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mirror of https://github.com/ilri/dspace-statistics-api.git synced 2024-11-25 07:40:17 +01:00

indexer.py: Add support for communities and collections

The logic to get views and downloads is very similar to that used
for items, but we facet by different fields. This uses a generic
function for indexing that takes an "indexType" and a "facetField"
parameter. The indexType parameter controls which database table
to insert into, and the facetField parameter indicates which field
to facet by in Solr.
This commit is contained in:
Alan Orth 2020-12-18 10:57:22 +02:00
parent b486f51dd7
commit 20c8ba0cf8

View File

@ -18,8 +18,8 @@
#
# ---
#
# 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).
# 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):
@ -36,7 +36,7 @@ from .database import DatabaseManager
from .util import get_statistics_shards
def index_item_views():
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
@ -47,14 +47,14 @@ def index_item_views():
solr_query_params = {
"q": "type:2",
"fq": "-isBot:true AND statistics_type:view",
"fl": "id",
"fl": facetField,
"facet": "true",
"facet.field": "id",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": 1,
"facet.offset": 0,
"stats": "true",
"stats.field": "id",
"stats.field": facetField,
"stats.calcdistinct": "true",
"shards": shards,
"rows": 0,
@ -67,11 +67,11 @@ def index_item_views():
try:
# get total number of distinct facets (countDistinct)
results_totalNumFacets = res.json()["stats"]["stats_fields"]["id"][
results_totalNumFacets = res.json()["stats"]["stats_fields"][facetField][
"countDistinct"
]
except TypeError:
print("No item views to index, exiting.")
print(f"{indexType}: no views, exiting.")
exit(0)
@ -88,15 +88,15 @@ def index_item_views():
while results_current_page <= results_num_pages:
# "pages" are zero based, but one based is more human readable
print(
f"Indexing item views (page {results_current_page + 1} of {results_num_pages + 1})"
f"{indexType}: indexing views (page {results_current_page + 1} of {results_num_pages + 1})"
)
solr_query_params = {
"q": "type:2",
"fq": "-isBot:true AND statistics_type:view",
"fl": "id",
"fl": facetField,
"facet": "true",
"facet.field": "id",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": results_per_page,
"facet.offset": results_current_page * results_per_page,
@ -110,12 +110,12 @@ def index_item_views():
# Solr returns facets as a dict of dicts (see json.nl parameter)
views = res.json()["facet_counts"]["facet_fields"]
# 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))
# 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 = "INSERT INTO items(id, views) VALUES %s ON CONFLICT(id) DO UPDATE SET views=excluded.views"
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()
@ -125,19 +125,19 @@ def index_item_views():
results_current_page += 1
def index_item_downloads():
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": "type:0",
"fq": "-isBot:true AND statistics_type:view AND bundleName:ORIGINAL",
"fl": "owningItem",
"fl": facetField,
"facet": "true",
"facet.field": "owningItem",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": 1,
"facet.offset": 0,
"stats": "true",
"stats.field": "owningItem",
"stats.field": facetField,
"stats.calcdistinct": "true",
"shards": shards,
"rows": 0,
@ -150,11 +150,11 @@ def index_item_downloads():
try:
# get total number of distinct facets (countDistinct)
results_totalNumFacets = res.json()["stats"]["stats_fields"]["owningItem"][
results_totalNumFacets = res.json()["stats"]["stats_fields"][facetField][
"countDistinct"
]
except TypeError:
print("No item downloads to index, exiting.")
print(f"{indexType}: no downloads, exiting.")
exit(0)
@ -171,15 +171,15 @@ def index_item_downloads():
while results_current_page <= results_num_pages:
# "pages" are zero based, but one based is more human readable
print(
f"Indexing item downloads (page {results_current_page + 1} of {results_num_pages + 1})"
f"{indexType}: indexing downloads (page {results_current_page + 1} of {results_num_pages + 1})"
)
solr_query_params = {
"q": "type:0",
"fq": "-isBot:true AND statistics_type:view AND bundleName:ORIGINAL",
"fl": "owningItem",
"fl": facetField,
"facet": "true",
"facet.field": "owningItem",
"facet.field": facetField,
"facet.mincount": 1,
"facet.limit": results_per_page,
"facet.offset": results_current_page * results_per_page,
@ -193,12 +193,12 @@ def index_item_downloads():
# Solr returns facets as a dict of dicts (see json.nl parameter)
downloads = res.json()["facet_counts"]["facet_fields"]
# 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))
# 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 = "INSERT INTO items(id, downloads) VALUES %s ON CONFLICT(id) DO UPDATE SET downloads=excluded.downloads"
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()
@ -215,13 +215,32 @@ with DatabaseManager() as db:
"""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_item_views()
index_item_downloads()
# 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: