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Commit 4ae7e49f authored by lixiaofang's avatar lixiaofang
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修改mapping

parent c4378545
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Showing with 213 additions and 159 deletions
search/utils/topic.py
View file @ 4ae7e49f
......@@ -251,9 +251,9 @@ class TopicUtils(object):
]
if query is not None: # 搜索帖子
multi_fields = {
#'description': 200,
# 'description': 200,
'content': 300,
#'name': 400,
# 'name': 400,
'tag_name_list': 300,
}
query_fields = ['^'.join((k, str(v))) for (k, v) in multi_fields.items()]
......@@ -329,18 +329,18 @@ class TopicUtils(object):
'query': query,
'type': 'best_fields',
'operator': 'and',
'fields': ["content","tag_name_list"],
'fields': ["content", "tag_name_list"],
}
functions_list += [
{
"weight": 300,
"filter":{
"bool":{
"must":{
"filter": {
"bool": {
"must": {
"term": {"content_level": 6},
},
"minimum_should_match": 1,
"should":[
"should": [
{'multi_match': multi_match},
{"term": {"tag_list": tag_id}},
{"term": {"user_nick_name_pre": query.lower()}}
......@@ -1067,6 +1067,20 @@ class TopicUtils(object):
}
},
})
elif sort_by == TOPIC_SEARCH_SORT.TOPIC_ADD_TIME:
sort_rule.append({
"related_billboard.topic_add_createtime": {
"order": "desc",
"nested_path": "related_billboard",
"nested_filter": {
"term": {
"related_billboard.pictorial_id": pictorial_id
}
}
},
})
logging.info("get picotirial:%s" % sort_rule)
return sort_rule
......
search/views/topic.py
View file @ 4ae7e49f
......@@ -14,6 +14,7 @@ from search.utils.common import *
from libs.es import ESPerform
from django.conf import settings
def get_discover_page_topic_ids(user_id, device_id, size, query_type=TopicPageType.FIND_PAGE):
try:
if user_id == -1:
......@@ -28,10 +29,11 @@ def get_discover_page_topic_ids(user_id, device_id, size, query_type=TopicPageTy
if have_read_topic_id_list == None:
have_read_topic_id_list = list()
recommend_topic_ids = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=0, offset=0, size=size,single_size=size,
query_type=query_type,
filter_topic_id_list=have_read_topic_id_list,index_type="topic",routing="4,5,6")
recommend_topic_ids = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=0, offset=0, size=size,
single_size=size,
query_type=query_type,
filter_topic_id_list=have_read_topic_id_list,
index_type="topic", routing="4,5,6")
have_read_topic_id_list.extend(recommend_topic_ids)
redis_dict = {
......@@ -46,27 +48,31 @@ def get_discover_page_topic_ids(user_id, device_id, size, query_type=TopicPageTy
def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query=None,
query_type=TopicPageType.HOME_RECOMMEND,promote_topic_list = [],disable_collpase=False,usefulrecall = -1,useful_tag_list =[]):
query_type=TopicPageType.HOME_RECOMMEND, promote_topic_list=[], disable_collpase=False,
usefulrecall=-1, useful_tag_list=[]):
try:
topic_star_routing = "6"
index_type = "topic-high-star"
device_redis_key = ""
if query is None:
if user_id>0:
if user_id > 0:
redis_key = "physical:home_recommend" + ":user_id:" + str(user_id) + ":query_type:" + str(query_type)
device_redis_key = "physical:home_recommend" + ":device_id:" + device_id + ":query_type:" + str(query_type)
device_redis_key = "physical:home_recommend" + ":device_id:" + device_id + ":query_type:" + str(
query_type)
else:
