def main():
topics = _topic_not_calc()
if topics and len(topics):
topic = topics[0]
start_ts = topic.start
end_ts = topic.end
db_date = topic.db_date
topicname = topic.topic
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
topic_id = acquire_topic_id(topicname, start_ts, end_ts)
windowsize = (end_ts - start_ts) / Day
date = ts2datetime(end_ts)
if windowsize > 7:
degree_rank(TOPK, date, topic_id, windowsize)
else:
pagerank_rank(TOPK, date, topic_id, windowsize)
topic_id = int(topic_id)
windowsize = int(windowsize)
if not topic_id:
gexf = ''
else:
gexf = make_network_graph(date, topic_id, topicname, windowsize)
save_gexf_results(topicname, date, windowsize, gexf)
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)
def main(topic, start_ts, end_ts):
#在topic_status中获取还未进行计算的话题
topics = _topic_not_calc(status='-1', module='i_news')
topic_status_info = db.session.query(TopicStatus).filter(TopicStatus.topic==topic ,\
TopicStatus.start==start_ts ,\
TopicStatus.end==end_ts ,\
TopicStatus.module=='i_news' ,\
TopicStatus.status==-1).first()
if topic_status_info:
topic_id = topic_status_info.id
start_ts = topic_status_info.start
end_ts = topic_status_info.end
topicname = topic_status_info.topic
db_date = topic_status_info.db_date
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date, 'i_news')
print 'update_status'
#mongodb中topic对应的collection
print 'get_dynamic_mongo'
news_collection , comment_collection = get_dynamic_mongo(topicname, start_ts, end_ts)
#早期参与者
print 'start compute early_join'
early_join(topicname, start_ts, end_ts, news_collection)
#趋势发起人
print 'start compute trend_user'
trend_user(topicname, start_ts, end_ts, news_collection, comment_collection)
print 'update_topic_end'
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date, 'i_news')
def main():
topics = _topic_not_calc()
if topics and len(topics):
topic = topics[0]
start_ts = topic.start
end_ts = topic.end
db_date = topic.db_date
topicname = topic.topic
print time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time())), topicname.encode('utf-8'), 'start'
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
result = calculate(topicname,start_ts,end_ts)
print time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time())), topicname.encode('utf-8'), result
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)
def _check_run_notcustomize_topic(during=Fifteenminutes):
'''定时执行非定制话题表中status为0的话题数量、关键词、关键微博计算
'''
topics = _topic_not_calc()
if topics and len(topics):
topic = topics[0]
start_ts = topic.start
end_ts = topic.end
db_date = topic.db_date
topicname = topic.topic
# update status to 0
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
print topicname.encode('utf-8'), ' run realtime job from %s to %s ' % (start_ts, end_ts)
sentimentRealTimeTopic(topicname, start_ts, end_ts+24*3600)
# update status to 1
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)
def compute_network(topic, start_ts, end_ts):
'''
topics = _topic_not_calc() # topics=[{id:x,module:x,status:x,topic:x,start:x,end:x,db_date:x}]
'''
'''
topic_status_info = db.session.query(TopicStatus).filter(TopicStatus.topic==topic ,\
TopicStatus.start==start_ts ,\
TopicStatus.end==end_ts ,\
TopicStatus.module=='identify' ,\
TopicStatus.status==-1).first()
if topic_status_info:
#topic = topics[0] # 每次只计算一个----为了做一个缓冲，每个n时间才计算一个
print 'topic_id', topic_status_info.id
start_ts = topic_status_info.start
end_ts = topic_status_info.end
db_date = topic_status_info.db_date
topicname = topic
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
print 'update_status'
topic_id = acquire_topic_id(topicname, start_ts, end_ts) # 重新获取id是因为TopicStatus中id是自增加的，进行更新后，id就不是原来的那一个了
windowsize = (end_ts - start_ts) / Day # 确定时间跨度的大小
date = ts2datetime(end_ts)
'''
#改动的地方从es表中读取话题的拼音也就是表名
if True:
print end_ts, type(end_ts)
#topicname = topic
date = ts2datetime(end_ts)
windowsize = (end_ts - start_ts) / Day # 确定时间跨度的大小
topic_pinyin_name = topic
