排版布局测试

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<!--- [![Inspections Status](https://img.shields.io/teamcity/http/teamcity.jetbrains.com/s/OpenSourceProjects_Druid_Inspections.svg?label=TeamCity%20inspections)](https://teamcity.jetbrains.com/viewType.html?buildTypeId=OpenSourceProjects_Druid_Inspections) --> <!--- [![Inspections Status](https://img.shields.io/teamcity/http/teamcity.jetbrains.com/s/OpenSourceProjects_Druid_Inspections.svg?label=TeamCity%20inspections)](https://teamcity.jetbrains.com/viewType.html?buildTypeId=OpenSourceProjects_Druid_Inspections) -->
--- ---
[中文文档](https://druid.apache.org/docs/latest/design/) |
[官方网站](https://druid.apache.org/) | [Website](https://druid.apache.org/) |
[官方文档(英文)](https://druid.apache.org/docs/latest/design/) | [Documentation](https://druid.apache.org/docs/latest/design/) |
[开发者邮件地址](https://lists.apache.org/list.html?dev@druid.apache.org) | [Developer Mailing List](https://lists.apache.org/list.html?dev@druid.apache.org) |
[用户邮件地址](https://groups.google.com/forum/#!forum/druid-user) | [User Mailing List](https://groups.google.com/forum/#!forum/druid-user) |
[Slack](https://s.apache.org/slack-invite) | [Slack](https://s.apache.org/slack-invite) |
[下载地址](https://druid.apache.org/downloads.html) [Twitter](https://twitter.com/druidio) |
[Download](https://druid.apache.org/downloads.html)
--- ---
## Apache Druid ## Apache Druid
Apache Druid 是一个高性能的实时分析型数据库。
### 云原生、流原生的分析型数据库 Druid is a high performance real-time analytics database. Druid's main value add is to reduce time to insight and action.
Druid专为需要快速数据查询与摄入的工作流程而设计在即时数据可见性、即席查询、运营分析以及高并发等方面表现非常出色。
在实际中[众多场景](Misc/usercase.md)下数据仓库解决方案中可以考虑将Druid当做一种开源的替代解决方案。 Druid is designed for workflows where fast queries and ingest really matter. Druid excels at powering UIs, running operational (ad-hoc) queries, or handling high concurrency. Consider Druid as an open source alternative to data warehouses for a variety of use cases.
### 可轻松与现有的数据管道进行集成 ### Getting started
Druid原生支持从[Kafka](http://kafka.apache.org/)、[Amazon Kinesis](https://aws.amazon.com/cn/kinesis/)等消息总线中流式的消费数据,也同时支持从[HDFS](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html)、[Amazon S3](https://aws.amazon.com/cn/s3/)等存储服务中批量的加载数据文件。
### 较传统方案提升近百倍的效率 You can get started with Druid with our [local](https://druid.apache.org/docs/latest/tutorials/quickstart.html) or [Docker](http://druid.apache.org/docs/latest/tutorials/docker.html) quickstart.
Druid创新地在架构设计上吸收和结合了[数据仓库](https://en.wikipedia.org/wiki/Data_warehouse)、[时序数据库](https://en.wikipedia.org/wiki/Time_series_database)以及[检索系统](https://en.wikipedia.org/wiki/Search_engine_(computing))的优势,在已经完成的[基准测试](https://imply.io/post/performance-benchmark-druid-presto-hive)中展现出来的性能远远超过数据摄入与查询的传统解决方案。
### 解锁了一种新型的工作流程 Druid provides a rich set of APIs (via HTTP and [JDBC](https://druid.apache.org/docs/latest/querying/sql.html#jdbc)) for loading, managing, and querying your data.
Druid为点击流、APM、供应链、网络监测、市场营销以及其他事件驱动类型的数据分析解锁了一种[新型的查询与工作流程](Misc/usercase.md),它专为实时和历史数据高效快速的即席查询而设计。 You can also interact with Druid via the [built-in console](https://druid.apache.org/docs/latest/operations/druid-console.html) (shown below).
### 可部署在AWS/GCP/Azure,混合云,Kubernetes, 以及裸机上 #### Load data
无论在云上还是本地Druid可以轻松的部署在商用硬件上的任何*NIX环境。部署Druid也是非常简单的包括集群的扩容或者下线都也同样很简单。
> [!TIP] [![data loader Kafka](https://user-images.githubusercontent.com/177816/65819337-054eac80-e1d0-11e9-8842-97b92d8c6159.gif)](https://druid.apache.org/docs/latest/ingestion/index.html)
> 在国内Druid的使用者越来越多但是并没有一个很好的中文版本的使用文档。 本文档根据Apache Druid官方文档0.20.1版本进行翻译目前托管在Github上欢迎更多的Druid使用者以及爱好者加入翻译行列为国内的使用者提供一个高质量的中文版本使用文档。
Load [streaming](https://druid.apache.org/docs/latest/ingestion/index.html#streaming) and [batch](https://druid.apache.org/docs/latest/ingestion/index.html#batch) data using a point-and-click wizard to guide you through ingestion setup. Monitor one off tasks and ingestion supervisors.
#### Manage the cluster
[![management](https://user-images.githubusercontent.com/177816/65819338-08499d00-e1d0-11e9-80fe-faee9e9468cb.gif)](https://druid.apache.org/docs/latest/ingestion/data-management.html)
Manage your cluster with ease. Get a view of your [datasources](https://druid.apache.org/docs/latest/design/architecture.html), [segments](https://druid.apache.org/docs/latest/design/segments.html), [ingestion tasks](https://druid.apache.org/docs/latest/ingestion/tasks.html), and [services](https://druid.apache.org/docs/latest/design/processes.html) from one convenient location. All powered by [SQL systems tables](https://druid.apache.org/docs/latest/querying/sql.html#metadata-tables), allowing you to see the underlying query for each view.
#### Issue queries
[![query view combo](https://user-images.githubusercontent.com/177816/65819341-0c75ba80-e1d0-11e9-9730-0f2d084defcc.gif)](https://druid.apache.org/docs/latest/querying/sql.html)
Use the built-in query workbench to prototype [DruidSQL](https://druid.apache.org/docs/latest/querying/sql.html) and [native](https://druid.apache.org/docs/latest/querying/querying.html) queries or connect one of the [many tools](https://druid.apache.org/libraries.html) that help you make the most out of Druid.
### Documentation
You can find the [documentation for the latest Druid release](https://druid.apache.org/docs/latest/) on
the [project website](https://druid.apache.org).
If you would like to contribute documentation, please do so under
`/docs` in this repository and submit a pull request.
### Community
Community support is available on the
[druid-user mailing list](https://groups.google.com/forum/#!forum/druid-user), which
is hosted at Google Groups.
Development discussions occur on [dev@druid.apache.org](https://lists.apache.org/list.html?dev@druid.apache.org), which
you can subscribe to by emailing [dev-subscribe@druid.apache.org](mailto:dev-subscribe@druid.apache.org).
Chat with Druid committers and users in real-time on the `#druid` channel in the Apache Slack team. Please use [this invitation link to join the ASF Slack](https://s.apache.org/slack-invite), and once joined, go into the `#druid` channel.
### Building from source
Please note that JDK 8 is required to build Druid.
For instructions on building Druid from source, see [docs/development/build.md](docs/development/build.md)
### Contributing
Please follow the [community guidelines](https://druid.apache.org/community/) for contributing.
For instructions on setting up IntelliJ [dev/intellij-setup.md](dev/intellij-setup.md)
### License
[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)