Eloquent Performance Patterns

2h 12m 50s
English
Paid

Learn how to drastically improve the performance of your Laravel applications by pushing more work to the database, all while still using the Eloquent ORM.

Read more about the course

Performance issues suck. Customers are frustrated. Your servers are overloaded. Management is breathing down your neck.

You've already solved all your N+1 issues, added the necessary indexes, and you're even paying for the most expensive database server available. But despite all this, some things just feel impossible to build in a performant way.

  1. We can't paginate results in the database because they depend on authorization checks that happen in Laravel.

  2. We have to do some really complicated calculations on large data sets, which seems impossible without a real programming language like PHP.

  3. We can't sort results in the database, because we have to sort by values computed in our application.

So you invest months into different caching strategies to try and speed things up, but caching is hard. Every time you think you've solved a performance problem, you have a new caching problem to deal with instead.

I've been there and it sucks. So one day I decided “that's it, I'm going to figure out how to push all this work to the database if it kills me.” The results blew my mind.

By leveraging advanced database techniques, like sub queries, conditional aggregates, and aggressive use of scopes, pages that took 30+ seconds to load were now loading within 500ms!!

I've since spoken about Eloquent and database performance at both Laracon Online and Laracon US, and have written in-depth articles on the topic.


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# Title Duration
1 Measuring your database performance 04:43
2 Minimizing memory usage by selecting only 04:29
3 Getting one record from has-many relationships 09:44
4 Creating dynamic relationships using sub queries 06:10
5 Calculating totals using conditional aggregates 04:21
6 Optimizing circular relationships 04:25
7 Setting up multi-column searching 04:07
8 Getting LIKE to use an index 05:05
9 Faster options than whereHas 03:55
10 When it makes sense to run additional queries 03:08
11 Using UNIONs to run queries independently 07:58
12 Fuzzier searching using regular expressions 04:45
13 Running authorization policies in the database 06:04
14 Faster ordering using compound indexes 04:05
15 Ordering by has-one relationships 01:38
16 Ordering by belongs-to relationships 01:39
17 Ordering by has-many relationships 04:21
18 Ordering by belongs-to-many relationships 05:39
19 Ordering with NULLs always last 07:36
20 Ordering by custom algorithms 06:38
21 Filtering and sorting anniversary dates 07:04
22 Making N+1 issues impossible 03:24
23 Ordering data for humans using natural sort 04:20
24 Full text searching with rankings 05:07
25 Getting the distance between geographic points 03:23
26 Filtering by geographic distance 03:00
27 Ordering by geographic distance 01:26
28 Filtering by geospatial area 04:36

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