def get_evaluate_rank(evaluate_ts, evaluate_value, evaluate_index):
result = []
evaluate_index_key = evaluate_index + '_' + str(evaluate_ts)
query_body = {
'query': {
'range': {
evaluate_index_key: {
'gte': evaluate_value,
'lt': MAX_VALUE
}
}
}
}
#get index_name, index_type
index_infor_item = evaluate_index_dict[evaluate_index]
index_name = index_infor_item[0]
index_type = index_infor_item[1]
evaluate_rank = ES_COPY_USER_PORTRAIT.count(index=index_name,
doc_type=index_type,
body=query_body)
if evaluate_rank['_shards']['successful'] != 0:
rank = evaluate_rank['count']
else:
rank = ''
return rank
def new_get_activeness_trend(uid, time_segment):
results = {}
try:
activeness_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_ACTIVENESS, doc_type=COPY_USER_PORTRAIT_ACTIVENESS_TYPE,\
id=uid)['_source']
except:
activeness_history = {}
if activeness_history:
results = get_evaluate_trend(activeness_history, 'activeness')
else:
results = {}
#deal results for situation---server power off
new_time_list = []
new_count_list = []
new_results = {}
now_time_ts = time.time()
now_date_ts = datetime2ts(ts2datetime(now_time_ts))
for i in range(time_segment, 0, -1):
iter_date_ts = now_date_ts - i * DAY
try:
date_count = results[iter_date_ts]
except:
date_count = 0
new_time_list.append(iter_date_ts)
new_count_list.append(date_count)
new_results = {'timeline': new_time_list, 'evaluate_index': new_count_list}
return new_results
def new_get_influence_trend(uid, time_segment):
results = {}
try:
influence_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE,\
id=uid)['_source']
print ES_COPY_USER_PORTRAIT, COPY_USER_PORTRAIT_INFLUENCE, COPY_USER_PORTRAIT_INFLUENCE_TYPE, uid
print influence_history
except:
influence_history = {}
if influence_history:
results = get_evaluate_trend(influence_history, 'bci')
else:
results = {}
print results
#deal results for situation---server power off
new_time_list = []
new_count_list = []
new_results = {}
now_time_ts = time.time()
now_date_ts = datetime2ts(ts2datetime(now_time_ts))
if RUN_TYPE == 0:
now_date_ts = datetime2ts(RUN_TEST_TIME)
for i in range(time_segment, 0, -1):
iter_date_ts = now_date_ts - i * DAY
try:
date_count = results[iter_date_ts]
except:
date_count = 0
new_time_list.append(iter_date_ts)
new_count_list.append(date_count)
new_results = {'timeline': new_time_list, 'evaluate_index': new_count_list}
return new_results
def new_get_activeness_trend(uid, time_segment):
results = {}
try:
activeness_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_ACTIVENESS, doc_type=COPY_USER_PORTRAIT_ACTIVENESS_TYPE,\
id=uid)['_source']
except:
activeness_history = {}
if activeness_history:
results = get_evaluate_trend(activeness_history, 'activeness')
else:
results = {}
#deal results for situation---server power off
new_time_list = []
new_count_list = []
new_results = {}
now_time_ts = time.time()
now_date_ts = datetime2ts(ts2datetime(now_time_ts))
for i in range(time_segment, 0, -1):
iter_date_ts = now_date_ts - i * DAY
try:
date_count = results[iter_date_ts]
except:
date_count = 0
new_time_list.append(iter_date_ts)
new_count_list.append(date_count)
new_results = {'timeline': new_time_list, 'evaluate_index': new_count_list}
return new_results
def new_get_activeness_trend(uid):
results = {}
try:
activeness_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_ACTIVENESS, doc_type=COPY_USER_PORTRAIT_ACTIVENESS_TYPE,\
id=uid)['_source']
except:
activeness_history = {}
if activeness_history:
results = get_evaluate_trend(activeness_history, 'activeness')
else:
results = {}
return results
def new_get_influence_trend(uid):
results = {}
try:
influence_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE,\
id=uid)['_source']
except:
influence_history = {}
if influence_history:
results = get_evaluate_trend(influence_history, 'bci')
else:
results = {}
return results
def new_get_activeness_trend(uid):
results = {}
try:
activeness_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_ACTIVENESS, doc_type=COPY_USER_PORTRAIT_ACTIVENESS_TYPE,\
id=uid)['_source']
except:
activeness_history = {}
if activeness_history:
results = get_evaluate_trend(activeness_history, 'activeness')
else:
results = {}
return results
def new_get_influence_trend(uid):
results = {}
try:
influence_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE,\
id=uid)['_source']
except:
influence_history = {}
if influence_history:
results = get_evaluate_trend(influence_history, 'bci')
else:
results = {}
return results
def get_influence_week_ave_rank(week_ave):
evaluate_index_key = 'bci_week_ave'
query_body = {
'query':{
'range':{
evaluate_index_key: {
'gte': week_ave,
'lt': MAX_VALUE
}
}
}
}
index_name = COPY_USER_PORTRAIT_INFLUENCE
index_type = COPY_USER_PORTRAIT_INFLUENCE_TYPE
week_ave_rank = ES_COPY_USER_PORTRAIT.count(index=index_name, doc_type=index_type,\
body=query_body)
if week_ave_rank['_shards']['successful'] != 0:
rank = week_ave_rank['count']
else:
rank = ''
return rank
def get_influence_week_ave_rank(week_ave):
evaluate_index_key = 'bci_week_ave'
query_body = {
'query':{
'range':{
evaluate_index_key: {
'gte': week_ave,
'lt': MAX_VALUE
}
}
}
}
index_name = COPY_USER_PORTRAIT_INFLUENCE
index_type = COPY_USER_PORTRAIT_INFLUENCE_TYPE
week_ave_rank = ES_COPY_USER_PORTRAIT.count(index=index_name, doc_type=index_type,\
body=query_body)
if week_ave_rank['_shards']['successful'] != 0:
rank = week_ave_rank['count']
else:
rank = ''
return rank
def get_evaluate_rank(evaluate_ts, evaluate_value, evaluate_index):
result = []
evaluate_index_key = evaluate_index + '_' + str(evaluate_ts)
query_body = {
'query':{
'range':{
evaluate_index_key:{
'gte': evaluate_value,
'lt': MAX_VALUE
}
}
}
}
#get index_name, index_type
index_infor_item = evaluate_index_dict[evaluate_index]
index_name = index_infor_item[0]
index_type = index_infor_item[1]
evaluate_rank = ES_COPY_USER_PORTRAIT.count(index=index_name, doc_type=index_type, body=query_body)
if evaluate_rank['_shards']['successful'] != 0:
rank = evaluate_rank['count']
else:
rank = ''
return rank
def new_get_user_evaluate(uid):
results = {}
#get all count in user_portrait
query_body = {
'query':{
'match_all': {}
}
}
all_count_results = es_user_portrait.count(index=portrait_index_name, doc_type=portrait_index_type, body=query_body)
if all_count_results['_shards']['successful'] != 0:
all_count = all_count_results['count']
else:
all_count = ''
#get influence from es influence history
try:
influence_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE, \
id = uid)['_source']
except:
influence_history = []
#get max value/min value/week ave value
if influence_history:
week_ave = influence_history['bci_week_ave']
week_ave_rank = get_influence_week_ave_rank(week_ave)
influence_item = [week_ave, week_ave_rank]
influence_max_min_now_list = get_evaluate_max_min_now(influence_history, 'bci')
influence_max_min_now_list.append(all_count)
influence_item.extend(influence_max_min_now_list[2:])
results['influence'] = influence_max_min_now_list
else:
results['influence'] = ['', '', '', '', all_count]
#get importance from es importance history
try:
importance_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_IMPORTANCE, doc_type=COPY_USER_PORTRAIT_IMPORTANCE_TYPE, \
id = uid)['_source']
except:
importance_history = []
#get max value/min value/now value
if importance_history:
importance_max_min_now_list = get_evaluate_max_min_now(importance_history, 'importance')
importance_max_min_now_list.append(all_count)
results['importance'] = importance_max_min_now_list
else:
results['importance'] = ['', '', '', '', all_count]
#get activeness from es activeness history
try:
activeness_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_ACTIVENESS, doc_type=COPY_USER_PORTRAIT_ACTIVENESS_TYPE ,\
id = uid)['_source']
except:
activeness_history = []
#get max value/min value/ now value
if activeness_history:
activeness_max_min_now_list = get_evaluate_max_min_now(activeness_history, 'activeness')
activeness_max_min_now_list.append(all_count)
results['activeness'] = activeness_max_min_now_list
else:
results['activeness'] = ['', '', '', '', all_count]
#get sensitive from es sensitive history
try:
sensitive_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_SENSITIVE, doc_type=COPY_USER_PORTRAIT_SENSITIVE_TYPE, \
id = uid)['_source']
except:
sensitive_history = []
#get max value/min value/ now value
if sensitive_history:
sensitive_max_min_now_list = get_evaluate_max_min_now(sensitive_history, 'sensitive')
sensitive_max_min_now_list.append(all_count)
results['sensitive'] = sensitive_max_min_now_list
else:
results['sensitive'] = ['', '', '', '', all_count]
return results
def new_get_user_evaluate(uid):
results = {}
#get all count in user_portrait
query_body = {
'query':{
'match_all': {}
}
}
all_count_results = es_user_portrait.count(index=portrait_index_name, doc_type=portrait_index_type, body=query_body)
if all_count_results['_shards']['successful'] != 0:
all_count = all_count_results['count']
else:
all_count = ''
#get influence from es influence history
try:
influence_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_INFLUENCE, doc_type=COPY_USER_PORTRAIT_INFLUENCE_TYPE, \
id = uid)['_source']
except:
influence_history = []
#get max value/min value/week ave value
if influence_history:
week_ave = influence_history['bci_week_ave']
week_ave_rank = get_influence_week_ave_rank(week_ave)
influence_item = [week_ave, week_ave_rank]
influence_max_min_now_list = get_evaluate_max_min_now(influence_history, 'bci')
influence_max_min_now_list.append(all_count)
influence_item.extend(influence_max_min_now_list[2:])
results['influence'] = influence_max_min_now_list
else:
results['influence'] = ['', '', '', '', all_count]
#get importance from es importance history
try:
importance_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_IMPORTANCE, doc_type=COPY_USER_PORTRAIT_IMPORTANCE_TYPE, \
id = uid)['_source']
except:
importance_history = []
#get max value/min value/now value
if importance_history:
importance_max_min_now_list = get_evaluate_max_min_now(importance_history, 'importance')
importance_max_min_now_list.append(all_count)
results['importance'] = importance_max_min_now_list
else:
results['importance'] = ['', '', '', '', all_count]
#get activeness from es activeness history
try:
activeness_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_ACTIVENESS, doc_type=COPY_USER_PORTRAIT_ACTIVENESS_TYPE ,\
id = uid)['_source']
except:
activeness_history = []
#get max value/min value/ now value
if activeness_history:
activeness_max_min_now_list = get_evaluate_max_min_now(activeness_history, 'activeness')
activeness_max_min_now_list.append(all_count)
results['activeness'] = activeness_max_min_now_list
else:
results['activeness'] = ['', '', '', '', all_count]
#get sensitive from es sensitive history
try:
sensitive_history = ES_COPY_USER_PORTRAIT.get(index=COPY_USER_PORTRAIT_SENSITIVE, doc_type=COPY_USER_PORTRAIT_SENSITIVE_TYPE, \
id = uid)['_source']
except:
sensitive_history = []
#get max value/min value/ now value
if sensitive_history:
sensitive_max_min_now_list = get_evaluate_max_min_now(sensitive_history, 'sensitive')
sensitive_max_min_now_list.append(all_count)
results['sensitive'] = sensitive_max_min_now_list
else:
results['sensitive'] = ['', '', '', '', all_count]
return results