Utilities to clear recommendations cache

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Current behavior

When Studio queries the Curriculum Automation API for recommendations, it caches the results in a table defined by the model RecommendationsCache. If a channel in the Kolibri Content Library (a public channel) changes and is republished, new recommendations could be applicable and old recommendations could be invalid.

Desired behavior

• A Django management should be created that:
  • should delete all data from the RecommendationsCache
• A utility function should be created that:
  • should accept a channel_id as an argument
  • should find all request_hash that have records with a matching channel_id
  • should delete all records with those request_hash
  • should be called during channel publishing, for that channel, when delete_public_channel_cache_keys() is called

Value add

• Allows us to do targeted cache clearing for prior recommendation requests that had recommendations from recently updated and published channels
• Allows us to do full cache clearing on a schedule, which will allow matching new recommendations for content that wasn't previously recommended

Possible tradeoffs

• Ideally, we release performance improvement prior to doing more aggressive cache clearing
• Targeted cache clearing doesn't cover all situations and may not be worthwhile long-term, but probably worthwhile until we better understand our performance limitations