With the attribute schema and data file in place, we can build the compressed binary index. This will hold all our data objects.
Using our example files, we can build the index by running the following command:
kes.exe build_index Academic.schema Academic.data Academic.index
A successful execution should produce the Academic.index
file, which we will use when we are hosting the service.
When running the command, the application will continuously output the status, which can look like the following:
00:00:00 Input Schema: \Programs\KES\Example\Academic.schema 00:00:00 Input Data: \Programs\KES\Example\Academic.data 00:00:00 Output Index: \Programs\KES\Example\Academic.index 00:00:00 Loading synonym file: Keyword.syn 00:00:00 Loaded 3700 synonyms (9.4 ms) 00:00:00 Pass 1 started 00:00:00 Total number of entities: 1000 00:00:00 Sorting entities 00:00:00 Pass 1 finished (14.5 ms) 00:00:00 Pass 2 started 00:00:00 Pass 2 finished (13.3 ms) 00:00:00 Processed attribute Title (20.0 ms) 00:00:00 Processed attribute Year (0.3 ms) 00:00:00 Processed attribute Author.Id (0.5 ms) 00:00:00 Processed attribute Author.Name (10.7 ms) 00:00:00 Processed attribute Author.Affiliation (2.3 ms) 00:00:00 Processed attribute Keyword (20.6 ms) 00:00:00 Pass 3 started 00:00:00 Pass 3 finished (15.5 ms, 73 page faults) 00:00:00 Post-processing started 00:00:00 Optimized attribute Title (0.1 ms) 00:00:00 Optimized attribute Year (0.0 ms) 00:00:00 Optimized attribute Author.Id (0.0 ms) 00:00:00 Optimized attribute Author.Name (0.5 ms) 00:00:00 Optimized attribute Author.Affiliation (0.2 ms) 00:00:00 Optimized attribute Keyword (0.6 ms) 00:00:00 Global optimization 00:00:00 Post-processing finished (17.2 ms) 00:00:00 Finalizing index 00:00:00 Total time: 157.6 ms 00:00:00 Peak memory usage: 23 MB (commit) + 0 MB (data file) = 23 MB