I added delete_when_reminder_sent to ignored_columns because it no longer exists and added a shortcut method delete_when_reminder_sent? to the Bookmark model. However I have been seeing some weird errors like:
> Job exception: unknown attribute 'delete_when_reminder_sent' for Bookmark.
So I am very suspicious. I am just renaming the method to auto_delete_when_reminder_sent? to avoid any potential conflicts.
Also found include_bookmark_delete_on_owner_reply? in PostSerializer which is used for nothing; I must have forgotten to delete it before.
For the following conditions, the TopicUser.bookmarked column was not updated correctly:
* When a bookmark was auto-deleted because the reminder was sent
* When a bookmark was auto-deleted because the owner of the bookmark replied to the topic
This adds another migration to fix the out-of-sync column and also some refactors to BookmarkManager to allow for more of these delete cases. BookmarkManager is used instead of directly destroying the bookmark in PostCreator and BookmarkReminderNotificationHandler.
This changes PG text search to only match the given title against
lexemes that are formed from the title. Likewise, the given raw will
only be matched against lexemes that are formed from the post's raw.
If a user posted a topic and Akismet decided it was spam, the topic gets deleted and put into the review queue. If a category moderator for that category marked the post/topic as "Not Spam" the topic did not get recovered correctly because Guardian.new(@user).can_review_topic?(@post.topic) returned false incorrectly because the topic was deleted.
This adds a special filter to topic lists that will filter to tracked and
watched categories.
To use it you can visit:
`https://sitename/?filter=tracked`
`https://sitename/unread?filter=tracked`
and so on
Note, we do not include explicitly tracked and watched topics **outside** of
the tracked categories and tags.
We can consider a `filter=all_tracked` to cover this edge case.
To reproduce the initial issue here:
1. A user makes a post, which discourse-akismet marks as spam (I cheated and called `DiscourseAkismet::PostsBouncer.new.send(:mark_as_spam, post)` for this)
2. The post lands in the review queue
3. The category the topic is in has a `reviewable_by_group_id`
4. A user in that group goes and looks at the Review queue, decides the post is not spam, and clicks Not Spam
5. Weird stuff happens because the `PostDestroyer#recover` method didn't handle this (the user who clicked Not Spam was not the owner of the post and was not a staff member, so the post didn't get un-destroyed and post counts didn't get updated)
Now users who belong to a group who can review a category now have the ability to recover/delete posts fully.
Previously we considered 'upload rows without etags' to be exempt from the check. This is bad, because older/migrated sites might not have etags on all their uploads. We should consider rows without etags to be broken, since we can't check them against the inventory.
This also removes the `by_users` scope. We need all uploads to be working, even ones created by the system user.
This adds an option to "delete on owner reply" to bookmarks. If you select this option in the modal, then reply to the topic the bookmark is in, the bookmark will be deleted on reply.
This PR also changes the checkboxes for these additional bookmark options to an Integer column in the DB with a combobox to select the option you want.
The use cases are:
* Sometimes I will bookmark the topics to read it later. In this case we definitely don’t need to keep the bookmark after I replied to it.
* Sometimes I will read the topic in mobile and I will prefer to reply in PC later. Or I may have to do some research before reply. So I will bookmark it for reply later.
* FEATURE: Allow List for PMs
This feature adds a new user setting that is disabled by default that
allows them to specify a list of users that are allowed to send them
private messages. This way they don't have to maintain a large list of
users they don't want to here from and instead just list the people they
know they do want. Staff will still always be able to send messages to
the user.
* Update PR based on feedback
Some definitions rely on others, in particular the c/cpp/c-like ones,
and we were appending the bundle of all files in the folder.
Instead for testing I've limited us to just three definitions. This has
the benefit of being a lot smaller to download/parse in test mode too.
It seems there was a discrepancy in that background images were attached
to the full slug category class: `category-:slug-:id` and our body class
only had `category-:slug`.
This fix adds support for both formats.
* Remove unneeded bookmark name index.
* Change bookmark search query to use post_search_data. This allows searching on topic title and post content
* Tweak the style/layout of the bookmark list so the search looks better and the whole page fits better on mobile.
