On 01/10/2021 17:09, Brandon Sara wrote:
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).
A text index is "per dataset".
A stack like:
* text dataset
* general dataset
Setup models as needed
* storage
Rebuild the Lucence text index (this can be done offline outside Fuseki)
when the read-only data changes then index the mutable data.
Andy
Thanks for the help!
