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authorbnewbold <bnewbold@archive.org>2021-11-11 01:12:18 +0000
committerbnewbold <bnewbold@archive.org>2021-11-11 01:12:18 +0000
commit6ad9d24e4d7d901d6fc394e6e91575f6acba7ff4 (patch)
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parent7e3f91f1a49ea85707cae31125021ba761f5373d (diff)
parent6eaf4f57c1f92b6f4f46adc38e5b39fd30b65d81 (diff)
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Merge branch 'bnewbold-import-refactors' into 'master'
import refactors and deprecations Some of these are from old stale branches (the datacite subject metadata patch), but most are from yesterday and today. Sort of a hodge-podge, but the general theme is getting around to deferred cleanups and refactors specific to importer code before making some behavioral changes. The Datacite-specific stuff could use review here. Remove unused/deprecated/dead code: - cdl_dash_dat and wayback_static importers, which were for specific early example entities and have been superseded by other importers - "extid map" sqlite3 feature from several importers, was only used for initial bulk imports (and maybe should not have been used) Refactors: - moved a number of large datastructures out of importer code and into a dedicated static file (`biblio_lookup_tables.py`). Didn't move all, just the ones that were either generic or very large (making it hard to read code) - shuffled around relative imports and some function names ("clean_str" vs. "clean") Some actual behavioral changes: - remove some Datacite-specific license slugs - stop trying to fix double-slashes in DOIs, that was causing more harm than help (some DOIs do actually have double-slashes!) - remove some excess metadata from datacite 'extra' fields
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@@ -52,6 +52,7 @@ Usually tens of minutes on fast production machine.
Usually 24 hours or so on fast production machine.
+ # NOTE: `--extid-map-file` was used during initial import, but is now deprecated
time xzcat /srv/fatcat/datasets/crossref-works.2018-09-05.json.xz | time parallel -j20 --round-robin --pipe ./fatcat_import.py crossref - /srv/fatcat/datasets/ISSN-to-ISSN-L.txt --extid-map-file /srv/fatcat/datasets/release_ids.ia_munge_20180908.sqlite3
## JALC
@@ -59,6 +60,7 @@ Usually 24 hours or so on fast production machine.
First import a random subset single threaded to create (most) containers. On a
fast machine, this takes a couple minutes.
+ # NOTE: `--extid-map-file` was used during initial import, but is now deprecated
time ./fatcat_import.py jalc /srv/fatcat/datasets/JALC-LOD-20180907.sample10k.rdf /srv/fatcat/datasets/ISSN-to-ISSN-L.txt --extid-map-file /srv/fatcat/datasets/release_ids.ia_munge_20180908.sqlite3
Then, in parallel:
@@ -116,6 +118,7 @@ Prep JSON files from sqlite (for parallel import):
Run import in parallel:
+ # NOTE: `--extid-map-file` was used during initial import, but is now deprecated
export FATCAT_AUTH_WORKER_CRAWL=...
zcat /srv/fatcat/datasets/s2_doi.json.gz | pv -l | time parallel -j12 --round-robin --pipe ./fatcat_import.py arabesque --json-file - --extid-type doi --crawl-id DIRECT-OA-CRAWL-2019 --no-require-grobid