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feat: incremental reindex_studio management command [FC-0062] [Backport] #35981

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222 changes: 142 additions & 80 deletions openedx/core/djangoapps/content/search/api.py
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@

import logging
import time
from contextlib import contextmanager
from contextlib import contextmanager, nullcontext
from datetime import datetime, timedelta, timezone
from functools import wraps
from typing import Callable, Generator
Expand All @@ -24,7 +24,14 @@
from rest_framework.request import Request
from common.djangoapps.student.role_helpers import get_course_roles
from openedx.core.djangoapps.content.course_overviews.models import CourseOverview
from openedx.core.djangoapps.content.search.models import get_access_ids_for_request
from openedx.core.djangoapps.content.search.models import get_access_ids_for_request, IncrementalIndexCompleted
from openedx.core.djangoapps.content.search.index_config import (
INDEX_DISTINCT_ATTRIBUTE,
INDEX_FILTERABLE_ATTRIBUTES,
INDEX_SEARCHABLE_ATTRIBUTES,
INDEX_SORTABLE_ATTRIBUTES,
INDEX_RANKING_RULES,
)
from openedx.core.djangoapps.content_libraries import api as lib_api
from xmodule.modulestore.django import modulestore

Expand Down Expand Up @@ -217,6 +224,42 @@ def _using_temp_index(status_cb: Callable[[str], None] | None = None) -> Generat
_wait_for_meili_task(client.delete_index(temp_index_name))


def _index_is_empty(index_name: str) -> bool:
"""
Check if an index is empty

Args:
index_name (str): The name of the index to check
"""
client = _get_meilisearch_client()
index = client.get_index(index_name)
return index.get_stats().number_of_documents == 0


def _configure_index(index_name):
"""
Configure the index. The following index settings are best changed on an empty index.
Changing them on a populated index will "re-index all documents in the index", which can take some time.

Args:
index_name (str): The name of the index to configure
"""
client = _get_meilisearch_client()

# Mark usage_key as unique (it's not the primary key for the index, but nevertheless must be unique):
client.index(index_name).update_distinct_attribute(INDEX_DISTINCT_ATTRIBUTE)
# Mark which attributes can be used for filtering/faceted search:
client.index(index_name).update_filterable_attributes(INDEX_FILTERABLE_ATTRIBUTES)
# Mark which attributes are used for keyword search, in order of importance:
client.index(index_name).update_searchable_attributes(INDEX_SEARCHABLE_ATTRIBUTES)
# Mark which attributes can be used for sorting search results:
client.index(index_name).update_sortable_attributes(INDEX_SORTABLE_ATTRIBUTES)

# Update the search ranking rules to let the (optional) "sort" parameter take precedence over keyword relevance.
# cf https://www.meilisearch.com/docs/learn/core_concepts/relevancy
client.index(index_name).update_ranking_rules(INDEX_RANKING_RULES)


def _recurse_children(block, fn, status_cb: Callable[[str], None] | None = None) -> None:
"""
Recurse the children of an XBlock and call the given function for each
Expand Down Expand Up @@ -279,8 +322,75 @@ def is_meilisearch_enabled() -> bool:
return False


# pylint: disable=too-many-statements
def rebuild_index(status_cb: Callable[[str], None] | None = None) -> None:
def reset_index(status_cb: Callable[[str], None] | None = None) -> None:
"""
Reset the Meilisearch index, deleting all documents and reconfiguring it
"""
if status_cb is None:
status_cb = log.info

status_cb("Creating new empty index...")
with _using_temp_index(status_cb) as temp_index_name:
_configure_index(temp_index_name)
status_cb("Index recreated!")
status_cb("Index reset complete.")


def _is_index_configured(index_name: str) -> bool:
"""
Check if an index is completely configured

Args:
index_name (str): The name of the index to check
"""
client = _get_meilisearch_client()
index = client.get_index(index_name)
index_settings = index.get_settings()
for k, v in (
("distinctAttribute", INDEX_DISTINCT_ATTRIBUTE),
("filterableAttributes", INDEX_FILTERABLE_ATTRIBUTES),
("searchableAttributes", INDEX_SEARCHABLE_ATTRIBUTES),
("sortableAttributes", INDEX_SORTABLE_ATTRIBUTES),
("rankingRules", INDEX_RANKING_RULES),
):
setting = index_settings.get(k, [])
if isinstance(v, list):
v = set(v)
setting = set(setting)
if setting != v:
return False
return True


def init_index(status_cb: Callable[[str], None] | None = None, warn_cb: Callable[[str], None] | None = None) -> None:
"""
Initialize the Meilisearch index, creating it and configuring it if it doesn't exist
"""
if status_cb is None:
status_cb = log.info
if warn_cb is None:
warn_cb = log.warning

if _index_exists(STUDIO_INDEX_NAME):
if _index_is_empty(STUDIO_INDEX_NAME):
warn_cb(
"The studio search index is empty. Please run ./manage.py cms reindex_studio"
" --experimental [--incremental]"
)
return
if not _is_index_configured(STUDIO_INDEX_NAME):
warn_cb(
"A rebuild of the index is required. Please run ./manage.py cms reindex_studio"
" --experimental [--incremental]"
)
return
status_cb("Index already exists and is configured.")
return

reset_index(status_cb)


def rebuild_index(status_cb: Callable[[str], None] | None = None, incremental=False) -> None: # lint-amnesty, pylint: disable=too-many-statements
"""
Rebuild the Meilisearch index from scratch
"""
Expand All @@ -292,96 +402,40 @@ def rebuild_index(status_cb: Callable[[str], None] | None = None) -> None:

# Get the lists of libraries
status_cb("Counting libraries...")
lib_keys = [lib.library_key for lib in lib_api.ContentLibrary.objects.select_related('org').only('org', 'slug')]
keys_indexed = []
if incremental:
keys_indexed = list(IncrementalIndexCompleted.objects.values_list("context_key", flat=True))
lib_keys = [
lib.library_key
for lib in lib_api.ContentLibrary.objects.select_related("org").only("org", "slug").order_by("-id")
if lib.library_key not in keys_indexed
]
num_libraries = len(lib_keys)

# Get the list of courses
status_cb("Counting courses...")
num_courses = CourseOverview.objects.count()

# Some counters so we can track our progress as indexing progresses:
num_contexts = num_courses + num_libraries
num_contexts_done = 0 # How many courses/libraries we've indexed
num_libs_skipped = len(keys_indexed)
num_contexts = num_courses + num_libraries + num_libs_skipped
num_contexts_done = 0 + num_libs_skipped # How many courses/libraries we've indexed
num_blocks_done = 0 # How many individual components/XBlocks we've indexed

status_cb(f"Found {num_courses} courses, {num_libraries} libraries.")
with _using_temp_index(status_cb) as temp_index_name:
with _using_temp_index(status_cb) if not incremental else nullcontext(STUDIO_INDEX_NAME) as index_name:
############## Configure the index ##############

# The following index settings are best changed on an empty index.
# Changing them on a populated index will "re-index all documents in the index, which can take some time"
# The index settings are best changed on an empty index.
# Changing them on a populated index will "re-index all documents in the index", which can take some time
# and use more RAM. Instead, we configure an empty index then populate it one course/library at a time.

# Mark usage_key as unique (it's not the primary key for the index, but nevertheless must be unique):
client.index(temp_index_name).update_distinct_attribute(Fields.usage_key)
# Mark which attributes can be used for filtering/faceted search:
client.index(temp_index_name).update_filterable_attributes([
# Get specific block/collection using combination of block_id and context_key
Fields.block_id,
Fields.block_type,
Fields.context_key,
Fields.usage_key,
Fields.org,
Fields.tags,
Fields.tags + "." + Fields.tags_taxonomy,
Fields.tags + "." + Fields.tags_level0,
Fields.tags + "." + Fields.tags_level1,
Fields.tags + "." + Fields.tags_level2,
Fields.tags + "." + Fields.tags_level3,
Fields.collections,
Fields.collections + "." + Fields.collections_display_name,
Fields.collections + "." + Fields.collections_key,
Fields.type,
Fields.access_id,
Fields.last_published,
Fields.content + "." + Fields.problem_types,
])
# Mark which attributes are used for keyword search, in order of importance:
client.index(temp_index_name).update_searchable_attributes([
# Keyword search does _not_ search the course name, course ID, breadcrumbs, block type, or other fields.
Fields.display_name,
Fields.block_id,
Fields.content,
Fields.description,
Fields.tags,
Fields.collections,
# If we don't list the following sub-fields _explicitly_, they're only sometimes searchable - that is, they
# are searchable only if at least one document in the index has a value. If we didn't list them here and,
# say, there were no tags.level3 tags in the index, the client would get an error if trying to search for
# these sub-fields: "Attribute `tags.level3` is not searchable."
Fields.tags + "." + Fields.tags_taxonomy,
Fields.tags + "." + Fields.tags_level0,
Fields.tags + "." + Fields.tags_level1,
Fields.tags + "." + Fields.tags_level2,
Fields.tags + "." + Fields.tags_level3,
Fields.collections + "." + Fields.collections_display_name,
Fields.collections + "." + Fields.collections_key,
Fields.published + "." + Fields.display_name,
Fields.published + "." + Fields.published_description,
])
# Mark which attributes can be used for sorting search results:
client.index(temp_index_name).update_sortable_attributes([
Fields.display_name,
Fields.created,
Fields.modified,
Fields.last_published,
])

# Update the search ranking rules to let the (optional) "sort" parameter take precedence over keyword relevance.
# cf https://www.meilisearch.com/docs/learn/core_concepts/relevancy
client.index(temp_index_name).update_ranking_rules([
"sort",
"words",
"typo",
"proximity",
"attribute",
"exactness",
])
if not incremental:
_configure_index(index_name)

############## Libraries ##############
status_cb("Indexing libraries...")

