Comments (4)
ElasticSearch的index,你可以查下官方文档,同一个索引下,文档量达到多少多少,搜索性能下降比例,其实很简单,按照业务分就好,商品相关的叫product-index,里边设置不同的type,会员相关的,收藏夹啊关注啊粉丝互动啊,叫member-index,其他类推,最好按照业务分,这样每个index下几百万几千万数据,没什么压力的。
至于数据同步问题嘛,目前我的处理是写到业务里,业务有修改,增加,删除触发ElasticSearch内数据的变更,这种同步中间件基本没有吧,反正我是不知道。
我是这个“D2C全球好设计”这个电商app后端的主负责,我们从单机项目,dubbo的SOA,到现在的微服务,大概凑活,只能说尽量学习阿里啊京东的解决方案,肯定没人家专业
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仅仅是电商场景应用,关系型数据库Mysql,主要存业务数据,需要严格控制事务的,如订单,会员,商品等信息,Mysql面对体量大的数据查询压力巨大,高并发下容易挂,MongoDB支持体量大,便于查询,适合存放社交信息如评论啊,和一些用户操作埋点的数据,这些数据不严格要求事务,还可以存站点的内容文章等信息
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Elasticsearch存一些需要全站搜索聚合的数据,可直接同步冗余处理,可能原先Mysql+MongoDB里都有的数据,经过处理加工推导Elasticsearch里,比如京东的商品查询,品牌查询,分类查询啊,或者社交电商的部分关注啊,买家秀啊等查询,当然还能做一些操作日志聚合
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嗯,谢谢你。
对于电商系统,ElasticSearch创建一个Index做为统一入口合适,还是分为多个Index合适。
关于Mysql+MongoDB处理加工到ES, 离线相对容易很多,如果实时同步,有符合的中间件吗?
非常感谢
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很中肯,很受用。 持续向你学习,谢谢你的回复。
未来消费升级,品味升级。设计师电商会越来越好。祝愿D2C越来越好。
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