# print 'start topic_name_transfer' #把汉字的时间名换成拼音 奥运会>aoyunhui
# topic_pinyin_name = weibo_TopicNameTransfer(topicname, start_ts, end_ts)
# print topic_pinyin_name
print 'start compute first_nodes'
#start_date = ts2datetime(start_ts) # used to compute the first user
get_first_node(topic_pinyin_name, start_ts, end_ts, windowsize, date)
print 'end compute first_nodes'
print 'start make network'
max_size = MAX_SIZE
attribute_add = True
g, gg, new_attribute_dict = make_network(topic_pinyin_name, date,
windowsize, max_size,
attribute_add)
#print g,gg,new_attribute_dict
print 'write gexf file'
#real_topic_id = acquire_real_topic_id(topicname, start_ts, end_ts)
real_topic_id = topic_pinyin_name
if not real_topic_id:
print 'the topic not exist'
return None
key = str(real_topic_id) + '_' + str(date) + '_' + str(windowsize)
print 'gexf_file:', str(GRAPH_PATH) + str(key) + '_g_graph.gexf'
#fh = open(str(GRAPH_PATH) + str(key) + '_g_graph.gexf', 'w+')
#fh.close()
#fh = open(str(GRAPH_PATH) + str(key) + '_gg_graph.gexf', 'w+')
#fh.close()
nx.write_gexf(g, str(GRAPH_PATH) + str(key) + '_g_graph.gexf')
nx.write_gexf(gg, str(GRAPH_PATH) + str(key) + '_gg_graph.gexf')
#nx.write_gexf(ds_dg, str(GRAPH_PATH) + str(key) + '_ds_dg_graph.gexf')
#nx.write_gexf(ds_udg, str(GRAPH_PATH) + str(key) + '_ds_udg_graph.gexf')
#这里要改一下 不用SSDB了
save_attribute_dict(new_attribute_dict, 'g')
#save_attribute_dict(ds_new_attribute_dict, 'ds_g')
print 'end make network'
print 'start PageRank'
all_uid_pr, data = pagerank_rank(TOPK, date, windowsize,
topic_pinyin_name)
print 'len(all_uid_pr):', len(all_uid_pr)
print 'end PageRank'
print 'start make network graph'
#topic_id = int(topic_id)
windowsize = int(windowsize)
if not topic_pinyin_name: # 待删
gexf = ''
else:
gexf = make_network_graph(date, topic_pinyin_name, windowsize,
all_uid_pr, data)
#gexf = json.dumps(gexf)
print 'save gexf'
#print '*************************'*10
#print gexf
#print '*************************'*10
save_gexf_results(topic_pinyin_name, date, windowsize, gexf, gexf_type)
print 'start fu_tr'
get_interval_count(topic_pinyin_name, date, windowsize)
print 'update_topic_end'
db_date = date
_update_topic_status2Completed(topic_pinyin_name, start_ts, end_ts,
db_date)
print 'all done!'
def main(topic, start_ts, end_ts):
'''
topics = _topic_not_calc() # topics=[{id:x,module:x,status:x,topic:x,start:x,end:x,db_date:x}]
'''
topic_status_info = db.session.query(TopicStatus).filter(TopicStatus.topic==topic ,\
TopicStatus.start==start_ts ,\
TopicStatus.end==end_ts ,\
TopicStatus.module=='identify' ,\
TopicStatus.status==-1).first()
if topic_status_info:
#topic = topics[0] # 每次只计算一个----为了做一个缓冲，每个n时间才计算一个
print 'topic_id', topic_status_info.id
start_ts = topic_status_info.start
end_ts = topic_status_info.end
db_date = topic_status_info.db_date
topicname = topic
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
print 'update_status'
topic_id = acquire_topic_id(topicname, start_ts, end_ts) # 重新获取id是因为TopicStatus中id是自增加的，进行更新后，id就不是原来的那一个了
windowsize = (end_ts - start_ts) / Day # 确定时间跨度的大小
date = ts2datetime(end_ts)
print 'start topic2xapianid'
topic_xapian_id = weibo_topic2xapian(topicname, start_ts, end_ts)
print 'topic_xapian_id:', topic_xapian_id
print 'start compute first_nodes'
start_date = ts2datetime(start_ts) # used to compute the first user
get_first_node(topicname, start_date, date, windowsize, topic_xapian_id)
print 'end compute first_nodes'
#
print 'start make network'
max_size = MAX_SIZE
attribute_add = True
g, gg, new_attribute_dict, ds_dg, ds_udg, ds_new_attribute_dict = make_network(topicname, date, windowsize, topic_xapian_id, max_size, attribute_add)
print 'write gexf file'
real_topic_id = acquire_real_topic_id(topicname, start_ts, end_ts)
if not real_topic_id:
print 'the topic not exist'
return None
key = str(real_topic_id) + '_' + str(date) + '_' + str(windowsize)
print 'gexf_file:', str(GRAPH_PATH)+str(key)+'_g_graph.gexf'
nx.write_gexf(g, str(GRAPH_PATH) + str(key) + '_g_graph.gexf')
