +223,6 @@ def test_iceberg(session, local_testing_mode):
     if not iceberg_supported(session, local_testing_mode) or is_in_stored_procedure():
         pytest.skip("Test requires iceberg support.")
 
-    session.sql(
-        "alter session set FEATURE_INCREASED_MAX_LOB_SIZE_PERSISTED=DISABLED"
-    ).collect()
-    session.sql(
-        "alter session set FEATURE_INCREASED_MAX_LOB_SIZE_IN_MEMORY=DISABLED"
-    ).collect()
-
     table_name = Utils.random_table_name()
     df = session.create_dataframe(
         [],
@@ -280,13 +273,6 @@ def test_iceberg_partition_by(session, local_testing_mode):
     if not iceberg_supported(session, local_testing_mode) or is_in_stored_procedure():
         pytest.skip("Test requires iceberg support.")
 
-    session.sql(
-        "alter session set FEATURE_INCREASED_MAX_LOB_SIZE_PERSISTED=DISABLED"
-    ).collect()
-    session.sql(
-        "alter session set FEATURE_INCREASED_MAX_LOB_SIZE_IN_MEMORY=DISABLED"
-    ).collect()
-
     df = session.create_dataframe(
         [],
         schema=StructType(

tests/integ/scala/test_datatype_suite.py

@@ -807,6 +807,76 @@ def test_iceberg_nested_fields(
         Utils.drop_table(structured_type_session, transformed_table_name)
 
 
+@pytest.mark.skipif(
+    "config.getoption('local_testing_mode', default=False)",
+    reason="local testing does not fully support iceberg tables yet.",
+)
+def test_iceberg_string_columns_use_max_size(session, local_testing_mode):
+    if not iceberg_supported(session, local_testing_mode):
+        pytest.skip("Test requires iceberg support.")
+
+    fdn_src_table = Utils.random_table_name()
+    iceberg_dest_table = Utils.random_table_name()
+    base_location = (
+        f"{ICEBERG_CONFIG['base_location']}/ice_varchar_repro_{uuid.uuid4().hex}"
+    )
+    iceberg_config = dict(ICEBERG_CONFIG)
+    iceberg_config["base_location"] = base_location
+
+    try:
+        # 1) Create destination Iceberg table.
+        session.sql(
+            f"""
+            CREATE OR REPLACE ICEBERG TABLE {iceberg_dest_table} (
+                NAME STRING, AGE INTEGER
+            )
+            CATALOG = '{ICEBERG_CONFIG["catalog"]}'
+            EXTERNAL_VOLUME = '{ICEBERG_CONFIG["external_volume"]}'
+            BASE_LOCATION = '{base_location}';
+            """
+        ).collect()
+
+        # 2) Create regular (FDN) source table.
+        session.sql(
+            f"CREATE OR REPLACE TABLE {fdn_src_table} (NAME VARCHAR, AGE INTEGER)"
+        ).collect()
+        session.sql(f"INSERT INTO {fdn_src_table} VALUES ('Bob', 25)").collect()
+
+        # 3) Read from normal table: VARCHAR maps to StringType(length=16777216).
+        fdn_df = session.table(fdn_src_table)
+        name_field = next(f for f in fdn_df.schema.fields if f.name.upper() == "NAME")
+        assert isinstance(name_field.datatype, StringType)
+        assert name_field.datatype.length == MAX_TABLE_STRING_SIZE
+
+        # 4) Overwrite Iceberg table using iceberg_config: STRING should be max-sized.
+        with session.query_history() as query_history:
+            fdn_df.write.mode("overwrite").save_as_table(
+                iceberg_dest_table, column_order="name", iceberg_config=iceberg_config
+            )
+
+        normalized_sqls = [
+            Utils.normalize_sql(q.sql_text).upper() for q in query_history.queries
+        ]
+        create_iceberg_sqls = [
+            s for s in normalized_sqls if "CREATE" in s and "ICEBERG TABLE" in s
+        ]
+        assert create_iceberg_sqls, (
+            "Expected Snowpark to issue a CREATE ... ICEBERG TABLE during overwrite, "
+            f"but none was found. Queries were: {normalized_sqls}"
+        )
+        assert any(
+            ("NAME STRING(134217728)" in s or '"NAME" STRING(134217728)' in s)
+            for s in create_iceberg_sqls
+        ), (
+            "Expected Iceberg CREATE TABLE to use max string size 134217728 for NAME, "
+            f"but got: {create_iceberg_sqls}"
+        )
+        assert not any("NAME STRING(16777216)" in s for s in create_iceberg_sqls)
+    finally:
+        Utils.drop_table(session, fdn_src_table)
+        Utils.drop_table(session, iceberg_dest_table)
+
+
 @pytest.mark.xfail(
     "config.getoption('local_testing_mode', default=False)",
     reason="local testing does not fully support structured types yet.",

tests/unit/test_types.py

@@ -1059,6 +1059,8 @@ def test_convert_sp_to_sf_type():
     assert convert_sp_to_sf_type(DoubleType()) == "DOUBLE"
     assert convert_sp_to_sf_type(StringType()) == "STRING"
     assert convert_sp_to_sf_type(StringType(77)) == "STRING(77)"
+    assert convert_sp_to_sf_type(StringType(), is_iceberg=True) == "STRING(134217728)"
+    assert convert_sp_to_sf_type(StringType(77), is_iceberg=True) == "STRING(134217728)"
     assert convert_sp_to_sf_type(NullType()) == "STRING"
     assert convert_sp_to_sf_type(BooleanType()) == "BOOLEAN"
     assert convert_sp_to_sf_type(DateType()) == "DATE"