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This diary is about load testing. I find load testing useful mainly because of two reasons: 1. it shows multiuser access problems; 2. it shows how good is the implementation.

The idea is to simulate mapathon. A mapathon is an event where multiple mappers map the same (big) area. To manage the work, the area is divided into smaller squares. Then, each mapper asks the server to map or review a square, works some time on the square, and finally asks the server to mark the square as needs mapping, needs review, or is done.

I use to load test the damn server. The test file is part of the repository. There is 80 % of mappers, 20 % of reviewers, and 2 testing areas. Each mapper/reviewer works for 30 - 60 seconds, then waits for 30 - 60 seconds, and then works again. All the mappers are spawned within the first minute. The test is stopped soon after there is 0 % to map for both of the areas. runs on $5/month VPS with 1 GB RAM, single 2.2 GHz vCPU, and 25 GB SSD disk.

100 mappers handled The first round of load testing gives the idea about the server after the refactoring. The average response time for 100 mappers is 270 ms. Not bad, I would say.

It’s a bit worse when testing 200 mappers, though. I’ve stopped the test after 20 minutes.

Some improvements Two years ago, I decided that there must be some better solution for the problem of dividing a big area into smaller squares. I found that there is PostGIS extension to PostgreSQL so I decided to go with it. Two year later (now,) I’ve discovered database indexes.

Also, I’ve read part of the documentation and set postgres parameters.

Finally, I switched gzip on.

200 mappers handled Pretty small changes, but I had to figure them out. I noted my journey in this thread. Anyway, with the changes applied, I load tested again. The average response time of 275 ms for 200 mappers looks good.

Writing good code is green. Don’t waste energy.


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