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How long does simple update take in MySQL?
We are having trouble with simple updates on a single table taking a long time. The table contains ~5 Million rows. This query updates ~80k rows and takes around 60 seconds to complete, and the more rows updated the longer it takes which results in timeouts.
Which is faster InnoDB or MySQL simple update?
Packing UUIDs into BINARY (16) would shrink the table, thereby providing more speed. Updating 80K rows at once takes a lot of effort, especially when planning for a possible ROLLBACK. This may partially explain why InnoDB seems to be slower than MyISAM.
When to use skip locked in MySQL 8.0?
MySQL 8.0 introduced support for both SKIP LOCKED and NO WAIT. SKIP LOCKED is useful for implementing a job queue (a.k.a batch queue) so that you can skip over locks that are already locked by a concurrent transaction. NO WAIT is useful for avoiding waiting until a concurrent transaction releases the locks that we are also interested in locking.
Why do we use no wait in MySQL?
NO WAIT is useful for avoiding waiting until a concurrent transaction releases the locks that we are also interested in locking. Without NO WAIT, we either have to wait until the locks are released (at commit or release time by the transaction that currently holds the locks) or the lock acquisition times out.
Why is InnoDB so slow compared to MyISAM?
This may partially explain why InnoDB seems to be slower than MyISAM. Will you often update that many rows? Sound like a design flaw. InnoDB in MySQL is really not well adapted to this type of data volume.
Why do you need hot update in SQL?
Normally, HOT updates can recycle dead rows on a data page and make UPDATEs a lot faster – effectively removing (most of) the need for vacuuming. Related: If your column is used in any index in any way, HOT UPDATEs are disabled, because it would break the index (es).
What’s the fastest way to update a table?
If you update large parts of your table, building new indexes from scratch is much faster than incrementally updating indexes with every changed row. Also, your update is not likely to break any foreign key constraints. You could try to delete & recreate those, too.