Tuning Your MySQL Queries
Tuning Your MySQL Queries
Get a look at the latest updates to MySQL and how to boost read-only queries with this interview of Oracle's Oystein Grovlen.
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Built by the engineers behind Netezza and the technology behind Amazon Redshift, AnzoGraph™ is a native, Massively Parallel Processing (MPP) distributed Graph OLAP (GOLAP) database that executes queries more than 100x faster than other vendors.
Welcome to another post in the series of Percona Live featured tutorial speakers blogs! In these blogs, we’ll highlight some of the tutorial speakers that will be at this year’s Percona Live conference. We’ll also discuss how these tutorials can help you improve your database environment. Make sure to read to the end to get a special Percona Live 2017 registration bonus!
In this Percona Live featured tutorial, we’ll meet Øystein Grøvlen, senior principal software engineer at Oracle. His tutorial is on How to Analyze and Tune MySQL Queries for Better Performance. SQL query performance plays a big role in application performance. If some queries execute slowly, these queries or the database schema may need tuning. I had a chance to speak with Øystein and learn a bit more about the MySQL query tuning:
Percona: How did you get into database technology? What do you love about it?
Øystein: I got into database technology during my Ph.D. studies. I got in touch with a research group in Trondheim, Norway, that did research on highly available distributed database systems. I ended up writing a thesis on query processing in such database systems.
What I love most about my job on the MySQL Optimizer Team is that it involves a lot of problem-solving. Why is a query so slow? What can we do to improve it? I have always been very interested in sports results and statistics. Working with query execution times gives me much of the same feeling. Searching for information is another interest of mine, and that is really what query execution is about.
Percona: What impacts database performance the most?
Øystein: From my point of view — mainly concerned with the performance of read-only queries — the most important performance metric is how much data needs to be accessed in order to answer a query. For update-intensive workloads, it is often about concurrency issues. For SELECT statements, the main thing is to not access more data than necessary.
Users should make sure to design their database schema so that the database system can efficiently access the needed data. This includes creating the right indexes. As MySQL developers, we need to develop the right algorithms to support efficient retrieval. We also need to provide a query optimizer that can pick the best query execution plan.
Of course, there are other performance aspects that are important. Especially if your data cannot fit in your database buffer pool. In that case, the order in which you access the data becomes more important. The best query plan when your data is disk-bound is not necessarily the same as when all data is in memory.
Percona: Your tutorial is called “How to Analyze and Tune MySQL Queries for Better Performance.” What are the most recent MySQL updates that help with tuning queries?
Øystein: I think the biggest improvements came in MySQL 5.6, with increased observability through performance schema and new variants of EXPLAIN (Structured EXPLAIN (JSON format) and visual EXPLAIN in MySQL Workbench). We also added Optimizer Trace, which gives insight into how the optimizer arrived at a certain query plan. All this made it easier to identify queries that need tuning, understand how a query is executed and what might be done to improve it.
In MySQL 5.7, we added a new syntax for optimizer hints, and provided a lot of new hints that can be used to influence the optimizer to change a non-optimal query plan. We also provided a query rewrite plugin that makes it possible to tune queries even when it is not possible to change the application.
MySQL 5.7 also came with improvements to EXPLAIN. It is now possible to get the query plan for a running query, and Structured EXPLAIN shows both estimated total query cost and the cost per table. A more experimental feature allows you to provide your own cost constants to the optimizer. This way, you can configure the optimizer to better suit your particular system.
For MySQL 8.0 we are continuing to improve tunability by adding more optimizer hints. At the same time, we are working hard on features that will reduce the need for tuning. Histograms and awareness of whether data is in memory or on disk make the optimizer able to pick better query plans.
Percona: What do you want attendees to take away from your tutorial session? Why should they attend?
Øystein: While the query optimizer in most cases will come up with a good query plan, there are some cases where it won’t generate the most optimal query plan. This tutorial will show how you can identify which queries need tuning, how you can further investigate the issues and what types of tuning options you have for different types of queries. By attending this tutorial, you will learn how to improve the performance of applications through query tuning.
Percona: What are you most looking forward to at Percona Live?
Øystein: I am looking forward to interacting with MySQL users, discussing the query performance issues they might have, and learning how I can help with their issues.
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