def scan_compute_redis():
hash_name = 'compute'
results = r.hgetall('compute')
iter_user_list = []
mapping_dict = dict()
for uid in results:
user_list = json.loads(results[uid])
in_date = user_list[0]
status = user_list[1]
if status == '2':
iter_user_list.append(uid)
mapping_dict[uid] = json.dumps([in_date, '3']) # mark status:3 computing
#revise identify_in_date
influence_hashname = 'identify_in_influence_'+str(in_date)
sensitive_hashname = 'identify_in_sensitive_'+str(in_date)
tmp = r.hget(influence_hashname, uid)
if tmp:
r.hset(influence_hashname, uid, '3')
else:
r.hset(sensitive_hashname, uid, '3')
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
#mark status from 1 to 3 as identify_compute to computing
r.hmset('compute', mapping_dict)
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
#deal user no weibo to compute portrait attribute
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
change_mapping_dict[change_user] = json.dumps([in_date, '2'])
r.hmset(change_mapping_dict)
iter_user_list = []
mapping_dict = {}
if iter_user_list != [] and mapping_dict != {}:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo date
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
#deal user no weibo to compute portrait attribute
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
change_mapping_dict[change_user] = json.dumps([in_date, '2'])
r.hmset(change_mapping_dict)
def deal_bulk_action(user_info_list, fansnum_max):
start_ts = time.time()
uid_list = user_info_list.keys()
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(uid_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(uid_list)
#compute attribute--keywords, topic, online_pattern
#get user topic results by bulk action
topic_results_dict, topic_results_label = topic_classfiy(uid_list, user_keywords_dict)
#get bulk action
bulk_action = []
for uid in uid_list:
results = {}
results['uid'] = uid
#add user topic attribute
user_topic_dict = topic_results_dict[uid]
user_label_dict = topic_results_label[uid]
results['topic'] = json.dumps(user_topic_dict)
results['topic_string'] = topic_en2ch(user_label_dict)
#add user keywords attribute
keywords_dict = user_keywords_dict[uid]
keywords_top50 = sorted(keywords_dict.items(), key=lambda x:x[1], reverse=True)[:50]
keywords_top50_string = '&'.join([keyword_item[0] for keyword_item in keywords_top50])
results['keywords'] = json.dumps(keywords_top50)
results['keywords_string'] = keywords_top50_string
#add online_pattern
user_online_pattern = json.dumps(online_pattern_dict[uid])
results['online_pattern'] = user_online_pattern
try:
results['online_pattern_aggs'] = '&'.join(user_online_pattern.keys())
except:
results['online_pattern_aggs'] = ''
#add user importance
user_domain = user_info_list[uid]['domain'].encode('utf-8')
user_fansnum = user_info_list[uid]['fansnum']
results['importance'] = get_importance(user_domain, results['topic_string'], user_fansnum, fansnum_max)
#bulk action
action = {'update':{'_id': uid}}
bulk_action.extend([action, {'doc': results}])
es_user_portrait.bulk(bulk_action, index=portrait_index_name, doc_type=portrait_index_type)
end_ts = time.time()
#log_should_delete
#print '%s sec count %s' % (end_ts - start_ts, len(uid_list))
#log_should_delete
start_ts = end_ts
def scan_compute_redis():
hash_name = 'compute'
results = r.hgetall('compute')
iter_user_list = []
mapping_dict = dict()
for uid in results:
user_list = json.loads(results[uid])
in_date = user_list[0]
status = user_list[1]
if status == '2': #imme
iter_user_list.append(uid)
mapping_dict[uid] = json.dumps([in_date, '3']) # mark status:3 computing
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
iter_user_list = []
mapping_dict = {}
if iter_user_list != [] and mapping_dict != {}:
r.mset('compute', mapping_dict)
#acquire bulk user weibo date
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
def scan_compute_redis():
iter_user_list = []
mapping_dict = dict()
#test
count = 0
while 1:
uid = r.rpop("uid_list") #用户列表
print uid
count += 1
if not uid:
break
iter_user_list.append(uid)
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
#acquire bulk user weibo data
out_list = es_km_storage(iter_uid_list)
if out_list:
iter_uid_list = out_list
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(
user_keywords_dict, user_weibo_dict, online_pattern_dict,
character_start_ts)
if compute_status == True:
print "finish iteration"
else:
for uid in iter_user_list:
r.lpush("uid_list", uid)
#when uid user no weibo at latest week to change compute status to 1
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(
user_keywords_dict.keys())
for change_user in change_user_list:
r.lpush("uid_list", change_user)
iter_user_list = []
mapping_dict = {}
if iter_user_list != []:
#acquire bulk user weibo date
print 'iter_user_list:', len(iter_user_list)
out_list = es_km_storage(iter_user_list)
iter_user_list = out_list
if iter_user_list:
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_user_list)
#compute text attribute
print 'user_weibo_dict:', len(user_weibo_dict)
compute_status = test_cron_text_attribute_v2(
user_keywords_dict, user_weibo_dict, online_pattern_dict,
character_start_ts)
if compute_status == True:
print "finish iteration"
else:
for uid in iter_user_list:
r.lpush("uid_list", uid)
