Kibana User Guide [4.2] » Introduction

Introduction

Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis and visualize your data in a variety of charts, tables, and maps.

Kibana是一个开源的分析和可视化平台，设计它的目的是和ElasticSearch一起工作。你可以使用Kibana和存储在ES索引中的数据进行搜索，查看。你可以很容易进行先进的数据分析，将你的数据以图表、表格和地图的形式进行可视化。

Kibana makes it easy to understand large volumes of data. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time.

Kibana的存在让理解大规模数据变得简单。Kibana的简单性和基于浏览器界面的特性使你能够很快创建和分享动态仪表盘，这个仪表盘能够实时响应你对ES做的修改。

Setting up Kibana is a snap. You can install Kibana and start exploring your Elasticsearch indices in minutes — no code, no additional infrastructure required.

设置Kibana是很容易的。只需要花费几分钟的时间，你就可以按照安装Kibana并浏览你的ES索引，不需要代码，不需要额外的设施支撑。

This guide describes how to use Kibana 4.2. For information about what’s new in Kibana 4.2, see the release notes. For earlier versions of Kibana 4, see the Kibana 4.1 User Guide. For information about Kibana 3, see the Kibana 3 User Guide.

这篇说明书是描述如何使用Kibana4.2。想要查看Kibana 4.2中的新东西，请查看release notes。想要查看Kibana 4以前的版本，请查看Kibana 4.1 User Guide。想要查看Kibana 3的信息，请查看Kibana 3 User Guide.

Data Discovery and Visualization

数据挖掘及可视化

Let’s take a look at how you might use Kibana to explore and visualize data. We’ve indexed some data from Transport for London (TFL) that shows one week of transit (Oyster) card usage.

让我们看一下你能使用Kibana做哪些数据挖掘和可视化工作。我们已经得到了一些伦敦交通局（TFL）的数据，然后展现一周数据的使用案例。

From Kibana’s Discover page, we can submit search queries, filter the results, and examine the data in the returned documents. For example, we can get all trips completed by the Tube during the week by excluding incomplete trips and trips by bus:

从Kibana的Discover页面，我们可以提交查询请求，过滤结果，对返回文档中的数据进行检查。例如，我们可以得到一周中只乘坐地铁的乘车方式，通过排除掉部分乘坐地铁的和乘坐公交的乘车方式。

Right away, we can see the peaks for the morning and afternoon commute hours in the histogram. By default, the Discover page also shows the first 500 entries that match the search criteria. You can change the time filter, interact with the histogram to drill down into the data, and view the details of particular documents. For more information about exploring your data from the Discover page, see Discover.

另外，我们可以通过把数据变成柱状图，看到上午和下午乘车的高峰。在默认情况下，Discover页面也展示了符合搜索标准的前500个信息。你可以改变时间过滤器，和柱状图进行交互，来向下挖取信息，查看特殊文档的细节。如果你想要从Discover页面搜索到更多的信息，请查看Discover。

You can construct visualizations of your search results from the Visualization page. Each visualization is associated with a search. For example, we can create a histogram that shows the weekly London commute traffic via the Tube using our previous search. The Y-axis shows the number of trips. The X-axis shows the day and time. By adding a sub-aggregation, we can see the top 3 end stations during each hour:

你可以构建你搜索结果的可视化展示从Visualization界面。每一个可视化展示都和一个搜索相关。例如，你可以使用上面提到的搜索，创建一个柱状图，来展现每周伦敦使用地铁的上下班交通情况。Y轴展现了交通量。X轴展现了日期和时间。通过增加一个地铁聚集（地铁站？），你可以查看每小时排名前三的终点站。

You can save and share visualizations and combine them into dashboards to make it easy to correlate related information. For example, we could create a dashboard that displays several visualizations of the TFL data:

你可以保持和分析可视化结果，把它们放到仪表盘内进行比较，使它容易和相关信息进行关联。例如，我们可以创建一个仪表盘，来展现TFL数据的一些可视化结果。

For more information about creating and sharing visualizations and dashboards, see the Visualize andDashboard topics. A complete tutorial covering several aspects of Kibana’s functionality is also available.

关于创建分享可视化结果和仪表盘的更多信息，可以查看 Visualize 和Dashboard 主题。一个覆盖更多Kibana性能的参考文档也可以从那里得到。

备注：

材料来自elastic官网。

地址：

https://www.elastic.co/guide/en/kibana/current/introduction.html#introduction