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fix: athena-iceberg/schema-evolution/new-columns-empty-in-athena #3067

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20 changes: 16 additions & 4 deletions awswrangler/athena/_write_iceberg.py
Original file line number Diff line number Diff line change
Expand Up @@ -549,10 +549,6 @@ def to_iceberg( # noqa: PLR0913

schema_differences["missing_columns"] = {}

# Ensure that the ordering of the DF is the same as in the catalog.
# This is required for the INSERT command to work.
df = df[catalog_cols]

if schema_evolution is False and any([schema_differences[x] for x in schema_differences]): # type: ignore[literal-required]
raise exceptions.InvalidArgumentValue(f"Schema change detected: {schema_differences}")

Expand All @@ -570,6 +566,22 @@ def to_iceberg( # noqa: PLR0913
boto3_session=boto3_session,
)

# Ensure that the ordering of the DF is the same as in the catalog.
# This is required for the INSERT command to work.
# update catalog_cols after altering table
catalog_column_types = typing.cast(
Dict[str, str],
catalog.get_table_types(
database=database,
table=table,
catalog_id=catalog_id,
filter_iceberg_current=True,
boto3_session=boto3_session,
),
)
catalog_cols = [key for key in catalog_column_types]
df = df[catalog_cols]

# if mode == "overwrite_partitions", drop matched partitions
if mode == "overwrite_partitions":
delete_from_iceberg_table(
Expand Down
55 changes: 55 additions & 0 deletions tests/unit/test_athena_iceberg.py
Original file line number Diff line number Diff line change
Expand Up @@ -1212,3 +1212,58 @@ def test_athena_to_iceberg_alter_schema(
)

assert_pandas_equals(df, df_actual)


@pytest.mark.parametrize("partition_cols", [None, ["name"]])
def test_athena_to_iceberg_append_schema_evolution(
path: str,
path2: str,
path3: str,
glue_database: str,
glue_table: str,
partition_cols: list[str] | None,
) -> None:
df = pd.DataFrame(
{
"id": [1, 2, 3, 4, 5],
"name": ["a", "b", "c", "a", "c"],
"age": [None, None, None, None, 50],
}
)
df["id"] = df["id"].astype("Int64") # Cast as nullable int64 type
df["name"] = df["name"].astype("string")
df["age"] = df["age"].astype("Int64") # Cast as nullable int64 type
split_index_rows = 4
split_index_columns = 2

wr.athena.to_iceberg(
df=df.iloc[:split_index_rows, :split_index_columns],
database=glue_database,
table=glue_table,
table_location=path,
temp_path=path2,
partition_cols=partition_cols,
keep_files=False,
)

wr.athena.to_iceberg(
df=df.iloc[split_index_rows:, :],
database=glue_database,
table=glue_table,
table_location=path,
temp_path=path2,
partition_cols=partition_cols,
schema_evolution=True,
keep_files=False,
mode="append",
s3_output=path3,
)

df_actual = wr.athena.read_sql_query(
sql=f'SELECT * FROM "{glue_table}" ORDER BY id',
database=glue_database,
ctas_approach=False,
unload_approach=False,
)

assert_pandas_equals(df, df_actual)