def co_search(add_info, update_bci_key, former_bci_key, now_ts):
uid_list = add_info.keys()
evaluate_history_results = es_user_portrait.mget(index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE,body={'ids':uid_list})['docs']
iter_count = 0
bulk_action = []
for uid in uid_list:
item = evaluate_history_results[iter_count]
if item['found']:
user_history_item = item['_source']
#更新新的字段
user_history_item.update(add_info[uid])
user_history_item['bci_day_change'] = user_history_item[update_bci_key] - user_history_item.get(former_bci_key, 0)
user_history_item['bci_week_change'] = user_history_item[update_bci_key] - user_history_item.get('bci_week_ave', 0)
user_history_item['bci_month_change'] = user_history_item[update_bci_key] - user_history_item.get('bci_month_ave', 0)
user_history_item['bci_week_ave'], user_history_item['bci_week_var'], user_history_item['bci_week_sum'] = compute_week(user_history_item, now_ts)
user_history_item['bci_month_ave'], user_history_item['bci_month_var'], user_history_item['bci_month_sum'] = compute_month(user_history_item, now_ts)
if user_history_item[update_bci_key] < LOW_INFLUENCE_THRESHOULD:
user_history_item['low_number'] += 1
else:
user_history_item['low_number'] = 0
else:
user_history_item = dict()
user_history_item.update(add_info[uid])
user_history_item["uid"] = uid
user_history_item.update(add_info[uid])
user_history_item['bci_day_change'] = user_history_item[update_bci_key]
user_history_item['bci_week_change'] = user_history_item[update_bci_key]
user_history_item['bci_month_change'] = user_history_item[update_bci_key]
user_history_item['bci_week_ave'], user_history_item['bci_week_var'], user_history_item['bci_week_sum'] = compute_week(user_history_item, now_ts)
user_history_item['bci_month_ave'], user_history_item['bci_month_var'], user_history_item['bci_month_sum'] = compute_month(user_history_item, now_ts)
if user_history_item[update_bci_key] < LOW_INFLUENCE_THRESHOULD:
user_history_item['low_number'] = 1
iter_count += 1
try:
user_history_item.pop(del_bci_key)
except:
pass
action = {'index':{'_id': uid}}
bulk_action.extend([action, user_history_item])
if bulk_action:
es_cluster.bulk(bulk_action, index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE,timeout=600)
print iter_count
def get_evaluate_trend():
#get uid list
uid_list = get_uid_list()
#save influence trend es result
f = open('/home/user_portrait_0320/revised_user_portrait/user_portrait/user_portrait/attribute/sensitive_trend.txt', 'w')
for uid in uid_list:
#try:
influence_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_SENSITIVE, doc_type=COPY_USER_PORTRAIT_SENSITIVE_TYPE, id=uid)['_source']
#except:
# influence_history = {}
if influence_history:
f.write('%s\n' % json.dumps(influence_history))
f.close()
def co_search(add_info, update_bci_key, former_bci_key, now_ts):
uid_list = add_info.keys()
evaluate_history_results = es_user_portrait.mget(index=COPY_USER_PORTRAIT_SENSITIVE, doc_type=COPY_USER_PORTRAIT_SENSITIVE_TYPE,body={'ids':uid_list})['docs']
iter_count = 0
bulk_action = []
for uid in uid_list:
item = evaluate_history_results[iter_count]
if item['found']:
user_history_item = item['_source']
#更新新的字段
user_history_item.update(add_info[uid])
user_history_item['sensitive_day_change'] = user_history_item[update_bci_key] - user_history_item.get(former_bci_key, 0)
user_history_item['sensitive_week_change'] = user_history_item[update_bci_key] - user_history_item.get('sensitive_week_ave', 0)
user_history_item['sensitive_month_change'] = user_history_item[update_bci_key] - user_history_item.get('sensitive_month_ave', 0)
user_history_item['sensitive_week_ave'], user_history_item['sensitive_week_var'], user_history_item['sensitive_week_sum'] = compute_week(user_history_item, now_ts)
user_history_item['sensitive_month_ave'], user_history_item['sensitive_month_var'], user_history_item['sensitive_month_sum'] = compute_month(user_history_item, now_ts)
else:
user_history_item = dict()
user_history_item.update(add_info[uid])
user_history_item["uid"] = uid
user_history_item.update(add_info[uid])
user_history_item['sensitive_day_change'] = user_history_item[update_bci_key]
user_history_item['sensitive_week_change'] = user_history_item[update_bci_key]
user_history_item['sensitive_month_change'] = user_history_item[update_bci_key]
user_history_item['sensitive_week_ave'], user_history_item['sensitive_week_var'], user_history_item['sensitive_week_sum'] = compute_week(user_history_item, now_ts)
user_history_item['sensitive_month_ave'], user_history_item['sensitive_month_var'], user_history_item['sensitive_month_sum'] = compute_month(user_history_item, now_ts)
iter_count += 1
try:
user_history_item.pop(del_bci_key)
except:
pass
action = {'index':{'_id': uid}}
bulk_action.extend([action, user_history_item])
if bulk_action:
es_cluster.bulk(bulk_action, index=COPY_USER_PORTRAIT_SENSITIVE, doc_type=COPY_USER_PORTRAIT_SENSITIVE_TYPE,timeout=600)
print iter_count
def get_evaluate_trend():
#get uid list
uid_list = get_uid_list()
#save influence trend es result
f = open(
'/home/user_portrait_0320/revised_user_portrait/user_portrait/user_portrait/attribute/sensitive_trend.txt',
'w')
for uid in uid_list:
#try:
influence_history = ES_COPY_USER_PORTRAIT.get(
index=COPY_USER_PORTRAIT_SENSITIVE,
doc_type=COPY_USER_PORTRAIT_SENSITIVE_TYPE,
id=uid)['_source']
#except:
# influence_history = {}
if influence_history:
f.write('%s\n' % json.dumps(influence_history))
f.close()