redis_key = "physical:home_recommend" + ":device_id:" + device_id + ":query_type:" + str(query_type)
else:
topic_star_routing = "3,4,5,6"
index_type = "topic"
if user_id>0:
redis_key = "physical:home_query" + ":user_id:" + str(user_id) + ":query:" + str(query) + ":query_type:" + str(query_type)
device_redis_key = "physical:home_query" + ":device_id:" + device_id + ":query:" + str(query) + ":query_type:" + str(query_type)
if user_id > 0:
redis_key = "physical:home_query" + ":user_id:" + str(user_id) + ":query:" + str(
query) + ":query_type:" + str(query_type)
device_redis_key = "physical:home_query" + ":device_id:" + device_id + ":query:" + str(
query) + ":query_type:" + str(query_type)
else:
redis_key = "physical:home_query" + ":device_id:" + device_id + ":query:" + str(query) + ":query_type:" + str(query_type)
redis_key = "physical:home_query" + ":device_id:" + device_id + ":query:" + str(
query) + ":query_type:" + str(query_type)
redis_field_list = [b'have_read_topic_list']
redis_field_val_list = redis_client.hmget(redis_key, redis_field_list)
......@@ -78,18 +84,17 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
if query is None:
have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
else:
if offset>0: # 首次搜索时不需要过滤已读
if offset > 0: # 首次搜索时不需要过滤已读
have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
elif len(device_redis_key)>0:
elif len(device_redis_key) > 0:
redis_field_val_list = redis_client.hmget(device_redis_key, redis_field_list)
if redis_field_val_list[0]:
if query is None:
have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
else:
if offset>0: # 首次搜索时不需要过滤已读
if offset > 0: # 首次搜索时不需要过滤已读
have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
if have_read_topic_id_list == None:
have_read_topic_id_list = list()
have_read_topic_id_list.extend(promote_topic_list)
......@@ -98,66 +103,72 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
attention_tag_list = list()
recommend_topic_list = list()
if query is None:
if user_id != -1:
# 有用标签召回
if usefulrecall != -1:
useful_topic_id_list = TopicUtils.userful_tag_topic_list(user_id, have_read_topic_id_list, 4,
"topic-high-star", "6",useful_tag_list=useful_tag_list)
# user_similar_score_redis_key = "physical:user_similar_score:user_id:" + str(user_id)
# redis_user_similar_score_redis_val = redis_client.get(user_similar_score_redis_key)
# user_similar_score_redis_list = json.loads(
# redis_user_similar_score_redis_val) if redis_user_similar_score_redis_val else []
size = size - len(useful_topic_id_list)
have_read_topic_id_list.extend(useful_topic_id_list)
# linucb 推荐帖子
topic_recommend_redis_key = "physical:linucb:topic_recommend:device_id:" + str(device_id)
recommend_topic_dict = redis_client.hgetall(topic_recommend_redis_key)
linucb_recommend_topic_id_list = list()
recommend_topic_list = list()
if b"data" in recommend_topic_dict:
linucb_recommend_topic_id_list = json.loads(recommend_topic_dict[b"data"])
if linucb_recommend_topic_id_list == None:
linucb_recommend_topic_id_list = list()
# 推荐帖子是强插的，要保证推荐帖子不在已读里
logging.warning("type1:%s,type2:%s"%(type(linucb_recommend_topic_id_list),type(have_read_topic_id_list)))
recommend_topic_id_list = list(set(linucb_recommend_topic_id_list) - set(have_read_topic_id_list))
recommend_topic_id_list.sort(key=linucb_recommend_topic_id_list.index)
