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