def get_sort(uid,fe):
result = {}
try:
u_bci = es.get(index=BCI_INDEX_NAME, doc_type=BCI_INDEX_TYPE, id=uid,fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
#u_bci = es.get(index='user_portrait_1222', doc_type='user', id=uid,fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
result['in_score'] = u_bci
except:
result['in_score']="";
query_body={
'query':{
'filtered':{
'filter':{
'bool':{
'must':[
{'range':{'bci_week_ave':{'gte':u_bci}}},
{'term':{'topic_string':fe}}]
}
}
}
}
}
result['in_top'] = es.search(index=BCI_INDEX_NAME, doc_type=BCI_INDEX_TYPE,body=query_body)['hits']['total']
print 'essearch'
print es.search(index=BCI_INDEX_NAME, doc_type=BCI_INDEX_TYPE,body=query_body)
try:
u_bci = es.get(index='bci_history', doc_type='bci', id=uid,fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
#u_bci = es.get(index='user_portrait_1222', doc_type='user', id=uid,fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
print "trymax"
bci_max = get_max_value(es_user_profile, "bci_history", "bci")
print "max",bci_max
result['all_score'] = math.log(u_bci/float(bci_max)*9+1,10)*100
except:
result['all_score']=""
result ['all_top']=""
query_body={
'query':{
'filtered':{
'filter':{
'bool':{
'must':[
{'range':{'bci_week_ave':{'gte':u_bci}}}]
}
}
}
}
}
result['all_top'] = es.search(index='bci_history', doc_type='bci',body=query_body)['hits']['total']
#result = es.search(index='user_portrait_1222', doc_type='user',body=query_body)
# return json.dumps([result['hits']['total'],u_bci])
return json.dumps(result)
def get_uid(uname):
try:
portrait_exist_result = es_user_portrait.search(index=profile_index_name, doc_type=profile_index_type, \
body={"query":{"bool":{"must":{"term":{"nick_name":uname}}}}})['hits']['hits'][0]['_id']
except:
return None
return portrait_exist_result
def get_person_value(uid):
#认证类型
#print es_user_profile,profile_index_name,profile_index_type,uid
try:
value_static = es_bci_history.get(index = bci_history_index_name,doc_type = bci_history_index_type,id=uid)
value_inf = es_user_portrait.get(index = portrait_index_name,doc_type = portrait_index_type,id=uid)
static = es_user_profile.get(index = profile_index_name,doc_type = profile_index_type,id=uid)
except:
return 'no'
fans_max = es_bci_history.search(index = bci_history_index_name,doc_type = bci_history_index_type,body={'query':{'match_all':{}},'sort':{'user_fansnum':{'order':'desc'}},'size':1})['hits']['hits'][0]['_source']['user_fansnum']
print 'max:',fans_max
#print static['found']
if static['found']==False:
return 'no'
else:
static = static['_source']
#print "static",static
try:
ver_calue = verified_value[static['verified_type']]
except:
ver_calue = 0
#账号创建时间
times = math.ceil((time.time()-int(static['create_at']))/31536000)
#粉丝数
#person = es_user_profile.get(index = profile_index_name,doc_type = profile_index_type,id=uid)['_source']
fans_value = math.log(float(value_static['_source']['user_fansnum'])/float(fans_max)*9+1,10)
#fans_value = (math.log(static['fansnum']+1000000,100000000)-0.75)*4
#if fans_value>1:
# fans_value=1.0
influence_max = es_user_portrait.search(index = portrait_index_name,doc_type = portrait_index_type,body={'query':{'match_all':{}},'sort':{'influence':{'order':'desc'}},'size':1})['hits']['hits'][0]['_source']['influence']
influence_value = float(value_inf['_source']['influence'])/float(influence_max)
final= (ver_calue*0.1+times*0.05+fans_value+influence_value*1.2)*30
print ver_calue,times,fans_value,influence_value
return final
def get_uid(uname):
try:
portrait_exist_result = es_user_portrait.search(index=profile_index_name, doc_type=profile_index_type, \
body={"query":{"bool":{"must":{"term":{"nick_name":uname}}}}})['hits']['hits'][0]['_id']
except:
return None
return portrait_exist_result
def search_portrait(condition_num, query, sort, size):
user_result = []
index_name = portrait_index_name
index_type = portrait_index_type
if condition_num > 0:
#try:
result = es_user_portrait.search(index=index_name, doc_type=index_type, \
body={'query':{'bool':{'must':query}}, 'sort':[{sort:{'order':'desc'}}], 'size':size})['hits']['hits']
#except Exception,e:
# raise e
## print 'result:', result
else:
try:
result = es_user_portrait.search(index=index_name, doc_type=index_type, \
body={'query':{'match_all':{}}, 'sort':[{sort:{"order":"desc"}}], 'size':size})['hits']['hits']
except Exception, e:
raise e
def search_portrait(condition_num, query, sort, size):
user_result = []
index_name = portrait_index_name
index_type = portrait_index_type
if condition_num > 0:
#try:
result = es_user_portrait.search(index=index_name, doc_type=index_type, \
body={'query':{'bool':{'must':query}}, 'sort':[{sort:{'order':'desc'}}], 'size':size})['hits']['hits']
#except Exception,e:
# raise e
#print 'result:', result
else:
try:
result = es_user_portrait.search(index=index_name, doc_type=index_type, \
body={'query':{'match_all':{}}, 'sort':[{sort:{"order":"desc"}}], 'size':size})['hits']['hits']
except Exception, e:
raise e
def ajax_show_task():
# show all working task
# "0": unfinish working task
# "1": finish working task
status = request.args.get("finish", "01")
user = request.args.get('user', '')
length = len(status)
query_body = {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [{
"term": {
"create_by": user
}
}]
}
}
}
},
"sort": {
"create_at": {
"order": "desc"
}
},
"size": 10000
}
#if length == 2:
# category_list = [status[0], status[1]]
# query_body['query']['filtered']['filter']["bool"]["must"].append({"term":{"finish": category_list}})
if length == 1:
query_body['query']['filtered']['filter']['bool']['must'].append(
{"term": {
"finish": status
}})
#else:
# print "error"
try:
search_results = es.search(index=index_manage_sensing_task,
doc_type=task_doc_type,
body=query_body)['hits']['hits']
except:
search_results = []
results = []
if search_results:
for item in search_results:
item = item['_source']
history_status = json.loads(item['history_status'])
if history_status:
item['history_status'] = sorted(history_status,
key=lambda x: x,
reverse=True)
else:
item['history_status'] = []
results.append(item)
return json.dumps(results)
def get_top_influence(key):
query_body = {
"query":{
"match_all": {}
},
"sort":{key:{"order":"desc"}},
"size": 1
}
search_result = es.search(index=portrait_index_name, doc_type=portrait_index_type, body=query_body)['hits']['hits']
if search_result:
result = search_result[0]['_source'][key]
return result
def get_top_influence(key):
query_body = {
"query":{
"match_all": {}
},
"sort":{key:{"order":"desc"}},
"size": 1
}
search_result = es.search(index=portrait_index_name, doc_type=portrait_index_type, body=query_body)['hits']['hits']
if search_result:
result = search_result[0]['_source'][key]
return result
def ajax_get_group_list():
user = request.args.get('user', '')
# get all group list from group manage
results = [] #
query_body = {
"query":{
"filtered":{
"filter":{
"bool":{
"should":[
{"term": {"task_type": "analysis"}},
{"bool":{
"must":[
{"term": {"task_type": "detect"}},
{"term": {"detect_process":100}}
]
}}
],
"must":{"term": {"submit_user": user}}
}
}
}
},
"sort": {"submit_date": {"order": "desc"}},
"size": 10000
}