# cursor = int(str(recommend_topic_dict[b"cursor"], encoding="utf-8"))
# newcursor = cursor + 6
if len(recommend_topic_id_list) > 0:
recommend_topic_list = recommend_topic_id_list[0:size]
if user_id != -1:
# 有用标签召回
if usefulrecall != -1:
useful_topic_id_list = TopicUtils.userful_tag_topic_list(user_id, have_read_topic_id_list, 4,
"topic-high-star", "6",
useful_tag_list=useful_tag_list)
# user_similar_score_redis_key = "physical:user_similar_score:user_id:" + str(user_id)
# redis_user_similar_score_redis_val = redis_client.get(user_similar_score_redis_key)
# user_similar_score_redis_list = json.loads(
# redis_user_similar_score_redis_val) if redis_user_similar_score_redis_val else []
size = size - len(useful_topic_id_list)
have_read_topic_id_list.extend(useful_topic_id_list)
# linucb 推荐帖子
topic_recommend_redis_key = "physical:linucb:topic_recommend:device_id:" + str(device_id)
recommend_topic_dict = redis_client.hgetall(topic_recommend_redis_key)
linucb_recommend_topic_id_list = list()
recommend_topic_list = list()
if b"data" in recommend_topic_dict:
linucb_recommend_topic_id_list = json.loads(recommend_topic_dict[b"data"])
if linucb_recommend_topic_id_list == None:
linucb_recommend_topic_id_list = list()
# 推荐帖子是强插的，要保证推荐帖子不在已读里
logging.warning(
"type1:%s,type2:%s" % (type(linucb_recommend_topic_id_list), type(have_read_topic_id_list)))
recommend_topic_id_list = list(set(linucb_recommend_topic_id_list) - set(have_read_topic_id_list))
recommend_topic_id_list.sort(key=linucb_recommend_topic_id_list.index)
# cursor = int(str(recommend_topic_dict[b"cursor"], encoding="utf-8"))
# newcursor = cursor + 6
if len(recommend_topic_id_list) > 0:
recommend_topic_list = recommend_topic_id_list[0:size]
# redis_client.hset(topic_recommend_redis_key, "cursor", newcursor)
if b"datadict" in recommend_topic_dict:
linucb_recommend_topic_id_dict = json.loads(recommend_topic_dict[b"datadict"])
if linucb_recommend_topic_id_dict is not None and len(recommend_topic_list) >0:
for i in recommend_topic_list:
recommend_topic_user_list.append(linucb_recommend_topic_id_dict[str(i)])
# if have_read_topic_id_list == None:
# have_read_topic_id_list = list()
# 用户关注标签
redis_tag_data = redis_client.hget("physical:linucb:register_user_tag_info", user_id)
attention_tag_list = json.loads(redis_tag_data) if redis_tag_data else []
if len(recommend_topic_list)>0:
size = size-len(recommend_topic_list)
have_read_topic_id_list.extend(recommend_topic_list)
# have_read_topic_id_list_add_promote = list()
# have_read_topic_id_list_add_promote.extend(have_read_topic_id_list)
# promote_recommend_topic_id_list = TopicHomeRecommend.objects.using(settings.SLAVE_DB_NAME).filter(
# is_online=1).values_list("topic_id",flat=True)
#
# for topic_id in promote_recommend_topic_id_list:
# have_read_topic_id_list_add_promote.append(topic_id)
if b"datadict" in recommend_topic_dict:
linucb_recommend_topic_id_dict = json.loads(recommend_topic_dict[b"datadict"])
if linucb_recommend_topic_id_dict is not None and len(recommend_topic_list) > 0:
for i in recommend_topic_list:
recommend_topic_user_list.append(linucb_recommend_topic_id_dict[str(i)])
# if have_read_topic_id_list == None:
# have_read_topic_id_list = list()
# 用户关注标签
redis_tag_data = redis_client.hget("physical:linucb:register_user_tag_info", user_id)
attention_tag_list = json.loads(redis_tag_data) if redis_tag_data else []
if len(recommend_topic_list) > 0:
