"The following source:\n" + query + "\n ... is empty"

)

high_precision_number_columns = [

col["column_name"]

for col in metadata

if col["type_code"] == 0 and col["scale"] == 0 and col["precision"] > 19

]

if high_precision_number_columns:

max_selects = [

f'MAX("{col}") AS "{col}"' for col in high_precision_number_columns

]

query = (

f"SELECT {', '.join(max_selects)} FROM {self.get_table_query_string()}"

)

with GetSnowflakeConnection(config.offline_store) as conn:

result = execute_snowflake_statement(conn, query).fetch_pandas_all()

for col in high_precision_number_columns:

max_value = result[col].iloc[0]

if max_value is not None:

str_length = len(str(int(max_value)))

for row in metadata:

if row["column_name"] == col:

if str_length <= 9:

row["snowflake_type"] = "NUMBER32"

elif str_length <= 19:

row["snowflake_type"] = "NUMBER64"

else:

raise NotImplementedError(

f"Number in column {col} larger than INT64 is not supported"

)

for row in metadata:

if row["type_code"] == 0:

if row["scale"] == 0:

elif row["precision"] <= 18: # max precision size to ensure INT64

row["snowflake_type"] = "NUMBER64"

else:

column = row["column_name"]

with GetSnowflakeConnection(config.offline_store) as conn:

query = f'SELECT MAX("{column}") AS "{column}" FROM {self.get_table_query_string()}'

result = execute_snowflake_statement(

conn, query

).fetch_pandas_all()

if (

result.dtypes[column].name

in python_int_to_snowflake_type_map

):

row["snowflake_type"] = python_int_to_snowflake_type_map[

result.dtypes[column].name

]

else:

if len(result) > 0:

max_value = result.iloc[0][0]

if max_value is not None and len(str(max_value)) <= 9:

row["snowflake_type"] = "NUMBER32"

continue

elif (

max_value is not None and len(str(max_value)) <= 18

):

row["snowflake_type"] = "NUMBER64"

continue

raise NotImplementedError(

"NaNs or Numbers larger than INT64 are not supported"

)

continue

else:

row["snowflake_type"] = "NUMBERwSCALE"