* Added scopes UI
* Create scopes when creating a new API key
* Show scopes on the API key show route
* Apply scopes on API requests
* Extend scopes from plugins
* Add missing scopes. A mapping can be associated with multiple controller actions
* Only send scopes if the use global key option is disabled. Use the discourse plugin registry to add new scopes
* Add not null validations and index for api_key_id
* Annotate model
* DEV: Move default mappings to ApiKeyScope
* Remove unused attribute and improve UI for existing keys
* Support multiple parameters separated by a comma
Follow up to d8c796bc4.
Note that his change increases query time by around 40% in the following
benchmark against `dev.discourse.org` but this is a tradeoff that has to be taken so that relevance
search is accurate.
```
require 'benchmark/ips'
Benchmark.ips do |x|
x.config(time: 10, warmup: 2)
x.report("current aggregate search query") do
DB.exec <<~SQL
SELECT "posts"."id", "posts"."user_id", "posts"."topic_id", "posts"."post_number", "posts"."raw", "posts"."cooked", "posts"."created_at", "posts"."updated_at", "posts"."reply_to_post_number", "posts"."reply_count", "posts"."quote_count", "posts"."deleted_at", "posts"."off_topic_count", "posts"."like_count", "posts"."incoming_link_count", "posts"."bookmark_count", "posts"."score", "posts"."reads", "posts"."post_type", "posts"."sort_order", "posts"."last_editor_id", "posts"."hidden", "posts"."hidden_reason_id", "posts"."notify_moderators_count", "posts"."spam_count", "posts"."illegal_count", "posts"."inappropriate_count", "posts"."last_version_at", "posts"."user_deleted", "posts"."reply_to_user_id", "posts"."percent_rank", "posts"."notify_user_count", "posts"."like_score", "posts"."deleted_by_id", "posts"."edit_reason", "posts"."word_count", "posts"."version", "posts"."cook_method", "posts"."wiki", "posts"."baked_at", "posts"."baked_version", "posts"."hidden_at", "posts"."self_edits", "posts"."reply_quoted", "posts"."via_email", "posts"."raw_email", "posts"."public_version", "posts"."action_code", "posts"."locked_by_id", "posts"."image_upload_id" FROM "posts" JOIN (SELECT *, row_number() over() row_number FROM (SELECT topics.id, min(posts.post_number) post_number FROM "posts" INNER JOIN "post_search_data" ON "post_search_data"."post_id" = "posts"."id" INNER JOIN "topics" ON "topics"."id" = "posts"."topic_id" AND ("topics"."deleted_at" IS NULL) LEFT JOIN categories ON categories.id = topics.category_id WHERE ("posts"."deleted_at" IS NULL) AND "posts"."post_type" IN (1, 2, 3, 4) AND (topics.visible) AND (topics.archetype <> 'private_message') AND (post_search_data.search_data @@ TO_TSQUERY('english', '''postgres'':*ABCD')) AND (categories.id NOT IN (
SELECT categories.id WHERE categories.search_priority = 1
)
) AND ((categories.id IS NULL) OR (NOT categories.read_restricted)) GROUP BY topics.id ORDER BY MAX((
TS_RANK_CD(
post_search_data.search_data,
TO_TSQUERY('english', '''postgres'':*ABCD'),
1|32
) *
(
CASE categories.search_priority
WHEN 2
THEN 0.6
WHEN 3
THEN 0.8
WHEN 4
THEN 1.2
WHEN 5
THEN 1.4
ELSE
CASE WHEN topics.closed
THEN 0.9
ELSE 1
END
END
)
)
) DESC, topics.bumped_at DESC LIMIT 51 OFFSET 0) xxx) x ON x.id = posts.topic_id AND x.post_number = posts.post_number WHERE ("posts"."deleted_at" IS NULL) ORDER BY row_number;
SQL
end
x.report("current aggregate search query with proper ranking") do
DB.exec <<~SQL