search_results = es.search(index=index_group_manage, doc_type=doc_type_group, body=query_body, timeout=600)['hits']['hits']
if search_results:
for item in search_results:
item = item['_source']
temp = []
temp.append(item['task_name'])
temp.append(item['submit_user'])
temp.append(item['submit_date'])
temp.append(0)
temp.append(item.get('state', ""))
try:
temp.append(json.loads(item['uid_list']))
count = len(json.loads(item['uid_list']))
temp[3] = count
except:
temp.append(item['uid_list'])
temp[3] = len(item['uid_list'])
results.append(temp)
return json.dumps(results)
def get_evaluate_max():
max_result = {}
evaluate_index = ['importance', 'influence', 'activeness', 'sensitive']
for evaluate in evaluate_index:
query_body = {
'query':{
'match_all':{}
},
'size': 1,
'sort': [{evaluate: {'order': 'desc'}}]
}
try:
result = es_user_portrait.search(index=portrait_index_name, doc_type=portrait_index_type, body=query_body)['hits']['hits']
except Exception, e:
raise e
max_evaluate = result[0]['_source'][evaluate]
max_result[evaluate] = max_evaluate
def filter_in_uname(input_dict):
input_uname = input_dict.keys()
all_count = len(input_uname)
iter_count = 0
in_portrait_result = []
while iter_count < all_count:
iter_user_list = input_uname[iter_count: iter_count+FILTER_ITER_COUNT]
try:
portrait_result = es_user_portrait.search(index=portrait_index_name, doc_type=portrait_index_type,\
body={'query':{'terms': {'uname': iter_user_list}}}, _source=False, fields=['photo_url', 'uname'])['hits']['hits']
except:
portrait_result = []
if portrait_result:
iter_in_portrait = [[item['_id'], item['uname'][0], item['photo_url'][0], input_uname[item['uname']]] for item in portrait_result]
in_portrait_result.extend(iter_in_portrait)
iter_count += FILTER_ITER_COUNT
return in_portrait_result
def ajax_show_task():
# show all working task
# "0": unfinish working task
# "1": finish working task
status = request.args.get("finish", "01")
user = request.args.get('user', '')
length = len(status)
query_body = {
"query":{
"filtered":{
"filter":{
"bool":{
"must":[
{"term":{"create_by": user}}
]
}
}
}
},
"sort": {"create_at": {"order": "desc"}},
"size": 10000
}
#if length == 2:
# category_list = [status[0], status[1]]
# query_body['query']['filtered']['filter']["bool"]["must"].append({"term":{"finish": category_list}})
if length == 1:
query_body['query']['filtered']['filter']['bool']['must'].append({"term":{"finish": status}})
#else:
# print "error"
try:
search_results = es.search(index=index_manage_sensing_task, doc_type=task_doc_type, body=query_body)['hits']['hits']
except:
search_results = []
results = []
if search_results:
for item in search_results:
item = item['_source']
history_status = json.loads(item['history_status'])
if history_status:
item['history_status'] = sorted(history_status, key=lambda x:x, reverse=True)
else:
item['history_status'] = []
results.append(item)
return json.dumps(results)
def get_max_value(es, index_name, _type):
query_body = {
"query":{
"match_all": {}
},
"sort":{'bci_week_ave':{"order":"desc"}},
"size": 1
}
max_value = 1
try:
result = es.search(index=index_name, doc_type=_type, body=query_body)['hits']['hits']
except:
result = []
if result:
max_value = result[0]['_source']['bci_week_ave']
return max_value
def get_top_all_influence(key, ts):
query_body = {
"query":{
"match_all": {}
},
"sort":{key:{"order":"desc"}},
"size": 1
}
index_name = "bci_" + ts2datetime(ts).replace('-','')
if not es.indices.exists(index=index_name):
index_name = "bci_" + ts2datetime(ts-DAY).replace('-','')
exist_es = es.indices.exists(index=index_name)
if exist_es:
search_result = es.search(index=index_name, doc_type="bci", body=query_body)['hits']['hits']
else:
search_result = {}
if search_result:
result = search_result[0]['_source'][key]
else:
result = 2000
return result
def get_evaluate_max():
max_result = {}
evaluate_index = ['importance', 'influence', 'activeness', 'sensitive']
for evaluate in evaluate_index:
query_body = {
'query': {
'match_all': {}
},
'size': 1,
'sort': [{
evaluate: {
'order': 'desc'
}
}]
}
try:
result = es_user_portrait.search(index=portrait_index_name,
doc_type=portrait_index_type,
body=query_body)['hits']['hits']
except Exception, e:
raise e
max_evaluate = result[0]['_source'][evaluate]
max_result[evaluate] = max_evaluate
def get_max_value(es, index_name, _type):
query_body = {
"query": {
"match_all": {}
},
"sort": {
'bci_week_ave': {
"order": "desc"
}
},
"size": 1
}
max_value = 1
try:
result = es.search(index=index_name, doc_type=_type,
body=query_body)['hits']['hits']
except:
result = []
if result:
max_value = result[0]['_source']['bci_week_ave']
return max_value
def get_social_topic(uid_set):
results = {}
query_body = {
'query':{
'filtered':{
'filter':{
'terms':{
'uid': list(uid_set)
}
}
}
},
'aggs':{
'all_topic':{
'terms':{'field': 'topic_string'}
}
}
}
search_result = es_user_portrait.search(index=portrait_index_name, doc_type=portrait_index_type,\
body=query_body)['aggregations']['all_topic']['buckets']
for item in search_result:
results[item['key']] = item['doc_count']
return results
def get_sort(uid, fe):
result = {}
try:
u_bci = es.get(index=BCI_INDEX_NAME,
doc_type=BCI_INDEX_TYPE,
id=uid,
fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
#u_bci = es.get(index='user_portrait_1222', doc_type='user', id=uid,fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
result['in_score'] = u_bci
except:
result['in_score'] = ""
query_body = {
'query': {
'filtered': {
'filter': {
'bool': {
'must': [{
'range': {
'bci_week_ave': {
'gte': u_bci
}
}
}, {
'term': {
'topic_string': fe
}
}]
}
}
}
}
}
result['in_top'] = es.search(index=BCI_INDEX_NAME,
doc_type=BCI_INDEX_TYPE,
body=query_body)['hits']['total']
# print 'essearch'
# print es.search(index=BCI_INDEX_NAME, doc_type=BCI_INDEX_TYPE,body=query_body)
try:
u_bci = es.get(index='bci_history',
doc_type='bci',
id=uid,
fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
#u_bci = es.get(index='user_portrait_1222', doc_type='user', id=uid,fields=['bci_week_ave'])['fields']['bci_week_ave'][0]
# print "trymax"
bci_max = get_max_value(es_user_profile, "bci_history", "bci")
# print "max",bci_max
result['all_score'] = math.log(u_bci / float(bci_max) * 9 + 1,
10) * 100
except:
result['all_score'] = ""
result['all_top'] = ""
query_body = {
'query': {
'filtered': {
'filter': {
'bool': {
'must': [{
'range': {
'bci_week_ave': {
'gte': u_bci
}
}
}]
}
}
}
}
}
result['all_top'] = es.search(index='bci_history',
doc_type='bci',
body=query_body)['hits']['total']
#result = es.search(index='user_portrait_1222', doc_type='user',body=query_body)
# return json.dumps([result['hits']['total'],u_bci])
return json.dumps(result)
def search_task(task_name, submit_date, state, status, submit_user):
results = []
query = []
condition_num = 0
if task_name:
task_name_list = task_name.split(' ')
for item in task_name_list:
query.append({'wildcard':{'task_name': '*' + item + '*'}})
condition_num += 1
if submit_date:
submit_date_ts = datetime2ts(submit_date)
submit_date_start = submit_date_ts
submit_date_end = submit_date_ts + DAY
query.append({'range':{'submit_date': {'gte': submit_date_start, 'lt': submit_date_end}}})
condition_num += 1
if state:
state_list = state.split(' ')
for item in state_list:
query.append({'wildcard':{'state': '*' + item + '*'}})
condition_num += 1
if status:
query.append({'match':{'status': status}})
condition_num += 1
if submit_user:
query.append({'term':{'submit_user': submit_user}})
condition_num += 1
print es_group_result,group_index_name,group_index_type
if condition_num > 0:
query.append({'term':{'task_type': 'analysis'}})
try:
source = es_group_result.search(
index = group_index_name,
doc_type = group_index_type,
body = {
'query':{
'bool':{
'must':query
}
},
'sort': [{'count':{'order': 'desc'}}],
'size': MAX_VALUE
}
)
except Exception as e:
raise e
else:
query.append({'term':{'task_type': 'analysis'}})
source = es.search(
index = group_index_name,
doc_type = group_index_type,
body = {
'query':{'bool':{
'must':query
}
},
'sort': [{'count': {'order': 'desc'}}],
'size': MAX_VALUE
}
)
try:
task_dict_list = source['hits']['hits']
except:
return None
result = []
for task_dict in task_dict_list:
try:
state = task_dict['_source']['state']
except:
state = ''
try:
status = task_dict['_source']['status']
except:
status = 0
#result.append([task_dict['_source']['task_name'], task_dict['_source']['submit_date'], task_dict['_source']['count'], state, status])
result.append({'task_name':task_dict['_source']['task_name'],'submit_date':ts2date(task_dict['_source']['submit_date']), 'group_count':task_dict['_source']['count'], 'status':status})
return result
def get_person_value(uid):
#认证类型
#print es_user_profile,profile_index_name,profile_index_type,uid
try:
value_static = es_bci_history.get(index=bci_history_index_name,
doc_type=bci_history_index_type,
id=uid)
value_inf = es_user_portrait.get(index=portrait_index_name,
doc_type=portrait_index_type,
id=uid)
static = es_user_profile.get(index=profile_index_name,
doc_type=profile_index_type,
id=uid)
except:
return 'no'
fans_max = es_bci_history.search(
index=bci_history_index_name,
doc_type=bci_history_index_type,
body={
'query': {
'match_all': {}
},
'sort': {
'user_fansnum': {
'order': 'desc'
}
},
'size': 1
})['hits']['hits'][0]['_source']['user_fansnum']
print 'max:', fans_max
#print static['found']
if static['found'] == False:
return 'no'
else:
static = static['_source']
#print "static",static
try:
ver_calue = verified_value[static['verified_type']]
except:
ver_calue = 0
#账号创建时间
times = math.ceil((time.time() - int(static['create_at'])) / 31536000)
#粉丝数
#person = es_user_profile.get(index = profile_index_name,doc_type = profile_index_type,id=uid)['_source']
fans_value = math.log(
float(value_static['_source']['user_fansnum']) / float(fans_max) * 9 +
1, 10)
#fans_value = (math.log(static['fansnum']+1000000,100000000)-0.75)*4
#if fans_value>1:
# fans_value=1.0
influence_max = es_user_portrait.search(
index=portrait_index_name,
doc_type=portrait_index_type,
body={
'query': {
'match_all': {}
},
'sort': {
'influence': {
'order': 'desc'
}
},
'size': 1
})['hits']['hits'][0]['_source']['influence']
influence_value = float(
value_inf['_source']['influence']) / float(influence_max)
final = (ver_calue * 0.1 + times * 0.05 + fans_value +
influence_value * 1.2) * 30
print ver_calue, times, fans_value, influence_value
return final
def ajax_get_group_list():
user = request.args.get('user', '')
# get all group list from group manage
results = [] #
query_body = {
"query": {
"filtered": {
"filter": {
"bool": {
"should": [{
"term": {
"task_type": "analysis"
}
}, {
"bool": {
"must": [{
"term": {
"task_type": "detect"
}
}, {
"term": {
"detect_process": 100
}
}]
}
}],
"must": {
"term": {
"submit_user": user
}
}
}
}
}
},
"sort": {
"submit_date": {