size = size - len(recommend_topic_list)
have_read_topic_id_list.extend(recommend_topic_list)
# have_read_topic_id_list_add_promote = list()
# have_read_topic_id_list_add_promote.extend(have_read_topic_id_list)
# promote_recommend_topic_id_list = TopicHomeRecommend.objects.using(settings.SLAVE_DB_NAME).filter(
# is_online=1).values_list("topic_id",flat=True)
#
# for topic_id in promote_recommend_topic_id_list:
# have_read_topic_id_list_add_promote.append(topic_id)
rank_topic_id_list = list()
if size>0:
if size > 0:
rank_topic_id_list = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=tag_id, offset=0, size=size,
single_size=size,query=query, query_type=query_type,
filter_topic_id_list=have_read_topic_id_list,
index_type=index_type,routing=topic_star_routing,attention_tag_list=attention_tag_list,linucb_user_id_list=recommend_topic_user_list,disable_collpase=disable_collpase)
single_size=size, query=query,
query_type=query_type,
filter_topic_id_list=have_read_topic_id_list,
index_type=index_type, routing=topic_star_routing,
attention_tag_list=attention_tag_list,
linucb_user_id_list=recommend_topic_user_list,
disable_collpase=disable_collpase)
# if len(recommend_topic_list) == 6 and query is None:
# if (size < 11):
......@@ -174,7 +185,7 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
# topic_id_list.extend(rank_topic_id_list)
have_read_topic_id_list.extend(rank_topic_id_list)
if len(have_read_topic_id_list) > 30000:
cut_len = len(have_read_topic_id_list)-30000
cut_len = len(have_read_topic_id_list) - 30000
have_read_topic_id_list = have_read_topic_id_list[cut_len:]
redis_dict = {
"have_read_topic_list": json.dumps(have_read_topic_id_list),
......@@ -183,13 +194,13 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
# 每个session key保存60天
redis_client.expire(redis_key, 60 * 60 * 24 * 60)
if usefulrecall != -1:
return recommend_topic_list,rank_topic_id_list,useful_topic_id_list
return recommend_topic_list, rank_topic_id_list, useful_topic_id_list
else:
return recommend_topic_list, rank_topic_id_list
except:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
if usefulrecall != -1:
return [],[],[]
return [], [], []
else:
return [], []
......@@ -204,7 +215,8 @@ def query_tag_id_by_topic(offset=0, size=10, topic_id_list=[], user_id=-1):
@bind("physical/search/home_recommend")
def home_recommend(device_id="", user_id=-1, offset=0, size=10, query_type=TopicPageType.HOME_RECOMMEND,promote_topic_list=[],usefulrecall = -1,useful_tag_list=[]):
def home_recommend(device_id="", user_id=-1, offset=0, size=10, query_type=TopicPageType.HOME_RECOMMEND,
promote_topic_list=[], usefulrecall=-1, useful_tag_list=[]):
"""
:remark:首页推荐，目前只推荐日记
:param session_id:
......@@ -237,26 +249,34 @@ def home_recommend(device_id="", user_id=-1, offset=0, size=10, query_type=Topic
have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
if len(have_read_topic_id_list) > offset:
recommend_topic_ids = have_read_topic_id_list[offset:offset+size]
recommend_topic_ids = have_read_topic_id_list[offset:offset + size]
else:
recommend_topic_ids = have_read_topic_id_list[0:size]
else:
if usefulrecall != -1 and len(useful_tag_list)>0:
recommend_topic_ids,rank_topic_ids,useful_topic_ids = get_home_recommend_topic_ids(user_id, device_id, tag_id=0, offset=0, size=size,
query_type=query_type,promote_topic_list=promote_topic_list,usefulrecall=usefulrecall,useful_tag_list=useful_tag_list)
