... | ... | @@ -5,4 +5,39 @@ Koha holds item and circulation data, including statistics, RDF holds metadata o |
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It also simplify the inspection and maintenance of the index: queries on MySQL are easier to master than inspecting ES, and changing ES schema will require a local reindex, without having to re-read the data from koha/rdf.
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It also improve debugging of issues, by checking the DB it’s easier to debug when an item is missing or not. And when/where the data was wrongly transmitted. |
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It also improve debugging of issues, by checking the DB it’s easier to debug when an item is missing or not. And when/where the data was wrongly transmitted.
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## DB
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# documents
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| column | type | comments / examples |
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|---|---|---|
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| id | varchar PK | "pub:1a2b3c4d", "place:oslo", "person:p123" |
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| source | varchar PK | "catalog", "cms", ... |
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| update_at | datetime ||
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| metadata | json | {"title":"Abcd","pubYear":"1987"} |
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| pop_data | structured | [{n:10,d:1},{n:100,d:10},...] |
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| pop_data_stored | double | popularity stored on ES |
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| reindex_at | datetime | IDX : When and if the document need to be reindexed |
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# links
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The DB is responsible to mirror linking inside the search container, in order to bleed scoring and popularity from linked works
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This might be solved in RDF though
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| column | type | comments / examples |
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| from_node | varchar FK | Foreign key items.id |
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| to_node | varchar | might be missing in items (still to be obtained) |
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| type | varchar | "author", "work", "place", "genre", "translator"... |
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| weight | double | Default 1.0 |
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# stats
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| column | type | comments / examples |
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|---|---|---|
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| id | varchar FK | foreign key items.id, e.g.: "recordId:12345” |
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| source | varchar PK | e.g.: "koha" |
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| popularity | structured | e.g.: items_count + loans_count*5 | |