Fixing flushing tokens workflow
During a backport patch [0] for this fix
it was found some problems in the previous
approach like, It didn't enabled back the
session.autocommit. Another comment was we should
create a new session and commit on it instead of
disable/enable autocommit.
After this, we should backport this change in order
to fix the previous releases, instead of the other
one.
[0] https://review.openstack.org/#/c/469514
Change-Id: Ifc024ba0e86bb71f4ab8b019917782bc5bf3be7a
Closes-Bug: #1649616
(cherry picked from commit 0b5c5c03ec
)
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parent
76bdca6498
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@ -276,9 +276,12 @@ class Token(token.persistence.TokenDriverBase):
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return _expiry_range_all
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def flush_expired_tokens(self):
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with sql.session_for_write() as session:
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# Turn off autocommit, as it doesn't work well with batch delete
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session.autocommit = False
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# The DBAPI itself is in a "never autocommit" mode,
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# BEGIN is emitted automatically as soon as any work is done,
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# COMMIT is emitted when SQLAlchemy invokes commit() on the
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# underlying DBAPI connection. So SQLAlchemy is only simulating
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# "begin" here in any case, it is in fact automatic by the DBAPI.
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with sql.session_for_write() as session: # Calls session.begin()
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dialect = session.bind.dialect.name
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expiry_range_func = self._expiry_range_strategy(dialect)
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query = session.query(TokenModel.expires)
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@ -291,9 +294,14 @@ class Token(token.persistence.TokenDriverBase):
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# Explicitly commit each batch so as to free up
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# resources early. We do not actually need
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# transactional semantics here.
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session.commit()
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session.commit() # Emits connection.commit() on DBAPI
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# Tells SQLAlchemy to "begin", e.g. hold a new connection
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# open in a transaction
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session.begin()
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total_removed += row_count
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LOG.debug('Removed %d total expired tokens', total_removed)
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# When the "with: " block ends, the final "session.commit()"
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# is emitted by enginefacade
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session.flush()
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LOG.info(_LI('Total expired tokens removed: %d'), total_removed)
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@ -0,0 +1,6 @@
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---
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fixes:
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- |
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[`bug 1689616 <https://bugs.launchpad.net/keystone/+bug/1649616>`_]
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Significant improvements have been made when performing a token flush
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on massive data sets.
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