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-rw-r--r--python/README_import.md18
1 files changed, 16 insertions, 2 deletions
diff --git a/python/README_import.md b/python/README_import.md
index 7301d72e..f43d9424 100644
--- a/python/README_import.md
+++ b/python/README_import.md
@@ -23,8 +23,13 @@ the others:
From CSV file:
+ export LC_ALL=C.UTF-8
time ./client.py import-issn /srv/datasets/journal_extra_metadata.csv
+ real 2m42.148s
+ user 0m11.148s
+ sys 0m0.336s
+
Pretty quick, a few minutes.
## ORCID
@@ -33,7 +38,8 @@ Directly from compressed tarball; takes about 2 hours in production:
tar xf /srv/datasets/public_profiles_API-2.0_2017_10_json.tar.gz -O | jq -c . | grep '"person":' | time parallel -j12 --pipe --round-robin ./client.py import-orcid -
-Or, from pre-uncompressed tarball:
+After tuning database, `jq` CPU seems to be bottleneck, so, from pre-extracted
+tarball:
tar xf /srv/datasets/public_profiles_API-2.0_2017_10_json.tar.gz -O | jq -c . | rg '"person":' > /srv/datasets/public_profiles_1_2_json.all.json
time parallel --bar --pipepart -j8 -a /srv/datasets/public_profiles_1_2_json.all.json ./client.py import-orcid -
@@ -76,11 +82,19 @@ For the full batch, on production machine with 12 threads, around 3.8 million re
=> 644/second
+After some simple database tuning:
+
+ 2177.86 user
+ 145.60 system
+ 56:41.26 elapsed
+
+ => 1117/second
+
## Crossref
From compressed:
- xzcat /srv/datasets/crossref-works.2018-01-21.json.xz | time parallel -j12 --round-robin --pipe ./client.py import-crossref - /srv/datasets/20180216.ISSN-to-ISSN-L.txt
+ xzcat /srv/datasets/crossref-works.2018-01-21.json.xz | time parallel -j20 --round-robin --pipe ./client.py import-crossref - /srv/datasets/20180216.ISSN-to-ISSN-L.txt
## Manifest