For example, does the FK need to be the first field in a unique together?
It seems like a lot of code to generate the tables in the first place and you STILL need to read the output scripts just to ensure the ORM isn't generating some garbage you didn't want.
That seems like a lot of extra effort when a simple migration service (such as liquibase) could do the same work running SQL directly. No question on "which indexes are getting created and why". No deep knowledge of Django interactions with sql. Instead, it's just directly running the SQL you want to run.
I don’t want to go without an ORM because I’ll end up making one ad-hoc anyway. I’m not going to do work on raw tuples in my application code.
I go the liquibase route for migrations, and just use the mapping portion of any ORM.
"Wow, 1-2 command and my app and database are in sync!"
In reality, migration tools are 100% about data loss prevention.
If you do not care about data loss, updating your schema is trivial, just drop everything and create. Dev environments should be stateless anyways, using separate data "fixtures" when needed.
Data loss itself is a highly nuanced topic. Some data is replaceable, some might be protected in a separate store. So I agree that ORMs should challenge the assumption that automatic migration tools need to be part of their kitchen sink.
Liquibase starts with "Write your database change code in your preferred authoring tool in SQL, YAML, JSON, or XML." So instead of just having my ORM generate that and I just have to read them to ensure correctness, I have to manually write change scripts instead? I don't see how that's is comparable.
Liquibase could certainly come in after I have some SQL scripts generated from my ORM and do whatever it does.
My assumption is that people have used orms that automatically add the index for you when you create a relationship so they just conflate them all. Often they’ll say that a foreign key is needed to improve the performance and when you dig into it, their mental model is all wrong. The sense they have is that the other table gets some sort of relationship array structure to make lookups fast.
It’s an interesting phenomenon of the abstraction.
Don’t get me wrong, I love sqlalchemy and alembic but probably because I understand what’s happening underneath so I know the right way to hold it so things are efficient and migrations are safe.
Is it? In Postgres, all FK references must be to a column with a PK or unique constraint or part of another index. Additionally, Postgres and Maria (maybe all SQL?) automatically create indexes for PKs and unique constraints. There's a high likelihood that a foreign key is already indexed _in the other table_.
Generally, I agree with your statement. Adding a FK won't magically improve performance or create useful indices. But, the presence of a FK or refactoring to support a FK does (tangentially) point back to that index.
Django automatically creates an index on the referencing table to ensure that joins are fast. The fact that you have the relationship in the ORM means that’s how you’re likely to access the data so it makes perfect sense.
The mental model mismatch I’ve seen is that people appear to think of the relationship as being on the parent object “pointing” at the child table.
FWIW, I've also asked everyone I've interviewed in the past decade about indexes and FKs. Most folks I've talked to seem to understand FKs. They're often fuzzier on the details of indexes, but I don't recall anyone conflating the two.
Depending upon the database storage engine, available memory, and table size I could see there being _some_ performance hit if only PKs are used for statistics but I'd think that modern RDBMSes are smart enough to cache appropriately. Am I missing something?
Maybe they were thinking about something like the "clustered indexes" from SQL Server, and mistakenly thought PostgreSQL also worked like that:
> "When you create a PRIMARY KEY constraint, a unique clustered index on the column or columns is automatically created if a clustered index on the table doesn't already exist and you don't specify a unique nonclustered index." [1]
> "Clustered indexes sort and store the data rows in the table or view based on their key values." [2]
So I'm guessing you could squeeze some extra performance for certain access patterns, maybe? I have not worked at any place where I had needed to worry about low level details like this, though, so obligatory disclaimer to take this comment with a grain of salt due to my lack of first-hand experience.
[1]: https://learn.microsoft.com/en-us/sql/relational-databases/i...
[2]: https://learn.microsoft.com/en-us/sql/relational-databases/i...
In postgres, primary key is basically unique index with some special semantics.
- The kind of person to dive into the schema and worry about an unnecessary index
- Smart enough to heed Django's warnings and use `Meta.UniqueConstraint`
- Dumb enough to ignore Django's warnings and not use `Meta.Indexes`
I think it's funny that the kind of dev that 100% relies on the ORM and would benefit from this warning would probably never find themselves in this gritty optimization situation in the first place.
That being said, I enjoyed the article and learned something so maybe I'm the target audience and not them.
> Don't use unique_together, use UniqueConstraint instead
> Always explicitly set db_index and add a comment
> Always check the SQL generated by migrations before applying them
> Provide reverse migration operations whenever possible
> Use concurrent index operations in busy systems
> Indexes on foreign keys are used indirectly by deletes
> Use partial indexes when possible
> Adjust the order of migration operations to reduce impact on live systems
> Explicitly state tables to lock when using select_for_update
> Use no_key=True when selecting a row for update to allow referencing objects to be created
This seems like you need much more non-essential knowledge than simply knowing SQL. Just not using an ORM bypasses so many footguns!
TBH, looking at the code to do this, it seems simpler to just bypass the ORM and use a thin wrapper to the DB.
Since the language in use here supports reflection, every query can automagically return a proper object with typed fields, at which point you gotta ask yourself "what value am I getting out of the ORM in exchange for all these footguns?"
jihadjihad•6mo ago
This is nice to know if you're using Django, but as important to note is that neither Postgres nor SQLAlchemy / Alembic will do this automatically.