def index_library(lib_key: str) -> list:
def index_library(lib_key: LibraryLocatorV2) -> list:
docs = []
for component in lib_api.get_library_components(lib_key):
try:
Expand All @@ -396,7 +450,7 @@ def index_library(lib_key: str) -> list:
if docs:
try:
# Add all the docs in this library at once (usually faster than adding one at a time):
_wait_for_meili_task(client.index(temp_index_name).add_documents(docs))
_wait_for_meili_task(client.index(index_name).add_documents(docs))
except (TypeError, KeyError, MeilisearchError) as err:
status_cb(f"Error indexing library {lib_key}: {err}")
return docs
Expand All @@ -416,7 +470,7 @@ def index_collection_batch(batch, num_done, library_key) -> int:
if docs:
try:
# Add docs in batch of 100 at once (usually faster than adding one at a time):
_wait_for_meili_task(client.index(temp_index_name).add_documents(docs))
_wait_for_meili_task(client.index(index_name).add_documents(docs))
except (TypeError, KeyError, MeilisearchError) as err:
status_cb(f"Error indexing collection batch {p}: {err}")
return num_done
Expand All @@ -439,6 +493,8 @@ def index_collection_batch(batch, num_done, library_key) -> int:
num_collections_done,
lib_key,
)
if incremental:
IncrementalIndexCompleted.objects.get_or_create(context_key=lib_key)
status_cb(f"{num_collections_done}/{num_collections} collections indexed for library {lib_key}")

num_contexts_done += 1
Expand All @@ -464,7 +520,7 @@ def add_with_children(block):

if docs:
# Add all the docs in this course at once (usually faster than adding one at a time):
_wait_for_meili_task(client.index(temp_index_name).add_documents(docs))
_wait_for_meili_task(client.index(index_name).add_documents(docs))
return docs

paginator = Paginator(CourseOverview.objects.only('id', 'display_name'), 1000)
Expand All @@ -473,10 +529,16 @@ def add_with_children(block):
status_cb(
f"{num_contexts_done + 1}/{num_contexts}. Now indexing course {course.display_name} ({course.id})"
)
if course.id in keys_indexed:
num_contexts_done += 1
continue
course_docs = index_course(course)
if incremental:
IncrementalIndexCompleted.objects.get_or_create(context_key=course.id)
num_contexts_done += 1
num_blocks_done += len(course_docs)

IncrementalIndexCompleted.objects.all().delete()
status_cb(f"Done! {num_blocks_done} blocks indexed across {num_contexts_done} courses, collections and libraries.")


Expand Down
70 changes: 70 additions & 0 deletions openedx/core/djangoapps/content/search/index_config.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,70 @@
"""Configuration for the search index."""
from .documents import Fields


INDEX_DISTINCT_ATTRIBUTE = "usage_key"

# Mark which attributes can be used for filtering/faceted search:
INDEX_FILTERABLE_ATTRIBUTES = [
# Get specific block/collection using combination of block_id and context_key
Fields.block_id,
Fields.block_type,
Fields.context_key,
Fields.usage_key,
Fields.org,
Fields.tags,
Fields.tags + "." + Fields.tags_taxonomy,
Fields.tags + "." + Fields.tags_level0,
Fields.tags + "." + Fields.tags_level1,
Fields.tags + "." + Fields.tags_level2,
Fields.tags + "." + Fields.tags_level3,
Fields.collections,
Fields.collections + "." + Fields.collections_display_name,
Fields.collections + "." + Fields.collections_key,
Fields.type,
Fields.access_id,
Fields.last_published,
Fields.content + "." + Fields.problem_types,
]

# Mark which attributes are used for keyword search, in order of importance:
INDEX_SEARCHABLE_ATTRIBUTES = [
# Keyword search does _not_ search the course name, course ID, breadcrumbs, block type, or other fields.
Fields.display_name,
Fields.block_id,
Fields.content,
Fields.description,
Fields.tags,
Fields.collections,
# If we don't list the following sub-fields _explicitly_, they're only sometimes searchable - that is, they
# are searchable only if at least one document in the index has a value. If we didn't list them here and,
# say, there were no tags.level3 tags in the index, the client would get an error if trying to search for
# these sub-fields: "Attribute `tags.level3` is not searchable."
Fields.tags + "." + Fields.tags_taxonomy,
Fields.tags + "." + Fields.tags_level0,
Fields.tags + "." + Fields.tags_level1,
Fields.tags + "." + Fields.tags_level2,
Fields.tags + "." + Fields.tags_level3,
Fields.collections + "." + Fields.collections_display_name,
Fields.collections + "." + Fields.collections_key,
Fields.published + "." + Fields.display_name,
Fields.published + "." + Fields.published_description,
]

# Mark which attributes can be used for sorting search results:
INDEX_SORTABLE_ATTRIBUTES = [
Fields.display_name,
Fields.created,
Fields.modified,
Fields.last_published,
]

# Update the search ranking rules to let the (optional) "sort" parameter take precedence over keyword relevance.
INDEX_RANKING_RULES = [
"sort",
"words",
"typo",
"proximity",
"attribute",
"exactness",
]
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