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dspace-statistics-api/indexer.py
Alan Orth e604d8ca81
indexer.py: Major refactor
Basically Solr's numFound has nothing to do with the actual number
of distinct facets that are returned. You need to use Solr's stats
component to get the number of distinct facets, aka countDistinct.
This is apparently deprecated in newer Solr versions, but we're on
version 4.10 and it works there.

Also, I realized that there is no need to return facets for items
without any views or downloads. Using facet.mincount=1 reduces the
result set size and also means we can store less data in the data-
base. The API returns HTTP 404 Not Found if an item is not in the
database anyways.

I can't figure it out exactly, but there is some weird issue with
Solr's facet results when you don't use facet.mincount=1. For some
reason you get tons of results with an id that doesn't even exist
in the document database, let alone as an actual DSpace item!

See: https://lucene.apache.org/solr/guide/6_6/the-stats-component.html
2018-09-26 02:41:10 +03:00

162 lines
5.7 KiB
Python
Executable File

#!/usr/bin/env python
#
# indexer.py
#
# Copyright 2018 Alan Orth.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# ---
#
# Connects to a DSpace Solr statistics core and ingests item views and downloads
# into a PostgreSQL database for use by other applications (like an API).
#
# This script is written for Python 3.5+ and requires several modules that you
# can install with pip (I recommend using a Python virtual environment):
#
# $ pip install SolrClient psycopg2-binary
#
# See: https://solrclient.readthedocs.io/en/latest/SolrClient.html
# See: https://wiki.duraspace.org/display/DSPACE/Solr
from database import database_connection
import json
from solr import solr_connection
def index_views():
# get total number of distinct facets for items with a minimum of 1 view,
# otherwise Solr returns all kinds of weird ids that are actually not in
# the database. Also, stats are expensive, but we need stats.calcdistinct
# so we can get the countDistinct summary.
#
# see: https://lucene.apache.org/solr/guide/6_6/the-stats-component.html
res = solr.query('statistics', {
'q':'type:2',
'fq':'isBot:false AND statistics_type:view',
'facet':True,
'facet.field':'id',
'facet.mincount':1,
'facet.limit':1,
'facet.offset':0,
'stats':True,
'stats.field':'id',
'stats.calcdistinct':True
}, rows=0)
# get total number of distinct facets (countDistinct)
results_totalNumFacets = json.loads(res.get_json())['stats']['stats_fields']['id']['countDistinct']
# divide results into "pages" (cast to int to effectively round down)
results_per_page = 100
results_num_pages = int(results_totalNumFacets / results_per_page)
results_current_page = 0
cursor = db.cursor()
while results_current_page <= results_num_pages:
print('Indexing item views (page {} of {})'.format(results_current_page, results_num_pages))
res = solr.query('statistics', {
'q':'type:2',
'fq':'isBot:false AND statistics_type:view',
'facet':True,
'facet.field':'id',
'facet.mincount':1,
'facet.limit':results_per_page,
'facet.offset':results_current_page * results_per_page
}, rows=0)
# check number of facets returned in the last query
#results_currentNumFacets = len(res.get_facets()['id'])
# SolrClient's get_facets() returns a dict of dicts
views = res.get_facets()
# in this case iterate over the 'id' dict and get the item ids and views
for item_id, item_views in views['id'].items():
cursor.execute('''INSERT INTO items(id, views) VALUES(%s, %s)
ON CONFLICT(id) DO UPDATE SET downloads=excluded.views''',
(item_id, item_views))
db.commit()
results_current_page += 1
cursor.close()
def index_downloads():
# get the total number of distinct facets for items with at least 1 download
res = solr.query('statistics', {
'q':'type:0',
'fq':'isBot:false AND statistics_type:view AND bundleName:ORIGINAL',
'facet':True,
'facet.field':'owningItem',
'facet.mincount':1,
'facet.limit':1,
'facet.offset':0,
'stats':True,
'stats.field':'owningItem',
'stats.calcdistinct':True
}, rows=0)
# get total number of distinct facets (countDistinct)
results_totalNumFacets = json.loads(res.get_json())['stats']['stats_fields']['owningItem']['countDistinct']
# divide results into "pages" (cast to int to effectively round down)
results_per_page = 100
results_num_pages = int(results_totalNumFacets / results_per_page)
results_current_page = 0
cursor = db.cursor()
while results_current_page <= results_num_pages:
print('Indexing item downloads (page {} of {})'.format(results_current_page, results_num_pages))
res = solr.query('statistics', {
'q':'type:0',
'fq':'isBot:false AND statistics_type:view AND bundleName:ORIGINAL',
'facet':True,
'facet.field':'owningItem',
'facet.mincount':1,
'facet.limit':results_per_page,
'facet.offset':results_current_page * results_per_page
}, rows=0)
# SolrClient's get_facets() returns a dict of dicts
downloads = res.get_facets()
# in this case iterate over the 'owningItem' dict and get the item ids and downloads
for item_id, item_downloads in downloads['owningItem'].items():
cursor.execute('''INSERT INTO items(id, downloads) VALUES(%s, %s)
ON CONFLICT(id) DO UPDATE SET downloads=excluded.downloads''',
(item_id, item_downloads))
db.commit()
results_current_page += 1
cursor.close()
db = database_connection()
solr = solr_connection()
# create table to store item views and downloads
cursor = db.cursor()
cursor.execute('''CREATE TABLE IF NOT EXISTS items
(id INT PRIMARY KEY, views INT DEFAULT 0, downloads INT DEFAULT 0)''')
index_views()
index_downloads()
db.close()
# vim: set sw=4 ts=4 expandtab: