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The entity manager doesn’t know about them anymore, and you’ll probably get an “entity-not-persisted” error. Note: After calling $manager->clear(), all persisted entities are now unmanaged. To track progress, let’s print out some meta information (batch identifier and memory usage). After every batch, we’ll flush and clear the EntityManager (i.e., detach persisted entities) and tell the garbage collector to do its job. There are excellent resources on optimizing Doctrine and Symfony for batch processing, and we’re going to use some of these tips to optimize fixtures loading.įirst, we’ll define a batch size of 100 galleries. For 1,000 galleries with 5 to 10 images per gallery that would be 5,000 – 10,000 downloads, which is really slow. Additionally, Faker is downloading a random image for every gallery entry. Now, if we run bin/refreshDb.sh, after some time we’ll probably get a not-so-nice message like PHP Fatal error: Allowed memory size of N bytes exhausted.Īpart from slow execution, every error would result in an empty database because EntityManager is flushed only at the very end of the fixture class. src/DataFixtures/ORM/LoadGalleriesData.phpĬlass LoadGalleriesData extends AbstractFixture implements ContainerAwareInterface, OrderedFixtureInterface We could try increasing the COUNT constant in our fixture classes and seeing what will happen: // src/DataFixtures/ORM/LoadUsersData.phpĬlass LoadUsersData extends AbstractFixture implements ContainerAwareInterface, OrderedFixtureInterface Generating thousands of entries takes some time (and computer resources), so we want to do it only once. a larger amount of database entries and image files for this project). Testing app performance, simulating real-world traffic and detecting bottlenecks requires bigger datasets (i.e. Simple fixtures like the ones we created in the previous article are great for the development phase, where loading ~30 entities is done quickly, and it can often be repeated while changing the DB schema. Once your entities are polished, and you’ve had your “That’s it! I’m done!” moment, it’s a perfect time to create a more significant dataset that can be used for further testing and preparing the app for production.
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If that’s the case, use this post as an explainer on how it was done.Īs a bonus, we’ll demonstrate how to set up a simple PHPUnit test suite with basic smoke tests. Note: if you did the “ Getting started with the app” step in the previous post, you’ve already followed the steps outlined in this post. The next step on our journey is to populate the database with a somewhat realistic amount of data to test application performance. In the previous article, we demonstrated how to set up a Symfony project from scratch with Flex, and how to create a simple set of fixtures and get the project up and running.