"order": "desc"
}
},
"size": 10000
}
search_results = es.search(index=index_group_manage,
doc_type=doc_type_group,
body=query_body,
timeout=600)['hits']['hits']
if search_results:
for item in search_results:
item = item['_source']
temp = []
temp.append(item['task_name'])
temp.append(item['submit_user'])
temp.append(item['submit_date'])
temp.append(0)
temp.append(item.get('state', ""))
try:
temp.append(json.loads(item['uid_list']))
count = len(json.loads(item['uid_list']))
temp[3] = count
except:
temp.append(item['uid_list'])
temp[3] = len(item['uid_list'])
results.append(temp)
return json.dumps(results)
def conclusion_on_influence(uid):
# test
index_name = copy_portrait_index_name
index_type = copy_portrait_index_type
total_number = es.count(index=copy_portrait_index_name, doc_type=copy_portrait_index_type)["count"]
try:
influ_result = es.get(index=index_name, doc_type=index_type, id=uid)['_source']
except:
influ_result = {}
result = [0, 0, 0, 0, 0, 0, total_number] # aver_activeness, sorted, aver_influence, sorted
return result
aver_activeness = influ_result.get("aver_activeness", 0)
aver_influence = influ_result.get("aver_influence", 0)
aver_importance = influ_result.get('aver_importance', 0)
influence_query_body = {
"query":{
"match_all": {}
},
"sort": {"aver_influence": {"order": "desc"}},
"size": 1
}
top_influence = es.search(index=copy_portrait_index_name, doc_type=copy_portrait_index_type, body=influence_query_body)['hits']['hits'][0]['sort'][0]
importance_query_body = {
"query":{
"match_all": {}
},
"sort": {"aver_importance": {"order": "desc"}},
"size": 1
}
top_importance = es.search(index=copy_portrait_index_name, doc_type=copy_portrait_index_type, body=importance_query_body)['hits']['hits'][0]['sort'][0]
activeness_query_body = {
"query":{
"match_all": {}
},
"sort": {"aver_activeness": {"order": "desc"}},
"size": 1
}
top_activeness = es.search(index=copy_portrait_index_name, doc_type=copy_portrait_index_type, body=activeness_query_body)['hits']['hits'][0]['sort'][0]
influence_query_body = {
"query": {
"filtered":{
"filter": {
"range": {
"aver_influence": {
"gt": aver_influence
}
}
}
}
}
}
activeness_query_body = {
"query": {
"filtered":{
"filter": {
"range": {
"aver_activeness": {
"gt": aver_activeness
}
}
}
}
}
}
importance_query_body = {
"query": {
"filtered":{
"filter": {
"range": {
"aver_importance": {
"gt": aver_importance
}
}
}
}
}
}
influence_count = es.count(index=copy_portrait_index_name, doc_type=copy_portrait_index_type, body=influence_query_body)['count']
activeness_count = es.count(index=copy_portrait_index_name, doc_type=copy_portrait_index_type, body=activeness_query_body)['count']
importance_count = es.count(index=copy_portrait_index_name, doc_type=copy_portrait_index_type, body=importance_query_body)['count']
result = [int(aver_activeness*100.0/top_activeness), activeness_count, int(aver_influence*100.0/top_influence), influence_count, int(aver_importance*100.0/top_importance), importance_count, total_number]
return result
def conclusion_on_influence(uid):
# test
index_name = copy_portrait_index_name
index_type = copy_portrait_index_type
total_number = es.count(index=copy_portrait_index_name,
doc_type=copy_portrait_index_type)["count"]
try:
influ_result = es.get(index=index_name, doc_type=index_type,
id=uid)['_source']
except:
influ_result = {}
result = [0, 0, 0, 0, 0, 0, total_number
] # aver_activeness, sorted, aver_influence, sorted
return result
aver_activeness = influ_result.get("aver_activeness", 0)
aver_influence = influ_result.get("aver_influence", 0)
aver_importance = influ_result.get('aver_importance', 0)
