def main():
scan_cursor = 0
count = 0
bulk_action = []
number = r.scard('user_set')
print number
if RUN_TYPE:
ts = time.time() - DAY
date = ts2datetime(ts)
start_time = str(ts2datetime(time.time()))
print "/cron/push_mid2redis.py&start&%s" %start_time
else:
date = '2013-09-05'
index_name = flow_text_index_name_pre+date
print index_name
ts = time.time()
while 1:
re_scan = r.sscan("user_set", scan_cursor, count=3000)
scan_cursor = re_scan[0]
uid_list = re_scan[1] #具体数据
if len(uid_list):
for uid in uid_list:
detail_dict = r.hgetall(uid)
for k,v in detail_dict.iteritems():
update_dict = dict()
if "_origin_weibo_retweeted" in k and v:
mid = k.split('_')[0]
update_dict["retweeted"] = int(v)
elif "_origin_weibo_comment" in k and v:
mid = k.split('_')[0]
update_dict["comment"] = int(v)
elif '_retweeted_weibo_comment' in k and v:
mid = k.split('_')[0]
update_dict["comment"] = int(v)
elif '_retweeted_weibo_retweeted' in k and v:
mid = k.split('_')[0]
update_dict["retweeted"] = int(v)
else:
pass
if update_dict:
action = {"update": {"_id": mid}}
xdata = {"doc": update_dict}
bulk_action.extend([action, xdata])
count += 1
if count % 400 == 0:
r_flow.lpush('update_mid_list', json.dumps(bulk_action))
bulk_action = []
tp = time.time()
#print "%s cost %s" %(count, tp-ts)
ts = tp
if int(scan_cursor) == 0:
break
if bulk_action:
r_flow.lpush('update_mid_list', json.dumps(bulk_action))
print count
def main():
scan_cursor = 0
count = 0
bulk_action = []
number = r.scard('user_set')
print number
if RUN_TYPE:
ts = time.time() - DAY
date = ts2datetime(ts)
else:
date = '2013-09-05'
index_name = flow_text_index_name_pre + date
ts = time.time()
while 1:
re_scan = r.sscan("user_set", scan_cursor, count=3000)
scan_cursor = re_scan[0]
uid_list = re_scan[1] #具体数据
if len(uid_list):
for uid in uid_list:
detail_dict = r.hgetall(uid)
for k, v in detail_dict.iteritems():
update_dict = dict()
if "_origin_weibo_retweeted" in k and int(v):
mid = k.split('_')[0]
update_dict["retweeted"] = int(v)
elif "_origin_weibo_comment" in k and int(v):
mid = k.split('_')[0]
update_dict["comment"] = int(v)
else:
pass
if update_dict:
action = {"update": {"_id": mid}}
xdata = {"doc": update_dict}
bulk_action.extend([action, xdata])
count += 1
if count % 1000 == 0:
#print bulk_action
r_flow.lpush('update_mid_list',
json.dumps(bulk_action))
bulk_action = []
tp = time.time()
print "%s cost %s" % (count, tp - ts)
ts = tp
if int(scan_cursor) == 0:
break
if bulk_action:
r_flow.lpush('update_mid_list', json.dumps(bulk_action))
print count
def scan_offline_task():
query = {
"query": {
"bool": {
"must": [{
"term": {
"status": 0
}
}]
}
},
"size": 1000
}
results = es_user_portrait.search(index=USER_RANK_KEYWORD_TASK_INDEX,
doc_type=USER_RANK_KEYWORD_TASK_TYPE,
body=query)['hits']['hits']
if results:
for item in results:
task_id = item['_id']
iter_item = item['_source']
search_type = iter_item['search_type']
pre = iter_item['pre']
during = iter_item['during']
start_time = iter_item['start_time']
keyword = json.loads(iter_item['keyword'])
search_key = iter_item['user_ts']
number = iter_item['number']
sort_norm = iter_item['sort_norm']
sort_scope = iter_item['sort_scope']
time = iter_item['time']
isall = iter_item['isall']
redis_task.lpush(
"task_user_rank",
json.dumps([
task_id, search_type, pre, during, start_time, keyword,
search_key, sort_norm, sort_scope, time, isall, number
]))
iter_item['status'] = -1
task_id = item['_id']
#print item
es_user_portrait.index(index=USER_RANK_KEYWORD_TASK_INDEX,
doc_type=USER_RANK_KEYWORD_TASK_TYPE,
id=task_id,
body=iter_item)
def scan_offline_task():
query = {"query":{"bool":{"must":[{"term":{"status":-1}}]}},"size":1000}
results = es_user_portrait.search(index = USER_RANK_KEYWORD_TASK_INDEX , doc_type = USER_RANK_KEYWORD_TASK_TYPE,body=query)['hits']['hits']
if results :
for item in results:
task_id = item['_id']
iter_item = item['_source']
search_type = iter_item['search_type']
pre = iter_item['pre']
during = iter_item['during']
start_time = iter_item['start_time']
keyword = json.loads(iter_item['keyword'])
search_key = iter_item['user_ts']
number = iter_item['number']
sort_norm = iter_item['sort_norm']
sort_scope = iter_item['sort_scope']
