As intuitive and streamlined as ecommerce technology might seem from the user's perspective, it involves so much data that engineering ingenuity and smart database management must constantly deliver in order to keep up. At organizations like Shopify—responsible for the easy and reliable transactions at top brands around the world—that excellence of performance involves deep monitoring of their MySQL core and their Redis caching infrastructure, plus insightful query profiling, packet captures, and the admittance of developers to platforms that measure database performance.

Shopify’s motto is “Make commerce better for everyone.” That mantra applies whether the shopping's done online, on mobile, or in-store. For Shopify's engineering team, better means a fast, reliable application that delivers a positive …

This question was asked at support by a customer to solve a difficult issue.

How to identify a sporadic burst of queries coming from one of the hosts accessing the database ?

If there are hundreds of hosts, it can be challenging, especially if the queries are fast. No chance for them to get logged in the famous slow query log !

Here is the solution using the performance_schema in MySQL 5.6 :

SELECT
host,
SUM(essbben.count_star) AS total_statements,
format_time(SUM(essbben.sum_timer_wait)) AS total_latency,
format_time(SUM(essbben.sum_timer_wait) / SUM(count_star))
AS avg_latency
FROM
performance_schema.events_statements_summary_by_host_by_event_name essbben
GROUP BY
host
ORDER BY
SUM(sum_timer_wait) DESC;

Here is the result :

+---------------+------------------+---------------+-------------+
| host          | total_statements | total_latency | avg_latency | …