ElasticSearch Doc值的缺点是什么 [英] What are the disadvantages of ElasticSearch Doc Values

问题描述

文档声称：

10–25% slower than in-memory fielddata

和

It is possible that doc values will become the default format in the near future

除了速度略有降低外，还有哪些缺点

Besides this slight reduction in speed, what are the downsides of using doc values in all of the properties?

谢谢！

推荐答案

趋势是在任何可能的地方都使用 doc_values ，因为它们的性能越来越强于字段数据（尤其是从ES 1.4开始）。目前的缺点之一是您不能将它们与已分析的字符串字段和布尔字段一起使用。另一个缺点是，如果您仍在使用方面，请分别使用。 Kibana 3，因为两者都没有利用doc值，但是您可以分别迁移到聚合。升级到Kibana 4，所以这并不是真正的问题。

The trend is to use doc_values whenever possible, as they are getting increasingly more performant than field data (especially since ES 1.4). One of the downsides for now is that you cannot use them with analyzed string fields and boolean fields. Another downside is if you're still using facets, resp. Kibana 3, as both are not leveraging doc values, but you can either migrate to aggregations, resp. upgrade to Kibana 4, so it's not really an issue.

查看此，解释了文档值与字段数据的来龙去脉。

Check out this excellent blog post by Chris Earle which explains the ins and outs of doc values vs fielddata.

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