Bring in stream metadata from static CSVs

[jeremyestein]

Addresses #45

Copy CSV metadata tables from Elise's repo and use this to fill in some gaps in the HL7 data we encounter (eg. sampling rate).

A further PR will perform validation that sampling rate is what we expect it to be. The gap checking algorithm in collation is already poised to do this, although it won't be able to do very much about it apart from report an error that we can investigate.

Also adding more threads to try and make it go faster. And hold locks for shorter periods during collation.

[github-actions]

PR checklist

Default guide for a PR (if multiple PRs for the work, only keep one version of it and link to it on the other PRs)

• From the UCLH data science desktop, a validation run has been set off
• load times
  in UCL teams has been populated with the run information
• During the run, glowroot has been checked for any queries which are taking a substantial proportion of the
  total processing time. This can be useful to identify indexes that are required.
• After the run, look for any unexpected errors in the etl_per_message_logging table, the error_search.sql file
  on the shared drive can be used for this \\sharefs6\UCLH6\EMAP\Shared\EmapSqlScripts\devops\error_search.sql.
  Create an issue if you find an unexpected exception and is not related to the changes you've made, otherwise
  fix them!
• After the run, populate the end time in
  load times
• Let Aasiyah know about the completed validation and give her information on the changes and where to start
  with the validation
• Check validation report and give any feedback to Aasiyah if there are any changes needed on her side,
  iterate on getting the validation to match at least 99% (validation and emap code).