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Major optimization to both single feed loads and river loads. Both are now checking training only for trained feeds, and river makes only a single subscirption call instead of N subscription calls.

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Samuel Clay 2013-06-25 15:41:42 -07:00
parent b8e6ff4a70
commit e62b058638
2 changed files with 24 additions and 14 deletions
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15
apps/reader/models.py
View file

@ -100,7 +100,7 @@ class UserSubscription(models.Model):
else: else:
r.delete(unread_ranked_stories_key) r.delete(unread_ranked_stories_key)
if not r.exists(stories_key): if not r.exists(stories_key):
print " ---> No stories on feed: %s" % self # print " ---> No stories on feed: %s" % self
return [] return []
elif read_filter != 'unread' or not r.exists(read_stories_key): elif read_filter != 'unread' or not r.exists(read_stories_key):
ignore_user_stories = True ignore_user_stories = True
@ -157,7 +157,8 @@ class UserSubscription(models.Model):
return [] return []
@classmethod @classmethod
def feed_stories(cls, user_id, feed_ids, offset=0, limit=6, order='newest', read_filter='all'): def feed_stories(cls, user_id, feed_ids, offset=0, limit=6, order='newest', read_filter='all',
usersubs=None):
r = redis.Redis(connection_pool=settings.REDIS_STORY_HASH_POOL) r = redis.Redis(connection_pool=settings.REDIS_STORY_HASH_POOL)
if order == 'oldest': if order == 'oldest':
@ -178,11 +179,15 @@ class UserSubscription(models.Model):
r.delete(ranked_stories_keys) r.delete(ranked_stories_keys)
cache.delete(unread_ranked_stories_keys) cache.delete(unread_ranked_stories_keys)
if not usersubs:
usersubs = cls.objects.get(user=user_id, feed__in=feed_ids)
usersubs = dict((sub.feed_id, sub) for sub in usersubs)
unread_feed_story_hashes = {} unread_feed_story_hashes = {}
for feed_id in feed_ids: for feed_id in feed_ids:
try: if feed_id in usersubs:
us = cls.objects.get(user=user_id, feed=feed_id) us = usersubs[feed_id]
except cls.DoesNotExist: else:
continue continue
story_hashes = us.get_stories(offset=0, limit=200, story_hashes = us.get_stories(offset=0, limit=200,
order=order, read_filter=read_filter, order=order, read_filter=read_filter,

19
apps/reader/views.py
View file

@ -786,8 +786,10 @@ def load_river_stories__redis(request):
now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone) now = localtime_for_timezone(datetime.datetime.now(), user.profile.timezone)
if not feed_ids and not story_hashes: if not feed_ids and not story_hashes:
usersubs = UserSubscription.objects.filter(user=user, active=True).only('feed') usersubs = UserSubscription.objects.filter(user=user, active=True)
feed_ids = [sub.feed_id for sub in usersubs] feed_ids = [sub.feed_id for sub in usersubs]
else:
usersubs = UserSubscription.objects.filter(user=user, active=True, feed__in=feed_ids)
offset = (page-1) * limit offset = (page-1) * limit
limit = page * limit - 1 limit = page * limit - 1
@ -800,11 +802,14 @@ def load_river_stories__redis(request):
story_hashes, unread_feed_story_hashes = UserSubscription.feed_stories(user.pk, feed_ids, story_hashes, unread_feed_story_hashes = UserSubscription.feed_stories(user.pk, feed_ids,
offset=offset, limit=limit, offset=offset, limit=limit,
order=order, order=order,
read_filter=read_filter) read_filter=read_filter,
usersubs=usersubs)
mstories = MStory.objects(story_hash__in=story_hashes).order_by(story_date_order) mstories = MStory.objects(story_hash__in=story_hashes).order_by(story_date_order)
stories = Feed.format_stories(mstories) stories = Feed.format_stories(mstories)
found_feed_ids = list(set([story['story_feed_id'] for story in stories])) found_feed_ids = list(set([story['story_feed_id'] for story in stories]))
stories, user_profiles = MSharedStory.stories_with_comments_and_profiles(stories, user.pk) stories, user_profiles = MSharedStory.stories_with_comments_and_profiles(stories, user.pk)
trained_feed_ids = [sub.feed_id for sub in usersubs if sub.is_trained]
found_trained_feed_ids = list(set(trained_feed_ids) & set(found_feed_ids))
# Find starred stories # Find starred stories
if found_feed_ids: if found_feed_ids:
@ -818,15 +823,15 @@ def load_river_stories__redis(request):
starred_stories = {} starred_stories = {}
# Intelligence classifiers for all feeds involved # Intelligence classifiers for all feeds involved
if found_feed_ids: if found_trained_feed_ids:
classifier_feeds = list(MClassifierFeed.objects(user_id=user.pk, classifier_feeds = list(MClassifierFeed.objects(user_id=user.pk,
feed_id__in=found_feed_ids)) feed_id__in=found_trained_feed_ids))
classifier_authors = list(MClassifierAuthor.objects(user_id=user.pk, classifier_authors = list(MClassifierAuthor.objects(user_id=user.pk,
feed_id__in=found_feed_ids)) feed_id__in=found_trained_feed_ids))
classifier_titles = list(MClassifierTitle.objects(user_id=user.pk, classifier_titles = list(MClassifierTitle.objects(user_id=user.pk,
feed_id__in=found_feed_ids)) feed_id__in=found_trained_feed_ids))
classifier_tags = list(MClassifierTag.objects(user_id=user.pk, classifier_tags = list(MClassifierTag.objects(user_id=user.pk,
feed_id__in=found_feed_ids)) feed_id__in=found_trained_feed_ids))
else: else:
classifier_feeds = [] classifier_feeds = []
classifier_authors = [] classifier_authors = []