* Reset p bottom margin for group lists to fix vertical alignment
* Remove double border for group lists to be consistent with project
lists
Signed-off-by: NDmitriy Zaporozhets <dmitriy.zaporozhets@gmail.com>

When displaying a project's pipelines
(Projects::PipelinesController#index) we now exclude the coverage data.
This data was not used by the frontend, yet getting it would require one
SQL query per pipeline. These queries in turn could be quite expensive
on GitLab.com.

When displaying the pipelines of a project we now preload the following
data:

1. Authors of the commits that belong to these pipelines
2. The number of warnings per pipeline, which is used by
   Ci::Pipeline#has_warnings?

== Commit Authors

Previously this data was queried for every Commit separately, leading to
20 SQL queries being executed in the worst case. With an average of 3 to
5 milliseconds per SQL query this could result in 100 milliseconds being
spent in _just_ getting Commit authors.

To preload this data Commit#author now uses BatchLoader (through
Commit#lazy_author), and a separate module
Gitlab::Ci::Pipeline::Preloader is used to ensure all authors are loaded
before they are used.

== Number of warnings

This changes Ci::Pipeline#has_warnings? so it supports preloading of the
number of warnings per pipeline. This removes the need for executing a
COUNT(*) query for every pipeline just to see if it has any warnings or
not.

When displaying the project pipelines dashboard we display a few tabs
for different pipeline states. For every such tab we count the number of
pipelines that belong to it. For large projects such as GitLab CE this
means having to count over 80 000 rows, which can easily take between 70
and 100 milliseconds per query.

To improve this we apply a technique we already use for search results:
we limit the number of rows to count. The current limit is 1000, which
means that if more than 1000 rows are present for a state we will show
"1000+" instead of the exact number. The SQL queries used for this
perform much better than a regular COUNT, even when a project has a lot
of pipelines.

Prior to these changes we would end up running a query like this:

    SELECT COUNT(*)
    FROM ci_pipelines
    WHERE project_id = 13083
    AND status IN ('success', 'failed', 'canceled')

This would produce a plan along the lines of the following:

    Aggregate  (cost=3147.55..3147.56 rows=1 width=8) (actual time=501.413..501.413 rows=1 loops=1)
      Buffers: shared hit=17116 read=861 dirtied=2
      ->  Index Only Scan using index_ci_pipelines_on_project_id_and_ref_and_status_and_id on ci_pipelines  (cost=0.56..2984.14 rows=65364 width=0) (actual time=0.095..490.263 rows=80388 loops=1)
            Index Cond: (project_id = 13083)
            Filter: ((status)::text = ANY ('{success,failed,canceled}'::text[]))
            Rows Removed by Filter: 2894
            Heap Fetches: 353
            Buffers: shared hit=17116 read=861 dirtied=2
    Planning time: 1.409 ms
    Execution time: 501.519 ms

Using the LIMIT count technique we instead run the following query:

    SELECT COUNT(*)
    FROM (
        SELECT 1
        FROM ci_pipelines
        WHERE project_id = 13083
        AND status IN ('success', 'failed', 'canceled')
        LIMIT 1001
    ) for_count

This query produces the following plan:

    Aggregate  (cost=58.77..58.78 rows=1 width=8) (actual time=1.726..1.727 rows=1 loops=1)
      Buffers: shared hit=169 read=15
      ->  Limit  (cost=0.56..46.25 rows=1001 width=4) (actual time=0.164..1.570 rows=1001 loops=1)
            Buffers: shared hit=169 read=15
            ->  Index Only Scan using index_ci_pipelines_on_project_id_and_ref_and_status_and_id on ci_pipelines  (cost=0.56..2984.14 rows=65364 width=4) (actual time=0.162..1.426 rows=1001 loops=1)
                  Index Cond: (project_id = 13083)
                  Filter: ((status)::text = ANY ('{success,failed,canceled}'::text[]))
                  Rows Removed by Filter: 9
                  Heap Fetches: 10
                  Buffers: shared hit=169 read=15
    Planning time: 1.832 ms
    Execution time: 1.821 ms

While this query still uses a Filter for the "status" field the number
of rows that it may end up filtering (at most 1001) is small enough that
an additional index does not appear to be necessary at this time.

See https://gitlab.com/gitlab-org/gitlab-ce/issues/43132#note_68659234
for more information.

Also moves the assertions were they belong

Signed-off-by: NRémy Coutable <remy@rymai.me>

Signed-off-by: NRémy Coutable <remy@rymai.me>

Signed-off-by: NRémy Coutable <remy@rymai.me>

Uses PostgreSQL tuple estimates to provide a much faster yet approximate
count. See https://wiki.postgresql.org/wiki/Slow_Counting for more details.
We only use this fast method if the table has been analyzed or vacuumed
within the last hour.

Closes #46255

Prior to this change, this was done through unicorn. In theory this
could time out. Workhorse has been sending these raw patches and diffs
for a long time and is stable in doing so.

Added bonus is the fact that `Commit#to_patch` can be removed.

`Commit#to_diff` too, which closes
https://gitlab.com/gitlab-org/gitaly/issues/324

Closes https://gitlab.com/gitlab-org/gitaly/issues/1196

destroy_all loads all records at once

ObjectStore uploader requires presence of associated `uploads` record
when deleting the upload file (through the carrierwave's after_commit
hook) because we keep info whether file is LOCAL or REMOTE in `upload`
object.

For this reason we can not destroy uploads as "dependent: :destroy" hook
because these would be deleted too soon. Instead we rely on
carrierwave's hook to destroy `uploads` in after_commit hook.

But in before_destroy hook we still have to delete not-mounted uploads
(which don't use carrierwave's destroy hook). This has to be done in
before_Destroy instead of after_commit because `FileUpload` requires
existence of model's object on destroy action.

This is not ideal state of things, in a next step we should investigate
how to unify model dependencies so we can use same workflow for all
uploads.

Related to #45425