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diff --git a/python/README_import.md b/python/README_import.md index 04b838f8..027ce7ad 100644 --- a/python/README_import.md +++ b/python/README_import.md @@ -54,6 +54,48 @@ Usually 24 hours or so on fast production machine. 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/20180216.ISSN-to-ISSN-L.txt --extid-map-file /srv/fatcat/datasets/release_ids.ia_munge_20180908.sqlite3 +## JALC + +First import a random subset single threaded to create (most) containers. On a +fast machine, this takes a couple minutes. + + 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: + + zcat /srv/fatcat/datasets/JALC-LOD-20180907.gz | pv -l | time parallel -j20 --round-robin --pipe ./fatcat_import.py jalc - /srv/fatcat/datasets/ISSN-to-ISSN-L.txt --extid-map-file /srv/fatcat/datasets/release_ids.ia_munge_20180908.sqlite3 + +## JSTOR + +Looks like: + + fd . /data/jstor/metadata/ | time parallel -j20 --round-robin --pipe ./fatcat_import.py jstor - /data/issn/20190129.ISSN-to-ISSN-L.txt + +## arXiv + +Single file: + + ./fatcat_import.py arxiv /srv/fatcat/datasets/arxiv_raw_oai_snapshot_2019-05-22/2007-12-31-00000001.xml + +Bulk (one file per process): + + fd .xml /srv/fatcat/datasets/arxiv_raw_oai_snapshot_2019-05-22/ | parallel -j15 ./fatcat_import.py arxiv {} + +## PubMed + +Run single: + + time ./fatcat_import.py pubmed /srv/fatcat/datasets/pubmed_medline_baseline_2019/pubmed19n0400.xml /srv/fatcat/datasets/ISSN-to-ISSN-L.txt + + real 13m21.756s + user 9m10.720s + sys 0m14.100s + +Bulk: + + # very memory intensive to parse these big XML files, so need to limit parallelism + fd .xml /srv/fatcat/datasets/pubmed_medline_baseline_2019 | time parallel -j3 ./fatcat_import.py pubmed {} /srv/fatcat/datasets/ISSN-to-ISSN-L.txt + ## Matched These each take 2-4 hours: |