Online Advertising Networks - MongoDB Applied Design Patterns - page 144

Finally, we iterate through each of the ads and check it using the
ad_is_acceptable function.

Here's our ad_iterator generator:

def def ad_iterator ( ads ):

'''Find available ads, sorted by ecpm, with random sort for ties'''
ecpm_groups = groupby ( ads , key = lambda

lambda ad : ad [ 'ecpm' ])

for for ecpm , ad_group iin ecpm_groups :

ad_group = list ( ad_group )
shuffle ( ad_group )
for for ad iin ad_group : yield yield ad

This generator yields the ads in an order that both maximizes profitability and randomly
shuffles ads of the same eCPM. Finally, here's our ad filter ad_is_acceptable :

def def ad_is_acceptable ( ad , profile ):

'''Returns False if the user has seen the ad today'''
threshold = datetime . utcnow () - timedelta ( days = 1 )
for for event iin reversed ( profile [ 'impressions' ]):

iif event [ 'timestamp' ] < threshold : break break

iif event [ 'detail' ][ 'ad_unit_id' ] == ad [ 'ad_unit_id' ]:
return

return False

return return True

This function examines all the user's ad impressions for the current day and rejects an ad that
has been displayed to that user.

In order to retrieve the user profile with the lowest latency possible, there needs to be an index
on the _id field, which MongoDB supplies by default.

Sharding

When sharding the ad.user collection, choosing the _id field as a shard key allows Mon-
goDB to route queries and updates to the user profile:

>>> >>> db . command ( 'shardcollection' , 'dbname.ads.ad.user' , {

...

... 'key' : { '_id' : 1 } })
{ "collectionsharded": "dbname.ads.ad.user", "ok": 1 }