#when uid user no weibo at latest week to change compute status to 1
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(
user_keywords_dict.keys())
for change_user in change_user_list:
r.lpush("uid_list", change_user)
def scan_compute_redis():
hash_name = 'compute'
results = r.hgetall('compute')
iter_user_list = []
mapping_dict = dict()
#test
count = 0
for uid in results:
user_list = json.loads(results[uid])
in_date = user_list[0]
status = user_list[1]
if status == '1': #imme
#test
count += 1
iter_user_list.append(uid)
mapping_dict[uid] = json.dumps([in_date, '3']) # mark status:3 computing
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
#when uid user no weibo at latest week to change compute status to 1
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
change_mapping_dict[change_user] = json.dumps([in_date, '1'])
r.hmset('compute', change_mapping_dict)
iter_user_list = []
mapping_dict = {}
if iter_user_list != [] and mapping_dict != {}:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo date
print 'iter_user_list:', len(iter_user_list)
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_user_list)
#compute text attribute
print 'user_weibo_dict:', len(user_weibo_dict)
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
#when uid user no weibo at latest week to change compute status to 1
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
change_mapping_dict[change_user] = json.dumps([in_date, '1'])
r.hmset('compute', change_mapping_dict)
def scan_compute_redis():
hash_name = 'compute'
results = r.hgetall('compute')
iter_user_list = []
mapping_dict = dict()
for uid in results:
user_list = json.loads(results[uid])
in_date = user_list[0]
status = user_list[1]
if status == '2':
iter_user_list.append(uid)
mapping_dict[uid] = json.dumps([in_date,
'3']) # mark status:3 computing
#revise identify_in_date
influence_hashname = 'identify_in_influence_' + str(in_date)
sensitive_hashname = 'identify_in_sensitive_' + str(in_date)
manual_hashname = "identify_in_manual_" + str(in_date)
tmp = r.hget(influence_hashname, uid)
tmp1 = r.hget(sensitive_hashname, uid)
if tmp:
r.hset(influence_hashname, uid, '3')
elif tmp1:
r.hset(sensitive_hashname, uid, '3')
else:
r.hset(manual_hashname, uid, '3')
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
#mark status from 1 to 3 as identify_compute to computing
r.hmset('compute', mapping_dict)
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(
user_keywords_dict, user_weibo_dict, online_pattern_dict,
character_start_ts)
if compute_status == True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
#deal user no weibo to compute portrait attribute
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(
user_keywords_dict.keys())
for change_user in change_user_list:
change_mapping_dict[change_user] = json.dumps(
[in_date, '2'])
r.hmset(change_mapping_dict)
iter_user_list = []
mapping_dict = {}
if iter_user_list != [] and mapping_dict != {}:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo date
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict,
user_weibo_dict,
online_pattern_dict,
character_start_ts)
if compute_status == True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
#deal user no weibo to compute portrait attribute
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(
user_keywords_dict.keys())
for change_user in change_user_list:
change_mapping_dict[change_user] = json.dumps([in_date, '2'])
r.hmset(change_mapping_dict)
def scan_compute_redis():
hash_name = 'compute'
results = r.hgetall('compute')
iter_user_list = []
mapping_dict = dict()
#test
count = 0
for uid in results:
user_list = json.loads(results[uid])
in_date = user_list[0]
status = user_list[1]
if status == '2': #imme
#test
count += 1
if count >= 3:
break
iter_user_list.append(uid)
mapping_dict[uid] = json.dumps([in_date,
'3']) # mark status:3 computing
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(
user_keywords_dict, user_weibo_dict, online_pattern_dict,
character_start_ts)
if compute_status == True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
iter_user_list = []
mapping_dict = {}
if iter_user_list != [] and mapping_dict != {}:
r.hmset('compute', mapping_dict)
#acquire bulk user weibo date
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_user_list)
#compute text attribute
compute_status = test_cron_text_attribute_v2(user_keywords_dict,
user_weibo_dict,
online_pattern_dict,
character_start_ts)
if compute_status == True:
change_status_computed(mapping_dict)
else:
change_status_compute_fail(mapping_dict)
def scan_compute_redis():
in_portrait_list = []
new_portrait_list = []
non_portrait_list = []
task_detail = r.rpop("user_portrait_task")
if not task_detail:
sys.exit(0)
task_detail = json.loads(task_detail)
task_name = task_detail[0]
task_time = task_detail[1]
task_uid_list = task_detail[2]
iter_user_list = []
mapping_dict = dict()
#test
count = 0
for uid in task_uid_list:
count += 1
iter_user_list.append(uid)
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
#acquire bulk user weibo data
in_list, out_list = es_km_storage(iter_uid_list)
in_portrait_list.extend(in_list)
if out_list:
iter_uid_list = out_list
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(iter_uid_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(iter_uid_list)
