dspace-statistics-api/dspace_statistics_api/indexer.py

232 lines
8.6 KiB
Python

# SPDX-License-Identifier: GPL-3.0-only
#
# indexer.py
#
# Connects to a DSpace Solr statistics core and ingests views and downloads for
# communities, collections, and items into a PostgreSQL database.
#
# This script is written for Python 3.6+ and requires several modules that you
# can install with pip (I recommend using a Python virtual environment):
#
# $ pip install psycopg2-binary
#
# See: https://wiki.duraspace.org/display/DSPACE/Solr
import math
import psycopg2.extras
import requests
from .config import SOLR_SERVER
from .database import DatabaseManager
from .util import get_statistics_shards
def index_views(indexType: str, facetField: str):
# 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 to calculate how many pages of
# results we have.
#
# see: https://lucene.apache.org/solr/guide/6_6/the-stats-component.html
solr_query_params = {
"q": f"type:2 AND {facetField}:/.{{36}}/",
"fq": "-isBot:true AND statistics_type:view",
"fl": facetField,
"facet": "true",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": 1,
"facet.offset": 0,
"stats": "true",
"stats.field": facetField,
"stats.calcdistinct": "true",
"shards": shards,
"rows": 0,
"wt": "json",
}
solr_url = SOLR_SERVER + "/statistics/select"
res = requests.get(solr_url, params=solr_query_params)
try:
# get total number of distinct facets (countDistinct)
results_totalNumFacets = res.json()["stats"]["stats_fields"][facetField][
"countDistinct"
]
except TypeError:
print(f"{indexType}: no views, exiting.")
exit(0)
# divide results into "pages" and round up to next integer
results_per_page = 100
results_num_pages = math.ceil(results_totalNumFacets / results_per_page)
results_current_page = 0
with DatabaseManager() as db:
with db.cursor() as cursor:
# create an empty list to store values for batch insertion
data = []
while results_current_page <= results_num_pages:
# "pages" are zero based, but one based is more human readable
print(
f"{indexType}: indexing views (page {results_current_page + 1} of {results_num_pages + 1})"
)
solr_query_params = {
"q": f"type:2 AND {facetField}:/.{{36}}/",
"fq": "-isBot:true AND statistics_type:view",
"fl": facetField,
"facet": "true",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": results_per_page,
"facet.offset": results_current_page * results_per_page,
"shards": shards,
"rows": 0,
"wt": "json",
"json.nl": "map", # return facets as a dict instead of a flat list
}
res = requests.get(solr_url, params=solr_query_params)
# Solr returns facets as a dict of dicts (see json.nl parameter)
views = res.json()["facet_counts"]["facet_fields"]
# iterate over the facetField dict and get the ids and views
for id_, views in views[facetField].items():
data.append((id_, views))
# do a batch insert of values from the current "page" of results
sql = f"INSERT INTO {indexType}(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
def index_downloads(indexType: str, facetField: str):
# get the total number of distinct facets for items with at least 1 download
solr_query_params = {
"q": f"type:0 AND {facetField}:/.{{36}}/",
"fq": "-isBot:true AND statistics_type:view AND bundleName:ORIGINAL",
"fl": facetField,
"facet": "true",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": 1,
"facet.offset": 0,
"stats": "true",
"stats.field": facetField,
"stats.calcdistinct": "true",
"shards": shards,
"rows": 0,
"wt": "json",
}
solr_url = SOLR_SERVER + "/statistics/select"
res = requests.get(solr_url, params=solr_query_params)
try:
# get total number of distinct facets (countDistinct)
results_totalNumFacets = res.json()["stats"]["stats_fields"][facetField][
"countDistinct"
]
except TypeError:
print(f"{indexType}: no downloads, exiting.")
exit(0)
results_per_page = 100
results_num_pages = math.ceil(results_totalNumFacets / results_per_page)
results_current_page = 0
with DatabaseManager() as db:
with db.cursor() as cursor:
# create an empty list to store values for batch insertion
data = []
while results_current_page <= results_num_pages:
# "pages" are zero based, but one based is more human readable
print(
f"{indexType}: indexing downloads (page {results_current_page + 1} of {results_num_pages + 1})"
)
solr_query_params = {
"q": f"type:0 AND {facetField}:/.{{36}}/",
"fq": "-isBot:true AND statistics_type:view AND bundleName:ORIGINAL",
"fl": facetField,
"facet": "true",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": results_per_page,
"facet.offset": results_current_page * results_per_page,
"shards": shards,
"rows": 0,
"wt": "json",
"json.nl": "map", # return facets as a dict instead of a flat list
}
res = requests.get(solr_url, params=solr_query_params)
# Solr returns facets as a dict of dicts (see json.nl parameter)
downloads = res.json()["facet_counts"]["facet_fields"]
# iterate over the facetField dict and get the item ids and downloads
for id_, downloads in downloads[facetField].items():
data.append((id_, downloads))
# do a batch insert of values from the current "page" of results
sql = f"INSERT INTO {indexType}(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
with DatabaseManager() as db:
with db.cursor() as cursor:
# create table to store item views and downloads
cursor.execute(
"""CREATE TABLE IF NOT EXISTS items
(id UUID PRIMARY KEY, views INT DEFAULT 0, downloads INT DEFAULT 0)"""
)
# create table to store community views and downloads
cursor.execute(
"""CREATE TABLE IF NOT EXISTS communities
(id UUID PRIMARY KEY, views INT DEFAULT 0, downloads INT DEFAULT 0)"""
)
# create table to store collection views and downloads
cursor.execute(
"""CREATE TABLE IF NOT EXISTS collections
(id UUID PRIMARY KEY, views INT DEFAULT 0, downloads INT DEFAULT 0)"""
)
# commit the table creation before closing the database connection
db.commit()
shards = get_statistics_shards()
# Index views and downloads for items, communities, and collections. Here the
# first parameter is the type of indexing to perform, and the second parameter
# is the field to facet by in Solr's statistics to get this information.
index_views("items", "id")
index_views("communities", "owningComm")
index_views("collections", "owningColl")
index_downloads("items", "owningItem")
index_downloads("communities", "owningComm")
index_downloads("collections", "owningColl")
# vim: set sw=4 ts=4 expandtab: