charm-percona-cluster/unit_tests
Trent Lloyd 0697559b51 wsrep_slave_threads: default to 48 on bionic
This improves performance significantly for environments constrained by
calls to sync() such as HDDs or lower-end SSDs (or just very busy
environments running many queries)

By default the the queries from other nodes are only processed with
1 thread, which means they will always run slower than on the master and
any long running query will hold up all other queries behind it.

Additionally, when multiple queries commit at once the server can
combine them together into a single on-disk sync ('group commit') which
is not possible otherwise. This optimisation appears to only occur on
Bionic (Percona 5.7) and not Xenial (Percona 5.6).

On Bionic, default to 48 threads which experimentally is a good number
for OpenStack environments without being too crazy high. Galera ensures
that queries that are dependent on each other are still executed
sequentially and generally it is not expected to cause replication
inconsistencies.

However Percona Cluster 5.6 on Xenial appears to have a bug handling
foreign key constraints that causes them to be violated (LP #1823850).
The result is that the slave node crashes out and has to do a full SST
to recover. The same issue is not present on the master. Thus we leave
the default wsrep_slave_threads=1 on Xenial to avoid this issue for now
particularly since Xenial does not appear to be able to use Group Commit
to optimise the number of sync requests generated by the queries - so
this option does not really improve performance there anyway.

Partial-Bug: #1822903
Change-Id: Ic9cdd6562f30a3e52aa3d26fea53ba7c2bbdc771
2019-04-09 15:55:19 +08:00
..
__init__.py Revert "Convert the charm to Python 3" 2019-03-14 15:12:50 +00:00
test_actions.py Series Upgrade 2018-09-17 15:38:00 +02:00
test_percona_hooks.py wsrep_slave_threads: default to 48 on bionic 2019-04-09 15:55:19 +08:00
test_percona_utils.py Revert "Convert the charm to Python 3" 2019-03-14 15:12:50 +00:00
test_utils.py Revert "Convert the charm to Python 3" 2019-03-14 15:12:50 +00:00