Join Percona Chief Evangelist Colin Charles as he covers happenings, gives pointers and provides musings on the open source database community.

Don’t wait, submit a talk for Percona Live Europe 2018 to be held in Frankfurt 5-7 November 2018. The call for proposals is ending soon, there is a committee being created, and it is a great conference to speak at, with a new city to boot!

Releases

• A big release, MySQL 8.0.12, with INSTANT ADD COLUMN support, BLOB optimisations, changes around replication, the query rewrite plugin and lots more. Naturally this also means the connectors get bumped up to the 8.0.12, including a nice new …

In this short blog post, I will show you how you can compare current and past time series in Percona Monitoring and Management (PMM).

Recently, a support customer shared a graph with us that compared query throughput between today and yesterday as a confirmation that optimizing their server variables improved performance.

Do you want to compare workload between today and yesterday? This week and last week? Or this month and last month? You can do this by simply duplicating an existing data source of a graph, but add a time offset so it will render past data. You can specify past offsets in (s)econds, (m)inutes, (h)ours, (d)ays, (w)eeks and even (y)ears.

Say you want to graph query throughput from a certain time period and one day before that. To do this, select the “MySQL Overview” dashboard, and then click the header of “MySQL Questions” panel. The panel menu should appear:

Click the …

Welcome to another post in our series of interview blogs for the upcoming Percona Live Europe 2017 in Dublin. This series highlights a number of talks that will be at the conference and gives a short preview of what attendees can expect to learn from the presenter.

This blog post is with Daniel Lee, a software developer at Grafana. His tutorial is Visualize Your Data With Grafana. This presentation teaches you how to create dashboards and graphs in Grafana and how to use them to gain insight into the behavior of your systems. In our conversation, we discussed how data visualization could benefit your database …

I love graphs. They just make things easier when it comes to finding patterns. I also love visibility. Having the ability to known what is going on inside the database is priceless. How about having visibility of the slow queries execution time on a graph? Let’s do it.

We’ve already described how to get query digest using performance schema. Since the MySQL server is already doing the heavy lifting for you with little-to-no overhead, this information is available practically at will. So let’s make some graphs with that data.

To accomplish this I will use the well-known tool Graphite to store and render time-series data. For those who are not familiar with Graphite, it’s actually a 3-piece tool, consisting of:

• The …

When you make a change to your MySQL configuration in production it would be great to know the impact (a “before and after” type of picture). Some changes are obvious. For many variables proper values can be determined beforehand, i.e. innodb_buffer_pool_size or innodb_log_file_size. However, there is 1 configuration variable which is much less obvious for many people working with MySQL: query_cache.

The idea of query cache is great, however, there are a lot of issues with MySQL query …

Following up to my previous blog on graphing statement execution in performance_schema, Sunny Bains on the InnoDB team pointed out that in looking at the INSERT graph, he didn’t think I had atomic operations enabled within my build.

Particularly here (from trunk):

225 /******************************************************************//**
226 Increments lock_word the specified amount and returns new value.
227 @return lock->lock_word after increment */
228 UNIV_INLINE
229 lint
230 rw_lock_lock_word_incr(
231 /*===================*/
232         rw_lock_t*      lock,           /*!< in/out: rw-lock */
233         ulint           amount)         /*!< in: amount of increment */
234 {
235 #ifdef …

I tried to come up with a number of topics for this post, but none seemed to really convey what I really feel.. And really this blog is about all of them..

• A look at PERFORMANCE_SCHEMA.STAGES and PERFORMANCE_SCHEMA.STATEMENTS
• Graphing MySQL Statement Execution
• A MySQL visual EXPLAIN plan with PERFORMANCE_SCHEMA
• Tracing Sessions with PERFORMANCE_SCHEMA

If that doesn’t whet your appetite (and trust me, I need to, this post is long, but I feel is worth reading all the way to the end), then let me start out by asking the question:

Wouldn’t you like to be able to trace what a SQL statement did, either in the same or another session, on a production instance, after the fact? Wouldn’t you like to know where all of it’s time was spent, and some statistics on what it was doing specifically?

I know, …

If you have been wondering why the overview and graphs pages say “no data to display” on the graphs when you first install Kontrollbase, it’s because there’s no data in the database being returned from the queries that generate the graphs – this is because a new install has no data to graph. This has […]

Only a few weeks after Walter’s session on Multi-Master Replication with MMM and thanks to the great gang at MySQL Docs (my colleagues from long ago!) I’ll be doing a MySQL University session in a few days, about the GRAPH computation engine. From talks/demos I’ve done about it so far, I’ve learnt that people love it but there are lots of interesting questions. After all, it’s a pretty new and in a way exotic thing.

MySQL University uses DimDim, an online presentation service. You’ll see slides, and hear my voice. You can also type questions in a live chat room. We actually even got desktop sharing working so a live demo is possible, we’ll see how that goes on the day (I’ll make sure to have static slides for the same also

For session details and the exact link to DimDim, see the …

First, the back story. One of the MEM developers asked me today about an interesting problem:

We have graphs in MEM that can be generated against an arbitrary time range in the UI - even for a year or more if the data is not purged. Currently MEM does not do any kind of rolling up of the data (in an RRD style), and pulls graph data from each agent/instance on a 1 minute interval. So if you wanted to pull, for instance, the last 3 months worth of data in to a graph - the server back end basically goes back to the database and requests all of the rows - all ~43,829 of them, oh, and that’s for each series - and then calculate deltas on the server side if need be (we store raw values), and stuffs the data in to a graphing library to draw the graph.

Further, graphs are only of a limited (but adjustable) size on the …