Karthik Appigatla, Sr. Database Engineers, LinkedIn, and Basavaiah Thambara, LinkedIn
This talk is about a new way of monitoring and analyzing millions of queries with no overhead.
Optimizing queries is the most important aspect of scaling database servers. Before we can optimize, we need to identify the problematic queries. We have slow-query log in MySQL where we can set a threshold and all the queries crossing threshold will be logged in a file and later can be used for analysis. Other way is to use performance_schema database inside MySQL which gives various metrics of queries.
The problem is that enabling the slow query log will incur a 25-35% overhead on the database, since we have to have to write to a file. Additionally, since only queries exceeding the threshold will be logged, we won't have any data about queries below that threshold. Meanwhile, enabling performance_schema incurs a 10-20% overhead, and is complex to understand.
To minimize overhead and effectively measure all queries, we have built a query analyzer which incurs less than 3% CPU overhead and no overhead on any other resources.
Karthik Appigatla, Sr. Database Engineer, LinkedIn
Karthik Appigatla is a database evangelist currently working for LinkedIn, Bangalore. Earlier he worked for companies like Yahoo, Pythian and Percona. Please check his LinkedIn profile to know about his work. LinkedIn Profile: https://www.linkedin.com/in/appigatla/
Basavaiah Thambara, Sr. Database Engineer, LinkedIn
Basavaiah Thambara (Basu) has decade of experience designing, building and scaling MySQL databases. He is currently working as a staff database engineer at LinkedIn managing Espresso, an in-house distributed NoSQL datastore. He currently lives in Bangalore,India https://in.linkedin.com/in/basavaiaht
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author = {Karthik Appigatla and Basavaiah Thambara},
title = {Capturing and Analyzing Millions of Queries without Any Overhead},
year = {2017},
address = {Dublin},
publisher = {USENIX Association},
month = aug
}