| Commit message (Collapse) | Author | Age | Files | Lines |
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to reduce allocation of same object
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We can skip the allocation of a full `AttributeSet` by changing the
semantics of how we structure things. Instead of comparing two separate
`AttributeSet` objects, and `Attribute` is now a singly linked list of
every change that has happened to it. Since the attribute objects are
immutable, to apply the changes we simply need to copy the head of the
list.
It's worth noting that this causes one subtle change in the behavior of
AR. When a record is saved successfully, the `before_type_cast` version
of everything will be what was sent to the database. I honestly think
these semantics make more sense, as we could have just as easily had the
DB do `RETURNING *` and updated the record with those if we had things
like timestamps implemented at the DB layer.
This brings our performance closer to 4.2, but we're still not quite
there.
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The biggest source of the performance regression in these methods
occurred because dirty tracking required eagerly materializing and type
casting the assigned values. In the previous commits, I've changed dirty
tracking to perform the comparisons lazily. However, all of this is moot
when calling `save`, since `changes_applied` will be called, which just
ends up eagerly materializing everything, anyway. With the new mutation
tracker, it's easy to just compare the previous two hashes in the same
lazy fashion.
We will not have aliasing issues with this setup, which is proven by the
fact that we're able to detect nested mutation.
Before:
User.create! 2.007k (± 7.1%) i/s - 10.098k
After:
User.create! 2.557k (± 3.5%) i/s - 12.789k
Fixes #19859
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In order to improve the performance of dirty checking, we're going to
need to duplicate all of the `previous_` methods in Active Model.
However, these methods are basically the same as their non-previous
counterparts, but comparing `@original_attributes` to
`@previous_original_attributes` instead of `@attributes` and
`@original_attributes`. This will help reduce that duplication.
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