return {"linucb_topic_ids": recommend_topic_ids,"rank_topic_ids":rank_topic_ids,"useful_topic_ids":useful_topic_ids}
else:
recommend_topic_ids,rank_topic_ids = get_home_recommend_topic_ids(user_id, device_id, tag_id=0, offset=0, size=size,
query_type=query_type,promote_topic_list=promote_topic_list)
return {"linucb_topic_ids": recommend_topic_ids,"rank_topic_ids":rank_topic_ids}
if usefulrecall != -1 and len(useful_tag_list) > 0:
recommend_topic_ids, rank_topic_ids, useful_topic_ids = get_home_recommend_topic_ids(user_id, device_id,
tag_id=0, offset=0,
size=size,
query_type=query_type,
promote_topic_list=promote_topic_list,
usefulrecall=usefulrecall,
useful_tag_list=useful_tag_list)
return {"linucb_topic_ids": recommend_topic_ids, "rank_topic_ids": rank_topic_ids,
"useful_topic_ids": useful_topic_ids}
else:
recommend_topic_ids, rank_topic_ids = get_home_recommend_topic_ids(user_id, device_id, tag_id=0,
offset=0, size=size,
query_type=query_type,
promote_topic_list=promote_topic_list)
return {"linucb_topic_ids": recommend_topic_ids, "rank_topic_ids": rank_topic_ids}
except:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
if usefulrecall != -1:
return {"linucb_topic_ids": [],"rank_topic_ids":[],"useful_topic_ids":[]}
return {"linucb_topic_ids": [], "rank_topic_ids": [], "useful_topic_ids": []}
else:
return {"linucb_topic_ids": [], "rank_topic_ids": []}
return {"linucb_topic_ids": [], "rank_topic_ids": []}
@bind("physical/search/discover_page")
......@@ -300,11 +320,12 @@ def home_query(device_id="", tag_id=-1, user_id=-1, query="", offset=0, size=10)
if not isinstance(device_id, str):
device_id = ""
recommend_topic_list, rank_topic_id_list = get_home_recommend_topic_ids(user_id, device_id, tag_id, offset=offset, size=size, query=query)
if len(rank_topic_id_list)>0 and len(rank_topic_id_list)<size:
recommend_topic_list, rank_topic_id_list = get_home_recommend_topic_ids(user_id, device_id, tag_id,
offset=offset, size=size, query=query)
if len(rank_topic_id_list) > 0 and len(rank_topic_id_list) < size:
recommend_topic_list, rank_topic_id_list = get_home_recommend_topic_ids(user_id, device_id, tag_id,
offset=offset, size=size,
query=query,disable_collpase=True)
query=query, disable_collpase=True)
return {"recommend_topic_ids": rank_topic_id_list}
except:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
......@@ -326,9 +347,9 @@ def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pic
if not isinstance(user_id, int):
user_id = -1
if user_id > 0:
redis_key = "physical:topic_detail_recommend" + ":user_id:" + str(user_id) + "topic_id:"+str(topic_id)
redis_key = "physical:topic_detail_recommend" + ":user_id:" + str(user_id) + "topic_id:" + str(topic_id)
else:
redis_key = "physical:topic_detail_recommend" + ":device_id:" + device_id + "topic_id:"+str(topic_id)
redis_key = "physical:topic_detail_recommend" + ":device_id:" + device_id + "topic_id:" + str(topic_id)
if int(offset) == 0:
have_read_topic_list = list()
# redis_dict = {
......@@ -341,7 +362,7 @@ def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pic
have_read_topic_list = list()
redis_field_list = [b'have_read_topic_list']
have_read_topic_redis_data = redis_client.hmget(redis_key,redis_field_list)
have_read_topic_redis_data = redis_client.hmget(redis_key, redis_field_list)
