Importer Metrics: Add the total number of projects imported

What does this MR do?

In order to start tracking the self-managed instances, we need to instrument usage pings to collect the total number of projects created and the number of imported projects.

Related to:

• #325900 (closed)
• https://gitlab.com/gitlab-data/analytics/-/issues/8226#note_531137689

Screenshots (strongly suggested)

Query plan

Query:

SELECT COUNT("projects"."id") FROM "projects" WHERE "projects"."created_at" BETWEEN '2021-04-19 11:56:32.457238' AND '2021-05-17 11:56:32.457454' AND "projects"."id" >= 1 AND "projects"."id" < 100001

Plan:

 Aggregate  (cost=19972.44..19972.45 rows=1 width=8) (actual time=4016.838..4016.840 rows=1 loops=1)
   Buffers: shared read=21915
   I/O Timings: read=3918.693 write=0.000
   ->  Index Only Scan using index_projects_on_created_at_and_id on public.projects  (cost=0.56..19968.16 rows=1712 width=4) (actual time=4016.832..4016.833 rows=0 loops=1)
         Index Cond: ((projects.created_at >= '2021-04-19 11:56:32.457238+00'::timestamp with time zone) AND (projects.created_at <= '2021-05-17 11:56:32.457454+00'::timestamp with time zone) AND (projects.id >= 1) AND (projects.id < 100001))
         Heap Fetches: 0
         Buffers: shared read=21915
         I/O Timings: read=3918.693 write=0.000

Recommendations:

❗️ Query processes too much data to return a relatively small number of rows. – Reduce data cardinality as early as possible during the execution, using one or several of the following techniques: new indexes, partitioning, query rewriting, denormalization. See the visualization of the plan to understand which plan nodes are the main bottlenecks. <http://momjian.us/main/writings/pgsql/hw_performance/|Show details>

Statistics:

Time: 4.021 s
  - planning: 3.745 ms
  - execution: 4.017 s
    - I/O read: 3.919 s
    - I/O write: 0.000 ms

Shared buffers:
  - hits: 0 from the buffer pool
  - reads: 21915 (~171.20 MiB) from the OS file cache, including disk I/O
  - dirtied: 0
  - writes: 0

Does this MR meet the acceptance criteria?

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• I have self-reviewed this MR per code review guidelines.
• This MR does not harm performance, or I have asked a reviewer to help assess the performance impact. (Merge request performance guidelines)
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