July 29, 2014

How can we bring query to the data?

Baron recently wrote about sending the query to the data looking at distributed systems like Cassandra. I want to take a look at more simple systems like MySQL and see how we’re doing in this space. It is obvious getting computations as closer to the data as possible is the most efficient as we will […]

MySQL Query Patterns, Optimized – Webinar questions followup

On Friday I gave a presentation on “MySQL Query Patterns, Optimized” for Percona MySQL Webinars.  If you missed it, you can still register to view the recording and my slides. Thanks to everyone who attended, and especially to folks who asked the great questions.  I answered as many as we had time for  during the session, but here […]

Analyzing Slow Query Table in MySQL 5.6

Next week I’m teaching an online Percona Training class, called Analyzing SQL Queries with Percona Toolkit.  This is a guided tour of best practices for pt-query-digest, the best tool for evaluating where your database response time is being spent. This month we saw the GA release of MySQL 5.6, and I wanted to check if any […]

Write contentions on the query cache

While doing a performance audit for a customer a few weeks ago, I tried to improve the response time of their top slow query according to pt-query-digest‘s report. This query was run very frequently and had very unstable performance: during the time data was collected, response time varied from 50µs to 1s. When I ran […]

Visualization tools for pt-query-digest tables

When you process MySQL slow query logs using pt-query-digest you can store samples of each query into query_review table and historical values for review trend analysis into query_review_history table. But it could be difficult to easily browse those tables without a good GUI tool. For the visual browsing of tables created by pt-query-digest you may […]

Identifying the load with the help of pt-query-digest and Percona Server

Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make […]

Distributed Set Processing with Shard-Query

Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]

Getting MySQL to use full key length

There is one bug, or “missing feature” in MySQL Optimizer which may give you hard time causing performance problems which may be hard to track down, it is using only part of the index when full index can be used or using shorter index while there is longer index available. The last item is yet […]

Feature Idea: Finding columns which query needs to access

In query examinations it is often interesting which columns query needs to access to provide result set as it gives you ideas if you can use covering indexes to speed things up or even cache some data by denormalizing tables. So far it has to be done manually – look at SELECT clause, WHERE clause, […]