Invalidating query cache entries mysql

05-Feb-2020 00:37 by 5 Comments

Invalidating query cache entries mysql - Online free sex videos chate

Is there a way to just clear the cache table entries for all updates from a binlog file if it's behind in time?slave info: os version: redhat linux mysql v5.5.15-log binlog format= mixed file: master-bin.000426 pos: 353,906,762 id | user | host | db | Command | Time | State | Info 18796 | system user | | NULL | Connect | 802 | Waiting for master to send event | NULL 18797 | system user | | NULL | Connect | 6265 | invalidating query cache entries (table) | NULL master info: os version: redhat linux mysql v5.5.15-log.

"Be cautious about sizing the query cache excessively large, which increases the overhead required to maintain the cache, possibly beyond the benefit of enabling it. See bug #38551 (must be fixed in 5.5.8, but anyway). It was ROW based replication when the problem was occuring.Also, check INNODB STATUS for thread with this status reported. I've now set this to mixed to see if this stops the problem as a workaround.XX Waiting for query cache lock INSERT INTO `db B`.`table B` (...) VALUES (...) ON DUPLICATE KEY UPDATE ... Simultaneous SELECT and INSERT in one database seems to cause a dead lock with query cache update by INSERT ON DUPLICATE KEY UPDATE in a different database.If I turn off either the Replication or the Query Cache then the lock up does not happen.The slave continues to move forward on the position, but not fast enough to catch-up to the master.

My assumption is that each time it reads a position or several positions from the binlog it has to go and invalidate the query cache entry table due to updates, and that process is super-expensive.Rows: ~49,917,839 Inno DB latin1_swedish_ci Size: 28.7 Gi B I've now yet been able to repeat with 100% accuracy.Any help as to how best to test my theory would be greatly appreciated.#53375 seems to suggest this being a consequence of primary keys.Everyone of the tables in the database has a primary key., mostly INSERT statements, around 5-10 rows per second. In 5-10 seconds when it will be time to process new data again the same lock up will happen. Query #2 is the updating of the post-processed data.