SELECT "posts"."id", "posts"."user_id", "posts"."topic_id", "posts"."post_number", "posts"."raw", "posts"."cooked", "posts"."created_at", "posts"."updated_at", "posts"."reply_to_post_number", "posts"."reply_count", "posts"."quote_count", "posts"."deleted_at", "posts"."off_topic_count", "posts"."like_count", "posts"."incoming_link_count", "posts"."bookmark_count", "posts"."score", "posts"."reads", "posts"."post_type", "posts"."sort_order", "posts"."last_editor_id", "posts"."hidden", "posts"."hidden_reason_id", "posts"."notify_moderators_count", "posts"."spam_count", "posts"."illegal_count", "posts"."inappropriate_count", "posts"."last_version_at", "posts"."user_deleted", "posts"."reply_to_user_id", "posts"."percent_rank", "posts"."notify_user_count", "posts"."like_score", "posts"."deleted_by_id", "posts"."edit_reason", "posts"."word_count", "posts"."version", "posts"."cook_method", "posts"."wiki", "posts"."baked_at", "posts"."baked_version", "posts"."hidden_at", "posts"."self_edits", "posts"."reply_quoted", "posts"."via_email", "posts"."raw_email", "posts"."public_version", "posts"."action_code", "posts"."locked_by_id", "posts"."image_upload_id" FROM "posts" JOIN (SELECT *, row_number() over() row_number FROM (SELECT subquery.topic_id id, (ARRAY_AGG(subquery.post_number ORDER BY rank DESC, bumped_at DESC))[1] post_number, MAX(subquery.rank) rank, MAX(subquery.bumped_at) bumped_at FROM (SELECT "posts"."id", "posts"."user_id", "posts"."topic_id", "posts"."post_number", "posts"."raw", "posts"."cooked", "posts"."created_at", "posts"."updated_at", "posts"."reply_to_post_number", "posts"."reply_count", "posts"."quote_count", "posts"."deleted_at", "posts"."off_topic_count", "posts"."like_count", "posts"."incoming_link_count", "posts"."bookmark_count", "posts"."score", "posts"."reads", "posts"."post_type", "posts"."sort_order", "posts"."last_editor_id", "posts"."hidden", "posts"."hidden_reason_id", "posts"."notify_moderators_count", "posts"."spam_count", "posts"."illegal_count", "posts"."inappropriate_count", "posts"."last_version_at", "posts"."user_deleted", "posts"."reply_to_user_id", "posts"."percent_rank", "posts"."notify_user_count", "posts"."like_score", "posts"."deleted_by_id", "posts"."edit_reason", "posts"."word_count", "posts"."version", "posts"."cook_method", "posts"."wiki", "posts"."baked_at", "posts"."baked_version", "posts"."hidden_at", "posts"."self_edits", "posts"."reply_quoted", "posts"."via_email", "posts"."raw_email", "posts"."public_version", "posts"."action_code", "posts"."locked_by_id", "posts"."image_upload_id", (
TS_RANK_CD(
post_search_data.search_data,
TO_TSQUERY('english', '''postgres'':*ABCD'),
1|32
) *
(
CASE categories.search_priority
WHEN 2
THEN 0.6
WHEN 3
THEN 0.8
WHEN 4
THEN 1.2
WHEN 5
THEN 1.4
ELSE
CASE WHEN topics.closed
THEN 0.9
ELSE 1
END
END
)
)
rank, topics.bumped_at bumped_at FROM "posts" INNER JOIN "post_search_data" ON "post_search_data"."post_id" = "posts"."id" INNER JOIN "topics" ON "topics"."id" = "posts"."topic_id" AND ("topics"."deleted_at" IS NULL) LEFT JOIN categories ON categories.id = topics.category_id WHERE ("posts"."deleted_at" IS NULL) AND "posts"."post_type" IN (1, 2, 3, 4) AND (topics.visible) AND (topics.archetype <> 'private_message') AND (post_search_data.search_data @@ TO_TSQUERY('english', '''postgres'':*ABCD')) AND (categories.id NOT IN (
SELECT categories.id WHERE categories.search_priority = 1
)
) AND ((categories.id IS NULL) OR (NOT categories.read_restricted))) subquery GROUP BY subquery.topic_id ORDER BY rank DESC, bumped_at DESC LIMIT 51 OFFSET 0) xxx) x ON x.id = posts.topic_id AND x.post_number = posts.post_number WHERE ("posts"."deleted_at" IS NULL) ORDER BY row_number;
SQL
end
x.compare!
end
```
```
Warming up --------------------------------------
current aggregate search query
1.000 i/100ms
current aggregate search query with proper ranking
1.000 i/100ms
Calculating -------------------------------------
current aggregate search query
18.040 (± 0.0%) i/s - 181.000 in 10.035241s
current aggregate search query with proper ranking
12.992 (± 0.0%) i/s - 130.000 in 10.007214s
Comparison:
current aggregate search query: 18.0 i/s
current aggregate search query with proper ranking: 13.0 i/s - 1.39x (± 0.00) slower
```
