In this post I will share a recovery scenario of a MySQL database restore from the binary logs. This post is also a good example of how we can achieve…

The post How to Restore / point in time recovery using binary logs MySQL first appeared on Change Is Inevitable.

Earlier this week, I presented a webinar on MySQL High Availability options for MySQL – what they are and how to choose the most appropriate one for your application.

The replay of this webinar can now be viewed here or if you just want to look at the charts then scroll down. At the end of this post, I include a summary of the Q&A from the webinar.

How important is your data? Can you afford to lose it? What about just some of it? What would be the impact if you couldn’t access it for a minute, an hour, a day or a week?

Different applications can have very different requirements for High Availability. Some need 100% …

MySQL 5.7 has had some great improvements within Performance Schema to be able to better trace what connections are doing, from adding memory information, through to transaction information, metadata locking, prepared statements, and even user variables, so far (there is still more to come in the next release – stay tuned).

Of course there are other improvements on top of this as well, such as the …

This past week was marked by a series of personal findings related to the use of Global Transaction IDs (GTIDs) on Galera-based clusters such as Percona XtraDB Cluster (PXC). The main one being the fact that transactions touching MyISAM tables (and FLUSH PRIVILEGES!) issued on a giving node of the cluster are recorded on a GTID set bearing the node’s server_uuid as “source id” and added to the binary log (if the node has binlog enabled), thus being replicated to any async replicas connected to it. However, they won’t be replicated across the cluster (that is, all of this is by design, if wsrep_replicate_myisam is …

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In this new webinar-on-demand, you will learn

MySQL’s default storage engine as of version 5.5 is InnoDB. InnoDB maintains a storage area called the buffer pool for caching data and indexes in memory. By keeping the frequently-accessed data in memory, related searches are retrieved much faster than reading from disk.

When you stop or restart MySQL, you lose the cached data stored in the buffer pool. There is a feature in MySQL 5.6 which allows you to dump the contents of the buffer pool before you shutdown the mysqld process. Then, when you start mysqld again, you can reload the contents of the buffer pool back into memory. You may also …

In a previous post, titled “Multi-threaded replication with MySQL 5.6: Use GTIDs,” I explained that using GTID replication is almost a requirement when using MySQL 5.6 MTS. Let’s see now how to perform the day-to-day operations when MTS and GTIDs are both enabled. (I’ll also be presenting a related webinar next week titled “Multi-threaded Replication in MySQL 5.6 and 5.7″).

Seeing the execution gaps

If you have a look at SHOW SLAVE STATUS while the slave is running, you may not be expecting such an output:

[...]
Executed_Gtid_Set: …

Carrying on with my MySQL 5.7 Labs Multi Source Replication scenario, I wanted to evaluate performance impact via MySQL Enterprise Monitor.

Whilst I opened my environment, I remember that I had generated lots of different skeleton scripts that allowed me to deploy the 50 servers quickly, and I didn’t want to add each of my targets 1 by 1 in MEM. So, I used one of the many features available, “Add Bulk MySQL Instances”.

So, I’ve got 50 (3001-3050) masters but only 1 slave (3100).

By default, MEM monitors it’s own repository, i.e. the 1/1 server being monitored in the All group.

I want to add my slave in first, because that’s how I’m organizing things, and I’ll take the opportunity to create the monitoring group I want to …

As a MySQL DBA I already know the data changes that happen on my system. I have logs for that.

However, it’s a common problem that several years into the life of an application, the current developers won’t know where in the codebase queries come from. It’s often hard for them to find the location in the code if queries are formed dynamically; the pattern I show them to optimize doesn’t match anything in the code.

I stumbled on a trick a couple years ago that has been invaluable in tracking down these problematic queries: query comments.

Here’s an example:

When a query generally shows up in a slow query log, it might look something like this:

# Time: 150217 10:26:01
# User@Host: comments[comments] @ localhost []  Id:    13
# Query_time: 0.000231  Lock_time: 0.000108 Rows_sent: 3  Rows_examined: 3
SET timestamp=1424186761;
select * from cars;

That logging shows me who executed the query …

There were so many valuable articles already written by others over past years explaining all details about InnoDB transaction isolation modes and how to deal with this. So, I'll avoid to repeat what was already said ;-) -- my attention attracted the performance study made by PeterZ and published in the following article: http://www.percona.com/blog/2015/01/14/mysql-performance-implications-of-innodb-isolation-modes/ -- the article is very good and providing a good analyze of the observed problem which is solved by using READ-COMMITTED transaction isolation instead of REPEATABLE-READ (which is default in InnoDB).. The natural question is coming then: why don't we have then the READ-COMMITTED mode by default?.. Is there any danger?..

Let's then investigate together..

First of all, you should …