have_read_topic_list = json.loads(have_read_topic_redis_data[0]) if have_read_topic_redis_data[0] else []
es_cli_obj = ESPerform.get_cli()
have_read_topic_list.append(topic_id)
......@@ -349,28 +370,33 @@ def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pic
topic_tag_result = list()
result = list()
if len(topic_tag_list) != 0:
topic_tag_result = TopicUtils.top_get_topic_detail_recommend_list(user_id,topic_id,have_read_topic_list,size,es_cli_obj,
index_type="topic",routing="3,4,5,6",topic_tag_list = topic_tag_list)
topic_tag_size = len(topic_tag_result)
have_read_topic_list.extend(topic_tag_result)
else:
topic_tag_size = 0
if topic_tag_size <size:
size = size - topic_tag_size
if topic_user_id != -1:
topic_user_result = TopicUtils.top_get_topic_detail_recommend_list(user_id, topic_id, have_read_topic_list,
topic_tag_result = TopicUtils.top_get_topic_detail_recommend_list(user_id, topic_id, have_read_topic_list,
size, es_cli_obj,
index_type="topic", routing="3,4,5,6",topic_user_id = topic_user_id
)
topic_user_size = len(topic_user_result)
have_read_topic_list.extend(topic_user_result)
if topic_user_size < size:
size = size - topic_user_size
result = TopicUtils.top_get_topic_detail_recommend_list(user_id, topic_id,
have_read_topic_list,
size, es_cli_obj,
index_type="topic", routing="4,5,6")
have_read_topic_list.extend(result)
index_type="topic", routing="3,4,5,6",
topic_tag_list=topic_tag_list)
topic_tag_size = len(topic_tag_result)
have_read_topic_list.extend(topic_tag_result)
else:
topic_tag_size = 0
if topic_tag_size < size:
size = size - topic_tag_size
if topic_user_id != -1:
topic_user_result = TopicUtils.top_get_topic_detail_recommend_list(user_id, topic_id,
have_read_topic_list,
size, es_cli_obj,
index_type="topic",
routing="3,4,5,6",
topic_user_id=topic_user_id
)
topic_user_size = len(topic_user_result)
have_read_topic_list.extend(topic_user_result)
if topic_user_size < size:
size = size - topic_user_size
result = TopicUtils.top_get_topic_detail_recommend_list(user_id, topic_id,
have_read_topic_list,
size, es_cli_obj,
index_type="topic", routing="4,5,6")
have_read_topic_list.extend(result)
# have_read_topic_redis_data = redis_client.get(redis_key)
# have_read_topic_list = json.loads(have_read_topic_redis_data) if have_read_topic_redis_data else []
......@@ -446,8 +472,8 @@ def topic_search(filters, nfilters=None, sorts_by=None, offset=0, size=10):
"""帖子搜索。"""
try:
(topic_id_list,total_count) = TopicUtils.list_topic_ids(filters=filters, nfilters=nfilters,
sorts_by=sorts_by, offset=offset, size=size)
(topic_id_list, total_count) = TopicUtils.list_topic_ids(filters=filters, nfilters=nfilters,
sorts_by=sorts_by, offset=offset, size=size)
return {
"topic_ids": topic_id_list,
......@@ -470,8 +496,10 @@ def query_topic_by_user_similarity(topic_similarity_score_dict, offset=0, size=1
try:
must_topic_id_list = list(topic_similarity_score_dict.keys())
topic_id_list = TopicUtils.get_recommend_topic_ids(tag_id=0, user_id=-1, offset=offset, size=size,single_size=size,
must_topic_id_list=must_topic_id_list,index_type="topic",routing="4,5,6")
topic_id_list = TopicUtils.get_recommend_topic_ids(tag_id=0, user_id=-1, offset=offset, size=size,
single_size=size,
must_topic_id_list=must_topic_id_list, index_type="topic",
routing="4,5,6")
return {"recommend_topic_ids": topic_id_list}
except:
......