influence_query_body = {
"query": {
"match_all": {}
},
"sort": {
"aver_influence": {
"order": "desc"
}
},
"size": 1
}
top_influence = es.search(
index=copy_portrait_index_name,
doc_type=copy_portrait_index_type,
body=influence_query_body)['hits']['hits'][0]['sort'][0]
importance_query_body = {
"query": {
"match_all": {}
},
"sort": {
"aver_importance": {
"order": "desc"
}
},
"size": 1
}
top_importance = es.search(
index=copy_portrait_index_name,
doc_type=copy_portrait_index_type,
body=importance_query_body)['hits']['hits'][0]['sort'][0]
activeness_query_body = {
"query": {
"match_all": {}
},
"sort": {
"aver_activeness": {
"order": "desc"
}
},
"size": 1
}
top_activeness = es.search(
index=copy_portrait_index_name,
doc_type=copy_portrait_index_type,
body=activeness_query_body)['hits']['hits'][0]['sort'][0]
influence_query_body = {
"query": {
"filtered": {
"filter": {
"range": {
"aver_influence": {
"gt": aver_influence
}
}
}
}
}
}
activeness_query_body = {
"query": {
"filtered": {
"filter": {
"range": {
"aver_activeness": {
"gt": aver_activeness
}
}
}
}
}
}
importance_query_body = {
"query": {
"filtered": {
"filter": {
"range": {
"aver_importance": {
"gt": aver_importance
}
}
}
}
}
}
influence_count = es.count(index=copy_portrait_index_name,
doc_type=copy_portrait_index_type,
body=influence_query_body)['count']
activeness_count = es.count(index=copy_portrait_index_name,
doc_type=copy_portrait_index_type,
body=activeness_query_body)['count']
importance_count = es.count(index=copy_portrait_index_name,
doc_type=copy_portrait_index_type,
body=importance_query_body)['count']
result = [
int(aver_activeness * 100.0 / top_activeness), activeness_count,
int(aver_influence * 100.0 / top_influence), influence_count,
int(aver_importance * 100.0 / top_importance), importance_count,
total_number
]
return result
def search_task(task_name, submit_date, state, status, submit_user):
results = []
query = []
condition_num = 0
if task_name:
task_name_list = task_name.split(' ')
for item in task_name_list:
query.append({'wildcard': {'task_name': '*' + item + '*'}})
condition_num += 1
if submit_date:
submit_date_ts = datetime2ts(submit_date)
submit_date_start = submit_date_ts
submit_date_end = submit_date_ts + DAY
query.append({
'range': {
'submit_date': {
'gte': submit_date_start,
'lt': submit_date_end
}
}
})
condition_num += 1
if state:
state_list = state.split(' ')
for item in state_list:
query.append({'wildcard': {'state': '*' + item + '*'}})
condition_num += 1
if status:
query.append({'match': {'status': status}})
condition_num += 1
if submit_user:
query.append({'term': {'submit_user': submit_user}})
condition_num += 1
if condition_num > 0:
query.append({'term': {'task_type': 'analysis'}})
try:
source = es_group_result.search(index=group_index_name,
doc_type=group_index_type,
body={
'query': {
'bool': {
'must': query
}
},
'sort': [{
'count': {
'order': 'desc'
}
}],
'size':
MAX_VALUE
})
except Exception as e:
raise e
else:
query.append({'term': {'task_type': 'analysis'}})
source = es.search(index=group_index_name,
doc_type=group_index_type,
body={
'query': {
'bool': {
'must': query
}
},
'sort': [{
'count': {
'order': 'desc'
}
}],
'size': MAX_VALUE
})
try:
task_dict_list = source['hits']['hits']
except:
return None
result = []
for task_dict in task_dict_list:
try:
state = task_dict['_source']['state']
except:
state = ''
try:
status = task_dict['_source']['status']
except:
status = 0
result.append([
task_dict['_source']['task_name'],
task_dict['_source']['submit_date'], task_dict['_source']['count'],
state, status
])
return result
