I’ve been going through the MySQL slow query log at my new job to optimize our applications performance. It’s a bit more scary making changes when you’re the “new guy” because there are a lot of “gotchas” you haven’t quite figured out in the new platform. Well one of the queries that I wanted to optimize lead me to get rid of some needless LEFT JOINS and trim down the amount of fields returned in the result set. Aside from testing the application as a whole after making my modification I needed a fast way to verify the exact same data was being returned for all 50,000 rows. One option was to append each field to a string and then convert that into an MD5 hash for each variation of the query. That seemed half assed too me so I decided to export the results to a CSV file then run a diff against the two from the linux shell. Read the rest of this entry »
Posts Tagged ‘query optimization’
MySQL Optimization Tip: Checking for Differences in Queries.
MySQL Temporary Tables Example – Optimizing PHP Applications
Shortly after starting a new job as Web Application Developer with an e-commerce company I was tasked with rewriting a legacy application. After analyzing and flow charting the current application I found numerous performance penalties, bloated code, linear programming (non-OOP), and many other areas for optimization. Even after refactoring the code and removing these performance barriers the application was a bit sluggish. Though I had improved overall application execution time by 90% I still knew there was more I could do. This is where temporary tables came into play.
MySQL Temporary Tables have the same functionality as standard disk-based tables except they exist in memory. Since memory is not long term storage, they are temporary tables, hence the name. Operating in memory makes working with these tables fast, your only limit is the amount of memory/swap space available to you.
Optimize MySQL Queries – Fast Inserts With Multiple Rows
I was programming some code that needed to do a lot of inserts a few months back. I hypothesized that creating a big SQL insert statement would be faster than executing a bunch of small insert statements. I didn’t have time to create a test, but I wanted to go back and test this theory at some point. The idea was that even though there is a penalty for looping through an array and accessing a variable to build the SQL statement that it would still be faster than asking PHP to send a bunch of tiny querries.
My test server is my local machine running Ubuntu 10.04, dual 1.80Ghz core Intel processors with 2 GB of memory. Its running the latest stable release of PHP5, Apache2, and MySql5. I used the standard php mysql_connect function, not mysqli. The database engine used in this test was MyIsam. I performed 1000 inserts in the first test, I then altered the code to build one giant insert. I restarted the apache and mysql server after the first scenario.