alexott commented on code in PR #27912:
URL: https://github.com/apache/airflow/pull/27912#discussion_r1032459844
##########
airflow/providers/databricks/hooks/databricks_sql.py:
##########
@@ -163,38 +163,43 @@ def run(
:param return_last: Whether to return result for only last statement
or for all after split
:return: return only result of the LAST SQL expression if handler was
provided.
"""
- self.scalar_return_last = isinstance(sql, str) and return_last
+ self.descriptions = []
if isinstance(sql, str):
if split_statements:
- sql = self.split_sql_string(sql)
+ sql_list = [self.strip_sql_string(s) for s in
self.split_sql_string(sql)]
else:
- sql = [self.strip_sql_string(sql)]
+ sql_list = [self.strip_sql_string(sql)]
+ else:
+ sql_list = [self.strip_sql_string(s) for s in sql]
- if sql:
- self.log.debug("Executing following statements against Databricks
DB: %s", list(sql))
+ if sql_list:
+ self.log.debug("Executing following statements against Databricks
DB: %s", sql_list)
else:
raise ValueError("List of SQL statements is empty")
results = []
- for sql_statement in sql:
+ for sql_statement in sql_list:
Review Comment:
Yes, this is done to support Azure Active Directory authentication - when we
have long-running queries, AAD token may expire, so next queries will fail. To
mitigate this, DBSQL hook checks if the AAD token is expiring, and renewing it.
This is necessary right now as DBSQL connector for Python doesn't have built-in
AAD auth support - this will come together with unified Python SDK next year.
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