time = iter_item['time']
isall = iter_item['isall']
redis_task.lpush("task_user_rank", json.dumps([task_id, search_type , pre , during , start_time , keyword , search_key , sort_norm , sort_scope ,time , isall, number]))
iter_item['status'] = -1
task_id = item['_id']
#print item
es_user_portrait.index(index=USER_RANK_KEYWORD_TASK_INDEX, doc_type=USER_RANK_KEYWORD_TASK_TYPE, id=task_id, body=iter_item)
def get_temporal_rank(timestamp):
index = get_queue_index(timestamp)
index_ts = "influence_timestamp_" + str(index)
uid_list = r.zrange(index_ts, 0, 10000, desc=True)
user_info = []
in_portrait = [] # 入库
if uid_list:
search_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={"ids":uid_list}, field=SOCIAL_SENSOR_INFO)["docs"]
for item in search_result:
if item["found"]:
temp = []
in_portrait.append(item['_id'])
for iter_key in SOCIAL_SENSOR_INFO:
"""
"""
放弃原先设想的采用redis cluster方案，而使用单台redis形式
"""
import sys
import redis
from redis import StrictRedis
reload(sys)
sys.path.append('../../')
from global_utils import R_CLUSTER_FLOW1 as r
if __name__ == '__main__':
"""
startup_nodes = [{"host": '219.224.135.91', "port": "6379"}]
weibo_redis = RedisCluster(startup_nodes = startup_nodes)
weibo_redis.flushall()
startup_nodes = [{"host": '219.224.135.91', "port": "6380"}]
weibo_redis = RedisCluster(startup_nodes = startup_nodes)
weibo_redis.flushall()
startup_nodes = [{"host": '219.224.135.93', "port": "6380"}]
weibo_redis = RedisCluster(startup_nodes = startup_nodes)
weibo_redis.flushall()
print "finish flushing!"
"""
r.flushdb()
"should":[
]
}
}
}
},
"size": 10000
}
if __name__ == "__main__":
scan_cursor = 0
sensitive_uid_list = []
count = 0
while 1:
re_scan = r_cluster.sscan('s_user_set', scan_cursor, count=10000)
if int(re_scan[0]) == 0:
sensitive_uid_list.extend(re_scan[1])
count += len(re_scan[1])
print count
break
else:
sensitive_uid_list.extend(re_scan[1])
count += 10000
scan_cursor = re_scan[0]
temp_list = sensitive_uid_list
count = 0
patition = 100
number = int(math.ceil(len(temp_list)/float(100)))
print number
number = iter_item['number']
sort_norm = iter_item['sort_norm']
sort_scope = iter_item['sort_scope']
time = iter_item['time']
isall = iter_item['isall']
redis_task.lpush("task_user_rank", json.dumps([task_id, search_type , pre , during , start_time , keyword , search_key , sort_norm , sort_scope ,time , isall, number]))
iter_item['status'] = -1
task_id = item['_id']
#print item
es_user_portrait.index(index=USER_RANK_KEYWORD_TASK_INDEX, doc_type=USER_RANK_KEYWORD_TASK_TYPE, id=task_id, body=iter_item)
def cron_task(data):
key_words_search(data[0], data[1], data[2], data[3], data[4], data[5], data[6], data[7], data[8], data[9], data[10], data[11])
if __name__ == "__main__":
scan_offline_task()
while 1:
data = redis_task.rpop("task_user_rank")
print data
#"""
if data:
cron_task(json.loads(data))
else:
break
#"""
json.dumps([
task_id, search_type, pre, during, start_time, keyword,
search_key, sort_norm, sort_scope, time, isall, number
]))
iter_item['status'] = -1
task_id = item['_id']
#print item
es_user_portrait.index(index=USER_RANK_KEYWORD_TASK_INDEX,
doc_type=USER_RANK_KEYWORD_TASK_TYPE,
id=task_id,
body=iter_item)
def cron_task(data):
key_words_search(data[0], data[1], data[2], data[3], data[4], data[5],
data[6], data[7], data[8], data[9], data[10], data[11])
if __name__ == "__main__":
scan_offline_task()
while 1:
data = redis_task.rpop("task_user_rank")
print data
#"""
if data:
cron_task(json.loads(data))
else:
break
#"""
return int(index)
if __name__ == "__main__":
now_ts = time.time()
date_ts = datetime2ts(ts2datetime(now_ts))
if now_ts - TIME_INTERVAL < date_ts:
sys.exit(0)
tmp_date = ts2date(now_ts)
print "cron_influence_start_" + tmp_date
index = get_queue_index(now_ts) #当前时间戳所对应的时间区间
influence_ts = "influence_timestamp_" + str(index)
scan_cursor = 0
count = 0
while 1:
re_scan = r.hscan(influence_ts, scan_cursor, count=1000)
scan_cursor = re_scan[0]
detail = re_scan[1]
if len(detail):
for k,v in detail.iteritems():
r.zadd(influence_ts, v, k)
count += 1
if int(scan_cursor) == 0:
break
tmp_date = ts2date(time.time())
print count
print "cron_influence_end_" + tmp_date
