In c6ceda8c, a bug was introduced where an admin searching for his own
private messages will actually end up searching through all private
messages on the site.
Follow-up to c6ceda8c4e
With the addition of `PostSearchData#private_message`, a partial
index consisting of only search data from regular posts can be created.
The partial index helps to speed up searches on large sites since PG
will not have to do an index scan on the entire search data index which
has shown to be a bottle neck.
The filter noops if an incorrect username is passed. This filter is not
exposed as part of the UI but is only used when an admin transitions
from a search within a user's personal messages to the full page search.
Follow-up to 4b30799054.
Renamed from `private_messages` to `personal_messages` without
deprecation because the `private_messages` advanced search filter never
worked in the first place when it was implemented.
Similar to `advanced_filter` I introduced `advanced_order`.
I needed a new option because default orders are evaluated after advanced_filter so I couldn't use it.
Also, that part is a little bit more generic
```
elsif word =~ /order:\w+/
@order = word.gsub('order:', '').to_sym
nil
```
After those changes, I can use them in plugins in this way:
```
Search.advanced_order(:votes) do |posts|
posts.reorder("COALESCE((SELECT dvvc.counter FROM discourse_voting_vote_counters dvvc WHERE dvvc.topic_id = subquery.topic_id), 0) DESC")
end
```
Considering document length in search introduced too much variance in
our search results such that it makes certain searches better but at the
same time made certain searches worst. Instead, we want to have a more
determistic way of ranking search so that it is easier to reason about
why a post is rank higher in search than another.
The long term plan to tackle repeated terms is to restrict the number of
positions for a given lexeme in our search index.
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
```
```
discourse_development=# SELECT alias, lexemes FROM TS_DEBUG('www.discourse.org');
alias | lexemes
-------+---------------------
host | {www.discourse.org}
discourse_development=# SELECT TO_TSVECTOR('www.discourse.org');
to_tsvector
-----------------------
'www.discourse.org':1
```
Given the above lexeme, we will inject additional lexeme by splitting
the host on `.`. The actual tsvector stored will look something like
```
tsvector
---------------------------------------
'discourse':1 'discourse.org':1 'org':1 'www':1 'www.discourse.org':1
```
Previously, we would only take either the `MIN` or `MAX` for
`post_number` during aggregation meaning that the ranking is not
considered.
```
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))[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
17.726 (± 0.0%) i/s - 178.000 in 10.045107s
current aggregate search query with proper ranking
17.802 (± 0.0%) i/s - 178.000 in 10.002230s
Comparison:
current aggregate search query with proper ranking: 17.8 i/s
current aggregate search query: 17.7 i/s - 1.00x (± 0.00) slower
```
This reverts commit 20780a1eee.
* SECURITY: re-adds accidentally reverted commit:
03d26cd6: ensure embed_url contains valid http(s) uri
* when the merge commit e62a85cf was reverted, git chose the 2660c2e2 parent to land on
instead of the 03d26cd6 parent (which contains security fixes)
Adds a new topic_excerpt_maxlength site setting.
* When topic excerpt is requested for a post, use the new topic_excerpt_maxlength site setting to limit the size of the excerpt
* Remove code for getting/setting Post.excerpt_size as it is not used anywhere
This introduces new APIs for obtaining optimized thumbnails for topics. There are a few building blocks required for this:
- Introduces new `image_upload_id` columns on the `posts` and `topics` table. This replaces the old `image_url` column, which means that thumbnails are now restricted to uploads. Hotlinked thumbnails are no longer possible. In normal use (with pull_hotlinked_images enabled), this has no noticeable impact
- A migration attempts to match existing urls to upload records. If a match cannot be found then the posts will be queued for rebake
- Optimized thumbnails are generated during post_process_cooked. If thumbnails are missing when serializing a topic list, then a sidekiq job is queued
- Topic lists and topics now include a `thumbnails` key, which includes all the available images:
```
"thumbnails": [
{
"max_width": null,
"max_height": null,
"url": "//example.com/original-image.png",
"width": 1380,
"height": 1840
},
{
"max_width": 1024,
"max_height": 1024,
"url": "//example.com/optimized-image.png",
"width": 768,
"height": 1024
}
]
```
- Themes can request additional thumbnail sizes by using a modifier in their `about.json` file:
```
"modifiers": {
"topic_thumbnail_sizes": [
[200, 200],
[800, 800]
],
...
```
Remember that these are generated asynchronously, so your theme should include logic to fallback to other available thumbnails if your requested size has not yet been generated
- Two new raw plugin outlets are introduced, to improve the customisability of the topic list. `topic-list-before-columns` and `topic-list-before-link`
Previous to this change slugs for leaves in 3 level nestings would not work
Our UX picks only the last two levels
This also makes the results consistent for slugs as it enforces order.
The new search modifier `in:all` can be used to include both public and personal messages in the same search.
Co-authored-by: adam j hartz <hz@mit.edu>
This feature adds the ability to define synonyms for tags, and the ability to merge one tag into another while keeping it as a synonym. For example, tags named "js" and "java-script" can be synonyms of "javascript". When searching and creating topics using synonyms, they will be mapped to the base tag.
Along with this change is a new UI found on each tag's page (for example, `/tags/javascript`) where more information about the tag can be shown. It will list the synonyms, which categories it's restricted to (if any), and which tag groups it belongs to (if tag group names are public on the `/tags` page by enabling the "tags listed by group" setting). Staff users will be able to manage tags in this UI, merge tags, and add/remove synonyms.
* When viewing a tag, the search widget will now show a checkbox to scope the search by tag, which will limit search results to that tag on desktop and mobile
Zeitwerk simplifies working with dependencies in dev and makes it easier reloading class chains.
We no longer need to use Rails "require_dependency" anywhere and instead can just use standard
Ruby patterns to require files.
This is a far reaching change and we expect some followups here.
* FEATURE: Add search operator to see all direct messages from a user
* Only show message if related messages >= 5
* Make "all messages" the hyperlink
* Review
The behaviour of #TERM in search has been amended
1. We try category or subcategory slugs
2. We try tags
3. We try tag-groups
The term `hello #my-group` will search for all posts tagged with any of
the tags in the tag group `My Group`
Future work may be introducing a slug cache here or caching it in the table
but the assumption is that the number of tag groups will not be huge
Arpit Jalan
Bianca Nenciu
Guo Xiang Tan
siriwatknp
Krzysztof Kotlarek
Vinoth Kannan
Michael Brown
Jeff Atwood
Martin Brennan
David Taylor
Sam Saffron
Jarek Radosz
adam j hartz
Mark VanLandingham
Neil Lalonde
Martin Brennan
Daniel Waterworth
Osama Sayegh
Josh Moore
Penar Musaraj