mirror of
https://github.com/ilri/dspace-statistics-api.git
synced 2024-11-16 11:27:03 +01:00
173 lines
6.1 KiB
Python
173 lines
6.1 KiB
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
|
|
import psycopg2.extras
|
|
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()
|
|
|
|
# create an empty list to store values for batch insertion
|
|
data = []
|
|
|
|
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)
|
|
|
|
# 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():
|
|
data.append((item_id, item_views))
|
|
|
|
# do a batch insert of values from the current "page" of results
|
|
sql = 'INSERT INTO items(id, views) VALUES %s ON CONFLICT(id) DO UPDATE SET views=excluded.views'
|
|
psycopg2.extras.execute_values(cursor, sql, data, template='(%s, %s)')
|
|
db.commit()
|
|
|
|
# clear all items from the list so we can populate it with the next batch
|
|
data.clear()
|
|
|
|
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()
|
|
|
|
# create an empty list to store values for batch insertion
|
|
data = []
|
|
|
|
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():
|
|
data.append((item_id, item_downloads))
|
|
|
|
# do a batch insert of values from the current "page" of results
|
|
sql = 'INSERT INTO items(id, downloads) VALUES %s ON CONFLICT(id) DO UPDATE SET downloads=excluded.downloads'
|
|
psycopg2.extras.execute_values(cursor, sql, data, template='(%s, %s)')
|
|
db.commit()
|
|
|
|
# clear all items from the list so we can populate it with the next batch
|
|
data.clear()
|
|
|
|
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:
|