Returning a boolean value from a constraint-level access control
function does nothing. For example:
```ts
{
label: 'Noone',
value: 'noone',
access: () => false,
},
```
This is because we were only handling query objects, disregarding any
boolean values. The fix is to check if the query is a boolean, and if
so, format a query object to return.
This adds support for running multiple job queue tasks in parallel
within the same workflow while preventing conflicts. Previously, this
would have caused the following issues:
- Job log entries get lost - the final job log is incomplete, despite
all tasks having been executed
- Write conflicts in postgres, leading to unique constraint violation
errors
The solution involves handling job log data updates in a way that avoids
overwriting, and ensuring the final update reflects the latest job log
data. Each job log entry now initializes its own ID, so a given job log
entry’s ID remains the same across multiple, parallel task executions.
## Postgres
In Postgres, we need to enable transactions for the
`payload.db.updateJobs` operation; otherwise, two tasks updating the
same job in parallel can conflict. This happens because Postgres handles
array rows by deleting them all, then re-inserting (rather than
upserting). The rows are stored in a separate table, and the following
scenario can occur:
Op 1: deletes all job log rows
Op 2: deletes all job log rows
Op 1: inserts 200 job log rows
Op 2: insert the same 200 job log rows again => `error: “duplicate key
value violates unique constraint "payload_jobs_log_pkey”`
Because transactions were not used, the rows inserted by Op 1
immediately became visible to Op 2, causing the conflict. Enabling
transactions fixes this. In theory, it can still happen if Op 1 commits
before Op 2 starts inserting (due to the read committed isolation
level), but it should occur far less frequently.
Alongside this change, we should consider inserting the rows using an
upsert (update on conflict), which will get rid of this error
completely. That way, if the insertion of Op 1 is visible to Op 2, Op 2
will simply overwrite it, rather than erroring. Individual job entries
are immutable and job entries cannot be deleted, thus this shouldn't
corrupt any data.
## Mongo
In Mongo, the issue is addressed by ensuring that log row deletions
caused due to different log states in concurrent operations are not
merged back to the client job log, and by making sure the final update
includes all job logs.
There is no duplicate key error in Mongo because the array log resides
in the same document and duplicates are simply upserted. We cannot use
transactions in Mongo, as it appears to lock the document in a way that
prevents reliable parallel updates, leading to:
`MongoServerError: WriteConflict error: this operation conflicted with
another operation. Please retry your operation or multi-document
transaction`
When selecting query presets from the list drawer, all query presets are
available for selection, even if unrelated to the underlying collection.
When selecting one of these presets, the list view will crash with
client-side exceptions because the columns and filters that are applied
are incompatible.
The fix is to the thread `filterOptions` through the query presets
drawer. This will ensure that only related collections are shown.
Query Presets allow you to save and share filters, columns, and sort
orders for your collections. This is useful for reusing common or
complex filtering patterns and column configurations across your team.
Query Presets are defined on the fly by the users of your app, rather
than being hard coded into the Payload Config.
Here's a screen recording demonstrating the general workflow as it
relates to the list view. Query Presets are not exclusive to the admin
panel, however, as they could be useful in a number of other contexts
and environments.
https://github.com/user-attachments/assets/1fe1155e-ae78-4f59-9138-af352762a1d5
Each Query Preset is saved as a new record in the database under the
`payload-query-presets` collection. This will effectively make them
CRUDable and allows for an endless number of preset configurations. As
you make changes to filters, columns, limit, etc. you can choose to save
them as a new record and optionally share them with others.
Normal document-level access control will determine who can read,
update, and delete these records. Payload provides a set of sensible
defaults here, such as "only me", "everyone", and "specific users", but
you can also extend your own set of access rules on top of this, such as
"by role", etc. Access control is customizable at the operation-level,
for example you can set this to "everyone" can read, but "only me" can
update.
To enable the Query Presets within a particular collection, set
`enableQueryPresets` on that collection's config.
Here's an example:
```ts
{
// ...
enableQueryPresets: true
}
```
Once enabled, a new set of controls will appear within the list view of
the admin panel. This is where you can select and manage query presets.
General settings for Query Presets are configured under the root
`queryPresets` property. This is where you can customize the labels,
apply custom access control rules, etc.
Here's an example of how you might augment the access control properties
with your own custom rule to achieve RBAC:
```ts
{
// ...
queryPresets: {
constraints: {
read: [
{
label: 'Specific Roles',
value: 'specificRoles',
fields: [roles],
access: ({ req: { user } }) => ({
'access.update.roles': {
in: [user?.roles],
},
}),
},
],
}
}
}
```
Related: #4193 and #3092
---------
Co-authored-by: Dan Ribbens <dan.ribbens@gmail.com>
