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当数据分析和客户服务需要弹性搜索时

[英]When Elastic search is needed for data analysis and costumer service

I work with Python for a warehousing project.我使用 Python 进行仓储项目。 I can for example use in function, pandas contain function.例如,我可以在函数中使用,pandas 包含函数。 Call any text mining library like fuzzy search and stemming libraries directly in my Python code.直接在我的 Python 代码中调用任何文本挖掘库,如模糊搜索和词干库。 When and why I would call elastic search by Python and slow down all the search performance?何时以及为什么我会通过 Python 调用弹性搜索并降低所有搜索性能? Am I missing some knowledge what would be the benefit of elastic search in my case?我是否缺少一些知识,在我的情况下弹性搜索有什么好处?

Is that sth for UI people or that can benefit data analyst and data scientist?这对 UI 人员来说是什么,还是可以使数据分析师和数据科学家受益?

You are comparing two different things, pandas is a data analysis and manipulation tool, elasticsearch is a search engine where you can perform a wide range of searchs, analysis and aggregations.您正在比较两种不同的东西, pandas是一种数据分析和操作工具, elasticsearch是一种搜索引擎,您可以在其中执行广泛的搜索、分析和聚合。

It is like comparing pandas to a Oracle or a PostgreSQL databases.这就像将pandas与 Oracle 或 PostgreSQL 数据库进行比较。

While in some use cases you can achieve the same end result with both, they still are different tools and have different functions.虽然在某些用例中,您可以使用两者获得相同的最终结果,但它们仍然是不同的工具并且具有不同的功能。

If you need elasticsearch or not, and if it would improve your searchs, depend exclusively on your use case, I would recommend that you read this link to understand a little more about the tool.如果您是否需要elasticsearch ,并且它是否会改进您的搜索,完全取决于您的用例,我建议您阅读此链接以了解有关该工具的更多信息。

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