In our previous post, we discussed the different ways to collect data about slow queries - MySQL offers slow log, general log and binary log. Using tcpdump, you can grab network traffic data - a good and low-impact method of collecting basic metrics for slow queries. So, now that you are sitting on top of a large pile of data, perhaps tens of gigabytes of logs, how do you get a whole picture of the workload?
Mid to large size applications tend to have hundred of SQL statements distributed throughout a large code base, with potentially hundreds of queries running every second. That can generate a lot of data. How do we identify causes of bottlenecks slowing down our applications? Obviously, going through the information query by query would not be great - we’ll get drowned with all the entries. We need to find a way to …
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