trans2es/mapping/topic-high-star.json
View file @ 4ae7e49f
{
"dynamic":"strict",
{"dynamic":"strict",
"_routing": {"required": true},
"properties": {
"id":{"type":"long"},
......@@ -60,6 +59,7 @@
"type":"nested",
"properties":{
"pictorial_id":{"type":"long"},
"topic_add_createtime":{"type":"long"},
"real_vote_cnt":{"type":"long"},
"virt_vote_cnt":{"type":"long"},
"total_vote_cnt":{"type":"long"}
......@@ -67,3 +67,6 @@
}
}
}
trans2es/mapping/topic-star-routing.json
View file @ 4ae7e49f
......@@ -8,18 +8,18 @@
"vote_num":{"type":"long"},
"total_vote_num":{"type":"long"},
"reply_num":{"type":"long"},
"name":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"description":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"content":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"name":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"description":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"content":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"content_level":{"type":"text"},
"user_id":{"type":"long"},
"user_nick_name":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},//帖子用户名
"user_nick_name":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},//帖子用户名
"user_nick_name_pre": {"type":"text","analyzer":"keyword"}, //不切词的用户名
"group_id":{"type":"long"}, //所在组ID
"tag_list":{"type":"long"},//标签属性
"useful_tag_list":{"type":"long"},//有用标签属性
"edit_tag_list":{"type":"long"},//编辑标签
"tag_name_list":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"tag_name_list":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"share_num":{"type":"long"},
"pick_id_list":{"type":"long"},
"offline_score":{"type":"double"},//离线算分
......@@ -44,14 +44,14 @@
"platform": {"type": "long"},
"platform_id": {"type": "long"},
"drop_score":{"type": "double"}, // 人工降分
"drop_score":{"type": "long"}, // 人工降分
"sort_score":{"type": "double"}, // 排序分
"pictorial_id":{"type": "long"}, //所在组ID
"pictorial_name":{ // 所在组名称
"type": "text",
"analyzer": "gm_default_index",
"search_analyzer": "gm_default_index"
"analyzer": "keyword",
"search_analyzer": "keyword"
},
"is_excellent":{"type": "long"},
"is_operation_home_recommend": {"type": "boolean"}, //是否首页运营推荐
......@@ -60,10 +60,14 @@
"type":"nested",
"properties":{
"pictorial_id":{"type":"long"},
"topic_add_createtime":{"type":"long"},
"real_vote_cnt":{"type":"long"},
"virt_vote_cnt":{"type":"long"},
"total_vote_cnt":{"type":"long"}
}
}
}
}
\ No newline at end of file
}
trans2es/mapping/topic-star.json
View file @ 4ae7e49f
......@@ -44,7 +44,7 @@
"platform": {"type": "long"},
"platform_id": {"type": "long"},
"drop_score":{"type": "double"}, // 人工降分
"drop_score":{"type": "long"}, // 人工降分
"sort_score":{"type": "double"}, // 排序分
"pictorial_id":{"type": "long"}, //所在组ID
......
trans2es/mapping/topic.json
View file @ 4ae7e49f
......@@ -8,18 +8,18 @@
"vote_num":{"type":"long"},
"total_vote_num":{"type":"long"},
"reply_num":{"type":"long"},
"name":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"description":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"content":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"name":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"description":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"content":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"content_level":{"type":"text"},
"user_id":{"type":"long"},
"user_nick_name":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},//帖子用户名
"user_nick_name":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},//帖子用户名
"user_nick_name_pre": {"type":"text","analyzer":"keyword"}, //不切词的用户名
"group_id":{"type":"long"}, //所在组ID
"tag_list":{"type":"long"},//标签属性
"useful_tag_list":{"type":"long"},//有用标签属性
"edit_tag_list":{"type":"long"},//编辑标签
"tag_name_list":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
"tag_name_list":{"type":"text","analyzer":"keyword","search_analyzer":"keyword"},
"share_num":{"type":"long"},
"pick_id_list":{"type":"long"},
"offline_score":{"type":"double"},//离线算分
......@@ -44,14 +44,14 @@
"platform": {"type": "long"},
"platform_id": {"type": "long"},
"drop_score":{"type": "double"}, // 人工降分
"drop_score":{"type": "long"}, // 人工降分
"sort_score":{"type": "double"}, // 排序分
"pictorial_id":{"type": "long"}, //所在组ID
"pictorial_name":{ // 所在组名称
"type": "text",
"analyzer": "gm_default_index",
"search_analyzer": "gm_default_index"
"analyzer": "keyword",
"search_analyzer": "keyword"
},
"is_excellent":{"type": "long"},
"is_operation_home_recommend": {"type": "boolean"}, //是否首页运营推荐
......@@ -60,6 +60,7 @@
"type":"nested",
"properties":{
"pictorial_id":{"type":"long"},
"topic_add_createtime":{"type":"long"},
"real_vote_cnt":{"type":"long"},
"virt_vote_cnt":{"type":"long"},
"total_vote_cnt":{"type":"long"}
......
