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alpha
physical
Commits
ba9eca6c
Commit
ba9eca6c
authored
Apr 22, 2019
by
lixiaofang
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Merge branch 'test' of git.wanmeizhensuo.com:alpha/physical into test
parents
32e5a81a
94907185
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Showing
2 changed files
with
166 additions
and
15 deletions
+166
-15
topic.py
search/utils/topic.py
+100
-1
topic.py
search/views/topic.py
+66
-14
No files found.
search/utils/topic.py
View file @
ba9eca6c
...
...
@@ -220,7 +220,7 @@ class TopicUtils(object):
{
"filter"
:
{
"bool"
:
{
"should"
:
{
"term"
:
{
"user_id"
:
topic_user_id
}}}},
"weight"
:
100
000
"weight"
:
5
000
}
)
query_function_score
=
{
...
...
@@ -425,6 +425,105 @@ class TopicUtils(object):
logging
.
error
(
"catch exception,err_msg:
%
s"
%
traceback
.
format_exc
())
return
[]
@classmethod
def
top_get_topic_detail_recommend_list
(
cls
,
user_id
,
topic_id
,
have_read_topic_list
,
size
,
es_cli_obj
=
None
,
index_type
=
"topic"
,
routing
=
None
,
collection_topic_tag_list
=
[],
topic_tag_list
=
[],
topic_user_id
=-
1
):
"""
:remark 帖子详情页推荐列表,缺少按时间衰减
:param user_id:
:param topic_tag_list:
:param topic_group_id:
:param topic_user_id:
:param offset:
:param size:
:return:
"""
try
:
if
not
es_cli_obj
:
es_cli_obj
=
ESPerform
.
get_cli
()
q
=
dict
()
q
[
"query"
]
=
dict
()
functions_list
=
[
{
"linear"
:
{
"create_time"
:
{
"scale"
:
"1d"
,
"decay"
:
0.5
}
}
}
]
if
len
(
topic_tag_list
)
!=
0
or
user_id
!=
-
1
:
query_function_score
=
{
"query"
:
{
"bool"
:
{
"must"
:
[
{
"range"
:
{
"content_level"
:
{
"gte"
:
3
,
"lte"
:
6
}}},
{
"term"
:
{
"is_online"
:
True
}},
{
"term"
:
{
"is_deleted"
:
False
}}
],
"must_not"
:
{
"terms"
:
{
"id"
:
have_read_topic_list
}
}
}
},
"score_mode"
:
"sum"
,
"boost_mode"
:
"sum"
,
"functions"
:
functions_list
}
else
:
query_function_score
=
{
"query"
:
{
"bool"
:
{
"must"
:
[
{
"range"
:
{
"content_level"
:
{
"gte"
:
4
,
"lte"
:
6
}}},
{
"term"
:
{
"is_online"
:
True
}},
{
"term"
:
{
"is_deleted"
:
False
}}
],
"must_not"
:
{
"terms"
:
{
"id"
:
have_read_topic_list
}
}
}
},
"score_mode"
:
"sum"
,
"boost_mode"
:
"sum"
,
"functions"
:
functions_list
}
if
len
(
topic_tag_list
)
>
0
:
query_function_score
[
"query"
][
"bool"
][
"should"
]
=
{
"terms"
:
{
"tag_list"
:
topic_tag_list
}
}
if
topic_user_id
!=
-
1
:
query_function_score
[
"query"
][
"bool"
][
"should"
]
=
{
"term"
:
{
"user_id"
:
topic_user_id
}
}
q
[
"query"
][
"function_score"
]
=
query_function_score
q
[
"_source"
]
=
{
"includes"
:
[
"id"
,
"pictorial_id"
,
"user_id"
,
"_score"
]
}
result_dict
=
ESPerform
.
get_search_results
(
es_cli_obj
,
sub_index_name
=
index_type
,
query_body
=
q
,
size
=
size
,
routing
=
routing
)
topic_id_list
=
list
()
for
item
in
result_dict
[
"hits"
]:
topic_id_list
.
append
(
item
[
"_source"
][
"id"
])
return
topic_id_list
except
:
logging
.
error
(
"catch exception,err_msg:
%
s"
%
traceback
.
format_exc
())
return
[]
@classmethod
def
get_topic_tag_id_list
(
cls
,
topic_id
,
es_cli_obj
=
None
):
"""
...
...
search/views/topic.py
View file @
ba9eca6c
...
...
@@ -265,7 +265,56 @@ def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pic
try
:
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
)
else
:
redis_key
=
"physical:topic_detail_recommend"
+
":device_id:"
+
device_id
+
"topic_id:"
+
str
(
topic_id
)
if
offset
==
0
:
have_read_topic_list
=
list
()
# redis_dict = {
# "have_read_topic_id": json.dumps(have_read_topic_list)
# }
redis_client
.
delete
(
redis_key
)
# redis_client.expire(redis_key, 60 * 60 * 24)
else
:
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_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
)
topic_user_result
=
list
()
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
=
"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
=
"4,5,6"
,
topic_tag_list
=
topic_tag_list
)
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 []
#
# redis_key = "physical:topic_detail_page_recommend" + ":user_id:" + str(user_id) + ":device_id:" + str(device_id)
# 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 []
...
...
@@ -279,21 +328,24 @@ def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pic
# result_list = TopicUtils.get_topic_detail_recommend_list(user_id, topic_id, topic_tag_list, topic_pictorial_id,
# topic_user_id, filter_topic_user_id,
# have_read_topic_list, offset, size, es_cli_obj,index_type="topic",routing="4,5,6")
result_list
=
TopicUtils
.
get_recommend_topic_ids
(
user_id
,
tag_id
=-
1
,
single_size
=
size
,
offset
=
offset
,
size
=
size
,
topic_user_id
=
topic_user_id
,
current_topic_id
=
topic_id
,
topic_tag_list
=
topic_tag_list
)
recommend_topic_ids_list
=
list
()
# if len(result_list) > 0:
# recommend_topic_ids_list = [item["_source"]["id"] for item in result_list]
recommend_topic_ids_list
.
extend
(
result_list
)
#
# have_read_topic_list.extend(recommend_topic_ids_list)
# result_list = TopicUtils.get_recommend_topic_ids(user_id, tag_id=-1, single_size=size, offset=offset, size=size,
# topic_user_id=topic_user_id, current_topic_id=topic_id,
# topic_tag_list=topic_tag_list)
#
# have_read_topic_len = len(have_read_topic_list)
# if have_read_topic_len > 5000:
# have_read_topic_list = have_read_topic_list[(have_read_topic_len - 5000):]
#
# redis_client.set(redis_key, json.dumps(have_read_topic_list))
# user_recommend_list = TopicUtils.get_recommend_topic_ids(user_id, tag_id=-1, single_size=size, offset=offset, size=size,
# topic_user_id=topic_user_id, current_topic_id=topic_id,
# topic_tag_list=topic_tag_list)
redis_dict
=
{
"have_read_topic_list"
:
json
.
dumps
(
have_read_topic_list
),
}
redis_client
.
hmset
(
redis_key
,
redis_dict
)
redis_client
.
expire
(
redis_key
,
60
*
60
*
24
)
result_list
=
[]
recommend_topic_ids_list
=
list
()
recommend_topic_ids_list
.
extend
(
topic_tag_result
)
recommend_topic_ids_list
.
extend
(
topic_user_result
)
recommend_topic_ids_list
.
extend
(
result
)
return
{
"recommend_topic_ids"
:
recommend_topic_ids_list
}
except
:
logging
.
error
(
"catch exception,err_msg:
%
s"
%
traceback
.
format_exc
())
...
...
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