#compute text attribute
iter_in_list = user_keywords_dict.keys()
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
new_portrait_list.extend(iter_in_list)
print "finish iteration"
non_in = list(set(iter_uid_list) - set(iter_in_list))
non_portrait_list.extend(non_in)
else:
non_portrait_list.extend(iter_in_list)
#when uid user no weibo at latest week to change compute status to 1
"""
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
r.lpush("uid_list",change_user)
"""
iter_user_list = []
mapping_dict = {}
if iter_user_list != []:
#acquire bulk user weibo date
print 'iter_user_list:', len(iter_user_list)
in_list, out_list = es_km_storage(iter_user_list)
in_portrait_list.extend(in_list)
iter_user_list = out_list
if iter_user_list:
print iter_user_list[0][0], type(iter_user_list)
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts, filter_keywords_dict = read_flow_text_sentiment(iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts,filter_keywords_dict = read_flow_text(iter_user_list)
#compute text attribute
print 'user_weibo_dict:', len(user_weibo_dict)
iter_in_list = user_keywords_dict.keys()
compute_status = test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts)
if compute_status==True:
new_portrait_list.extend(iter_in_list)
print "finish iteration"
non_in = list(set(iter_user_list) - set(iter_in_list))
non_portrait_list.extend(non_in)
else:
non_portrait_list.extend(iter_in_list)
#when uid user no weibo at latest week to change compute status to 1
"""
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
r.lpush("uid_list",change_user)
"""
results = dict()
results["task_name"] = task_name
results["task_time"] = task_time
results["in_portrait_list"] = json.dumps(in_portrait_list)
results["new_in_list"] = json.dumps(new_portrait_list)
results["not_in_list"] = json.dumps(non_portrait_list)
es_km.index(index="user_portrait_task_results", doc_type="user", id=task_name, body=results)
try:
es_km.update(index="user_status", doc_type="user", id=task_name, body={"doc":{"status": "2"}})["_source"]
except Exception:
print Exception
def scan_compute_redis():
in_portrait_list = []
new_portrait_list = []
non_portrait_list = []
task_detail = r.rpop("user_portrait_task")
if not task_detail:
sys.exit(0)
task_detail = json.loads(task_detail)
task_name = task_detail[0]
task_time = task_detail[1]
task_uid_list = task_detail[2]
iter_user_list = []
mapping_dict = dict()
#test
count = 0
for uid in task_uid_list:
count += 1
iter_user_list.append(uid)
if len(iter_user_list) % 100 == 0 and len(iter_user_list) != 0:
#acquire bulk user weibo data
in_list, out_list = es_km_storage(iter_uid_list)
in_portrait_list.extend(in_list)
if out_list:
iter_uid_list = out_list
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(
iter_uid_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(
iter_uid_list)
#compute text attribute
iter_in_list = user_keywords_dict.keys()
compute_status = test_cron_text_attribute_v2(
user_keywords_dict, user_weibo_dict, online_pattern_dict,
character_start_ts)
if compute_status == True:
new_portrait_list.extend(iter_in_list)
print "finish iteration"
non_in = list(set(iter_uid_list) - set(iter_in_list))
non_portrait_list.extend(non_in)
else:
non_portrait_list.extend(iter_in_list)
#when uid user no weibo at latest week to change compute status to 1
"""
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
r.lpush("uid_list",change_user)
"""
iter_user_list = []
mapping_dict = {}
if iter_user_list != []:
#acquire bulk user weibo date
print 'iter_user_list:', len(iter_user_list)
in_list, out_list = es_km_storage(iter_user_list)
in_portrait_list.extend(in_list)
iter_user_list = out_list
if iter_user_list:
print iter_user_list[0][0], type(iter_user_list)
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts, filter_keywords_dict = read_flow_text_sentiment(
iter_user_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts, filter_keywords_dict = read_flow_text(
iter_user_list)
#compute text attribute
print 'user_weibo_dict:', len(user_weibo_dict)
iter_in_list = user_keywords_dict.keys()
compute_status = test_cron_text_attribute_v2(
user_keywords_dict, user_weibo_dict, online_pattern_dict,
character_start_ts)
if compute_status == True:
new_portrait_list.extend(iter_in_list)
print "finish iteration"
non_in = list(set(iter_user_list) - set(iter_in_list))
non_portrait_list.extend(non_in)
else:
non_portrait_list.extend(iter_in_list)
#when uid user no weibo at latest week to change compute status to 1
"""
if len(user_keywords_dict) != len(iter_user_list):
change_mapping_dict = dict()
change_user_list = set(iter_user_list) - set(user_keywords_dict.keys())
for change_user in change_user_list:
r.lpush("uid_list",change_user)
"""
results = dict()
results["task_name"] = task_name
results["task_time"] = task_time
results["in_portrait_list"] = json.dumps(in_portrait_list)
results["new_in_list"] = json.dumps(new_portrait_list)
results["not_in_list"] = json.dumps(non_portrait_list)
es_km.index(index="user_portrait_task_results",
doc_type="user",
id=task_name,
body=results)
try:
es_km.update(index="user_status",
doc_type="user",
id=task_name,
body={"doc": {
"status": "2"
}})["_source"]
except Exception:
print Exception
