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Update README.md #309

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9 changes: 6 additions & 3 deletions README.md
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Expand Up @@ -2,7 +2,7 @@

[![Join the chat at https://gitter.im/interestinglab_waterdrop/Lobby](https://badges.gitter.im/interestinglab_waterdrop/Lobby.svg)](https://gitter.im/interestinglab_waterdrop/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

Waterdrop 是一个`非常易用`，`高性能`，能够应对`海量数据`的`实时`数据处理产品，构建于Apache Spark之上。
Waterdrop 是一个`非常易用`，`高性能`、支持`实时流式`和`离线批处理`的`海量数据`处理产品，架构于`Apache Spark` 和 `Apache Flink`之上。

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Expand Down Expand Up @@ -85,12 +85,15 @@ Elasticsearch, File, Hdfs, Jdbc, Kafka, Mysql, S3, Stdout, 自行开发的Output

## 环境依赖

需要以下Spark集群环境的任意一种：
1. java运行环境，java >= 8

2. 如果您要在集群环境中运行Waterdrop，那么需要以下Spark集群环境的任意一种：

* Spark on Yarn
* Spark Standalone
* Spark on Mesos

如果您的数据量较小或者只是做功能验证，也可以仅使用local模式启动，无需集群环境。
如果您的数据量较小或者只是做功能验证，也可以仅使用`local`模式启动，无需集群环境，Waterdrop支持单机运行。

## 文档

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9 changes: 6 additions & 3 deletions docs/zh-cn/README.md
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[![Join the chat at https://gitter.im/interestinglab_waterdrop/Lobby](https://badges.gitter.im/interestinglab_waterdrop/Lobby.svg)](https://gitter.im/interestinglab_waterdrop/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

Waterdrop 是一个`非常易用`，`高性能`，能够应对`海量数据`的`实时`数据处理产品，构建于Apache Spark之上。
Waterdrop 是一个`非常易用`，`高性能`、支持`实时流式`和`离线批处理`的`海量数据`处理产品，架构于`Apache Spark` 和 `Apache Flink`之上。

---

Expand Down Expand Up @@ -78,12 +78,15 @@ Elasticsearch, File, Hdfs, Jdbc, Kafka, Mysql, S3, Stdout, 自行开发的Output

## 环境依赖

需要以下Spark集群环境的任意一种：
1. java运行环境，java >= 8

2. 如果您要在集群环境中运行Waterdrop，那么需要以下Spark集群环境的任意一种：

* Spark on Yarn
* Spark Standalone
* Spark on Mesos

如果您的数据量较小或者只是做功能验证，也可以仅使用local模式启动，无需集群环境。
如果您的数据量较小或者只是做功能验证，也可以仅使用`local`模式启动，无需集群环境，Waterdrop支持单机运行。

## [配置/文档](zh-cn/configuration/base)

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