perf(sql): use org and course_key filters to use primary key indexes

[Ian2012]

Description

Based on a performance check, we found that using the course_key filter instead of course_name better uses ClickHouse primary key indexes, reducing the number of rows processed and improving memory usage and execution time. This PR updates most of the datasets to make use of the primary key indexes.

It also deletes unused .sql template files.

Benchmarks

Numbers speak for themselves.

Before:

1. learner-groups - Problem Attempts
Superset time: 3.416288 (s).
Query duration: 1.818 (s).
Result rows: 160
Memory Usage (MB): 212.7149143218994
Row count (superset) 160
Filters: [{'column': 'emission_time'}, {'column': 'course_name'}, {'column': 'org'}]
SQL:

6. learner-groups - Subsection Summary
Superset time: 1.602989 (s).
Query duration: 0.845 (s).
Result rows: 30
Memory Usage (MB): 351.30071449279785
Row count (superset) 30
Filters: [{'column': 'visited_on'}, {'column': 'course_name'}, {'column': 'org'}]
SQL:

After:

13. learner-groups - Problem Attempts
Superset time: 1.983724 (s).
Query duration: 0.31 (s).
Result rows: 160
Memory Usage (MB): 166.58758544921875
Row count (superset) 160
Filters: [{'column': 'emission_time'}, {'column': 'course_name'}, {'column': 'org'}]
SQL:

16. course-dashboard - Subsection Summary
Superset time: 0.742814 (s).
Query duration: 0.247 (s).
Result rows: 30
Memory Usage (MB): 113.08792209625244
Row count (superset) 30
Filters: [{'column': 'visited_on'}, {'column': 'course_name'}, {'column': 'org'}]
SQL:

before.txt
after.txt

[openedx-webhooks]

Thanks for the pull request, @Ian2012!

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