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: ProgramsKESExampleAcademic.schema
00:00:00 Input Data: ProgramsKESExampleAcademic.data
00:00:00 Output Index: ProgramsKESExampleAcademic.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..................Content has been hidden....................
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