We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
服务需要支持对不同类型的document进行索引。目前我们需要支持3种类型的document:user(用户),venue(地点),fabula(故事)。 而每个document又有不同的field。以venue为例,文本类型的field有name,alias,address,pitch等几个字段;另外还有一些数字类型的field,如CityId(所属城市), category(所属类别),AverageCost(平均消费),LikersCount(收藏数),以及需要动态计算的Distance(与当前位置的距离),数字类型的field用在filter和sort。
search时
The text was updated successfully, but these errors were encountered:
明白了。所以我们需要支持半结构化的文档——既有结构化的内容,用来做filter;也要有分结构化的内容,比如文本描述。之前我们做广告系统的retrieval system的时候也是有类似的需求的。我找原来的同事问问,尽量回忆一下当时踩过的坑,再跟大家分享。更重要的是,今晚会上向慷慷了解和学习目前的做法。 @chenkaitopic @brjg @cwtopic
Sorry, something went wrong.
No branches or pull requests
服务需要支持对不同类型的document进行索引。目前我们需要支持3种类型的document:user(用户),venue(地点),fabula(故事)。
而每个document又有不同的field。以venue为例,文本类型的field有name,alias,address,pitch等几个字段;另外还有一些数字类型的field,如CityId(所属城市), category(所属类别),AverageCost(平均消费),LikersCount(收藏数),以及需要动态计算的Distance(与当前位置的距离),数字类型的field用在filter和sort。
search时
The text was updated successfully, but these errors were encountered: