elif api == 'id_list': ## this for debugging purposes
userid = message['userid']
itemid = message['itemid']
timestamp = message['timestamp']
domainid = message['domainid']
additional_filter = {'domainid': domainid}
if config_global.SAVE_RANDOM_RECOMMENDER in backends:
fb = Random_Recommender()
fb.set_recommendables(itemid, additional_filter)
if config_global.SAVE_HADOOP_SINK in backends:
hS = HadoopSink(append=True)
rating = 1
hS.save_mode2(userid, itemid, domainid, timestamp)
if config_global.SAVE_USER_STATS in backends:
us = UserStats('userid', 'itemid')
us.save(userid, itemid)
#save sync
else:
body_message = {'message': message,
'api': api,
'backends': backends}
body_message = pickle.dumps(body_message)
""" select as much ids as you want then enque this as a replay job.
Each worker will then fetch the task from the queue and request to
the Request handler then """
""" grab the messages and send them as a post to the contest request handler """
db=_mysql.connect(host="localhost",user="******",
passwd=config_local.mysql_password,db="contest")
SAVE_ITEM_BY_USER = False
SAVE_DIMENSION_LIST = False
SAVE_DISTRIBUTED_COUNTER = False
SAVE_HADOOP_SINK = False
hS = HadoopSink()
#db.query("""SELECT * FROM contest.contest_messages c LIMIT 0,1000""")
#db.query("""SELECT id, type, timestamp, json, response_time, response_id FROM contest.contest_messages c \
#WHERE type = 'impression' AND id > 1500004 LIMIT 5""")
db.query("""SELECT id, type, timestamp, json, response_time, response_id FROM contest.contest_messages c \
WHERE ( type = 'impression' ) AND id > 1000000 LIMIT 10 """)
r=db.use_result()
""" what happens if there is a timestamp collison? It doesn't matter if we don't try to count with the timestamp
"""
replay_time = time2.time()
result = r.fetch_row()