Here is my scenario:
- I have a large read-only set of data and a very small mutable set of data.
- The read-only set of data can be pre-populated into a TDB2 while the mutable 
set of data will start out empty but will, obviously have data injected 
overtime during runtime.
- I want one Fuseki service which combines both of these sets of data into a 
single dataset so that inference can be performed for the mutable data 
dependent upon the read-only data. (I.E. union them as named graphs into a 
single dataset).
- I know that I can accomplish the union of the two sets of data as separate 
named graphs in the final dataset, but I also need full text search on both the 
read-only and the mutable portions of the final dataset.

How do I accomplish the need for indexing both read-only and mutable data that 
get combined into a single dataset? Do I create two indexes? Am I able to share 
indexes? I know that I could create an initial index from the read-only data 
which could then be updated when changes are made to the mutable data. However, 
once the read-only data needs updates (which it will from time to time), I need 
to regenerate the entire index in order to get any changes that weren’t added 
via an update through Fuseki (which is how the read-only data would be updated, 
likely a new tdb2 would be generated).

Thanks for the help!
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