trans2es/models/topic.py
View file @ 4ae7e49f
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import unicode_literals, absolute_import, print_function
from django.conf import settings
from django.core.management.base import BaseCommand, CommandError
import traceback
import logging
import datetime
import time
from libs.es import ESPerform
from django.db import models
import datetime
from alpha_types.venus import GRAP_PLATFORM
from .pick_topic import PickTopic
from .tag import TopicTag, Tag
from .user_extra import UserExtra
......@@ -203,7 +202,7 @@ class Topic(models.Model):
tag_id_list = TopicTag.objects.using(settings.SLAVE_DB_NAME).filter(topic_id=self.id,
is_collection=1).values_list("tag_id",
flat=True)
return list(tag_id_list)
return list(tag_id_list)
except:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
return []
......@@ -283,25 +282,29 @@ class Topic(models.Model):
def get_related_billboard(self):
try:
pictorial_ids = Topic.get_pictorial_id(self)
# pictorial_ids = Topic.get_pictorial_id(self)
pictorial_id_list = []
related_billboard_list = list()
for pictorial_id in pictorial_ids:
pictorials = PictorialTopic.objects.filter(topic_id=self.id).values("pictorial_id", "create_time")
for pictorial_id in pictorials:
query_result = TopicBillBoard.objects.filter(pictorial_id=pictorial_id,
query_result = TopicBillBoard.objects.filter(pictorial_id=pictorial_id.get('pictorial_id', None),
topic_id=self.id).values().first()
if query_result == None:
related_billboard_list.append({"pictorial_id": pictorial_id, "real_vote_cnt": 0,
"virt_vote_cnt": 0, "total_vote_cnt": 0})
related_billboard_list.append({"pictorial_id": pictorial_id.get('pictorial_id', None), "real_vote_cnt": 0,
"virt_vote_cnt": 0, "total_vote_cnt": 0,
"topic_add_createtime": int(
time.mktime(pictorial_id.get("create_time", None).timetuple()))})
else:
total_vote_cnt = int(query_result["virt_vote_cnt"]) + int(query_result["real_vote_cnt"])
related_billboard_list.append(
{"pictorial_id": query_result["pictorial_id"], "real_vote_cnt": query_result["real_vote_cnt"],
"virt_vote_cnt": query_result["virt_vote_cnt"], "total_vote_cnt": total_vote_cnt})
"virt_vote_cnt": query_result["virt_vote_cnt"], "total_vote_cnt": total_vote_cnt,
"topic_add_createtime": int(time.mktime(pictorial_id.get("create_time", None).timetuple()))})
logging.info("product_brand_info" % related_billboard_list)
......@@ -342,6 +345,7 @@ class PictorialTopic(models.Model):
topic_id = models.BigIntegerField(verbose_name=u'帖子ID')
is_online = models.BooleanField(verbose_name=u"是否有效", default=True)
is_deleted = models.BooleanField(verbose_name=u'是否删除')
create_time = models.DateTimeField(verbose_name=u'创建时间', default=datetime.datetime.fromtimestamp(0))
class TopicExtra(models.Model):
......
trans2es/utils/topic_transfer.py
View file @ 4ae7e49f
......@@ -8,6 +8,7 @@ from libs.tools import tzlc
import time
import re
import datetime
from trans2es.models.user import User
from trans2es.models.topic import ExcellentTopic, TopicHomeRecommend
......
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