Hi There. We need as part of our start-up product to compute "similar user feature". And we've decided to go with pig for it. I've been learning pig for a few days now and understand how it work. So to start here is how the log file look like.
user url time user1 http://someurl.com 1235416 user1 http://anotherlik.com 1255330 user2 http://someurl.com 1705012 user3 http://something.com 1705042 user3 http://someurl.com 1705042 As the number of users and url can be huge, we can't use a bruteforce approach here, so first we need to find the user's that have access at least to on common url. The algorithm could be splited as bellow: 1. Find all users that has accessed to some common urls. 2. generate pair-wise combination of all users for each resource accessed. 3. for each pair and and url, compute the similarity of those users: the similarity depend of the timeinterval between the access (so we need to keep track of the time). 4. sum up for each pair-url the similarity. here is what i've written so far: A = LOAD 'logs.txt' USING PigStorage('\t') AS (uid:bytearray, url:bytearray, time:long); grouped_pos = GROUP A BY ($1); I know it is not much yet, but now i don't know how to generate the pair or move further. So any help would be appreciated. Thanks.