nx.write_gexf(gg, str(GRAPH_PATH) + str(key) + '_gg_graph.gexf')
nx.write_gexf(ds_dg, str(GRAPH_PATH) + str(key) + '_ds_dg_graph.gexf')
nx.write_gexf(ds_udg, str(GRAPH_PATH) + str(key) + '_ds_udg_graph.gexf')
save_attribute_dict(new_attribute_dict, 'g')
save_attribute_dict(ds_new_attribute_dict, 'ds_g')
print 'end make network'
print 'start PageRank'
all_uid_pr, ds_all_uid_pr, data, ds_data = pagerank_rank(TOPK, date, topic_id, windowsize, topicname, real_topic_id)
print 'len(all_uid_pr):', len(all_uid_pr)
print 'end PageRank'
print 'start make network graph'
topic_id = int(topic_id)
windowsize = int(windowsize)
if not topic_id: # 待删
gexf = ''
else:
gexf, ds_gexf = make_network_graph(date, topic_id, topicname, windowsize, all_uid_pr, data, ds_all_uid_pr, ds_data, real_topic_id)
print 'save gexf'
save_gexf_results(topicname, date, windowsize, gexf, gexf_type)
save_gexf_results(topicname, date, windowsize, ds_gexf, ds_gexf_type)
print 'start fu_tr'
get_interval_count(topicname, date, windowsize, topic_xapian_id)
print 'update_topic_end'
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)
def main(topic, start_ts, end_ts):
'''
topics = _topic_not_calc() # topics=[{id:x,module:x,status:x,topic:x,start:x,end:x,db_date:x}]
'''
topic_status_info = db.session.query(TopicStatus).filter(TopicStatus.topic==topic ,\
TopicStatus.start==start_ts ,\
TopicStatus.end==end_ts ,\
TopicStatus.module=='identify' ,\
TopicStatus.status==-1).first()
if topic_status_info:
#topic = topics[0] # 每次只计算一个----为了做一个缓冲，每个n时间才计算一个
print 'topic_id', topic_status_info.id
start_ts = topic_status_info.start
end_ts = topic_status_info.end
db_date = topic_status_info.db_date
topicname = topic
_update_topic_status2Computing(topicname, start_ts, end_ts, db_date)
print 'update_status'
topic_id = acquire_topic_id(
topicname, start_ts,
end_ts) # 重新获取id是因为TopicStatus中id是自增加的，进行更新后，id就不是原来的那一个了
windowsize = (end_ts - start_ts) / Day # 确定时间跨度的大小
date = ts2datetime(end_ts)
print 'start topic2xapianid'
topic_xapian_id = weibo_topic2xapian(topicname, start_ts, end_ts)
print 'topic_xapian_id:', topic_xapian_id
print 'start compute first_nodes'
start_date = ts2datetime(start_ts) # used to compute the first user
get_first_node(topicname, start_date, date, windowsize,
topic_xapian_id)
print 'end compute first_nodes'
#
print 'start make network'
max_size = MAX_SIZE
attribute_add = True
g, gg, new_attribute_dict, ds_dg, ds_udg, ds_new_attribute_dict = make_network(
topicname, date, windowsize, topic_xapian_id, max_size,
attribute_add)
print 'write gexf file'
real_topic_id = acquire_real_topic_id(topicname, start_ts, end_ts)
if not real_topic_id:
print 'the topic not exist'
return None
key = str(real_topic_id) + '_' + str(date) + '_' + str(windowsize)
print 'gexf_file:', str(GRAPH_PATH) + str(key) + '_g_graph.gexf'
nx.write_gexf(g, str(GRAPH_PATH) + str(key) + '_g_graph.gexf')
nx.write_gexf(gg, str(GRAPH_PATH) + str(key) + '_gg_graph.gexf')
nx.write_gexf(ds_dg, str(GRAPH_PATH) + str(key) + '_ds_dg_graph.gexf')
nx.write_gexf(ds_udg,
str(GRAPH_PATH) + str(key) + '_ds_udg_graph.gexf')
save_attribute_dict(new_attribute_dict, 'g')
save_attribute_dict(ds_new_attribute_dict, 'ds_g')
print 'end make network'
print 'start PageRank'
all_uid_pr, ds_all_uid_pr, data, ds_data = pagerank_rank(
TOPK, date, topic_id, windowsize, topicname, real_topic_id)
print 'len(all_uid_pr):', len(all_uid_pr)
print 'end PageRank'
print 'start make network graph'
topic_id = int(topic_id)
windowsize = int(windowsize)
if not topic_id: # 待删
gexf = ''
else:
gexf, ds_gexf = make_network_graph(date, topic_id, topicname,
windowsize, all_uid_pr, data,
ds_all_uid_pr, ds_data,
real_topic_id)
print 'save gexf'
save_gexf_results(topicname, date, windowsize, gexf, gexf_type)
save_gexf_results(topicname, date, windowsize, ds_gexf, ds_gexf_type)
print 'start fu_tr'
get_interval_count(topicname, date, windowsize, topic_xapian_id)
print 'update_topic_end'
_update_topic_status2Completed(topicname, start_ts, end_ts, db_date)
