update export tools

docs-2.0-en/import-export/write-tools.md

@@ -5,19 +5,21 @@
 There are many ways to write NebulaGraph {{ nebula.release }}:
 
 - Import with [the command -f](../2.quick-start/3.connect-to-nebula-graph.md): This method imports a small number of prepared nGQL files, which is suitable to prepare for a small amount of manual test data.
-- Import with [Studio](../nebula-studio/quick-start/st-ug-import-data.md): This method uses a browser to import multiple csv files of this machine. A single file cannot exceed 100 MB, and its format is limited.
-- Import with [Importer](use-importer.md): This method imports multiple csv files on a single machine with unlimited size and flexible format.
-- Import with [Exchange](nebula-exchange/about-exchange/ex-ug-what-is-exchange.md): This method imports from various distribution sources, such as Neo4j, Hive, MySQL, etc., which requires a Spark cluster.
-- Import with [Spark-connector](../connector/nebula-spark-connector.md)/[Flink-connector](../connector/nebula-flink-connector.md): This method has corresponding components (Spark/Flink) and writes a small amount of code.
+- Import with [Studio](../nebula-studio/quick-start/st-ug-import-data.md): This method uses a browser to import multiple CSV files of this machine. A single file cannot exceed 100 MB, and its format is limited.
+- Import with [Importer](use-importer.md): This method imports multiple CSV files on a single machine with unlimited size and flexible format. Suitable for scenarios with less than one billion records of data.
+- Import with [Exchange](nebula-exchange/about-exchange/ex-ug-what-is-exchange.md): This method imports from various distribution sources, such as Neo4j, Hive, MySQL, etc., which requires a Spark cluster. Suitable for scenarios with more than one billion records of data.
+- Read and write APIs with [Spark-connector](../connector/nebula-spark-connector.md)/[Flink-connector](../connector/nebula-flink-connector.md): This method requires you to write a small amount of code to make use of the APIs provided by Spark/Flink connector.
 - Import with [C++/GO/Java/Python SDK](../20.appendix/6.eco-tool-version.md): This method imports in the way of writing programs, which requires certain programming and tuning skills.
 
 The following figure shows the positions of these ways:
 
  ![image](https://docs-cdn.nebula-graph.com.cn/figures/write-choice.png)
 
-
 ## Export tools
 
-!!! enterpriseonly
+- Read and write APIs with [Spark-connector](../connector/nebula-spark-connector.md)/[Flink-connector](../connector/nebula-flink-connector.md): This method requires you to write a small amount of code to make use of the APIs provided by Spark/Flink connector.
+- Export the data in database to a CSV file or another graph space (different NebulaGraph database clusters are supported) using the export function of the Exchange.
+
+  !!! enterpriseonly
 
-    The export tool is exclusively available in the Enterprise Edition. If you require access to this version, please [contact us](mailto:[email protected]).
+        The export function is exclusively available in the Enterprise Edition. If you require access to this version, please [contact us](mailto:[email protected]).

docs-2.0-zh/import-export/write-tools.md

@@ -1,18 +1,27 @@
-# 导入工具选择
+# 导入导出工具概述
 
+## 导入工具
 
-有多种方式可以将数据写入 {{nebula.name}} {{ nebula.release }}：
+有多种方式可以将数据写入{{nebula.name}} {{ nebula.release }}：
 
-- 使用[命令行 -f 的方式](../2.quick-start/3.quick-start-on-premise/3.connect-to-nebula-graph.md)导入：可以导入少量准备好的 nGQL 文件，适合少量手工测试数据准备；
+- 使用[命令行 -f 的方式](../2.quick-start/3.quick-start-on-premise/3.connect-to-nebula-graph.md)导入：可以导入少量准备好的 nGQL 文件，适合少量手工测试数据准备。
 
-- 使用 [Studio 导入](../nebula-studio/quick-start/st-ug-import-data.md)：可以用过浏览器导入本机多个 csv 文件，格式有限制； 
+- 使用 [Studio 导入](../nebula-studio/quick-start/st-ug-import-data.md)：可以用过浏览器导入本机多个 CSV 文件，格式有限制。
 
-- 使用 [Importer 导入](use-importer.md)：导入单机多个 csv 文件，大小没有限制，格式灵活；数据量十亿级以内；
-- 使用 [Exchange 导入](nebula-exchange/about-exchange/ex-ug-what-is-exchange.md)：从 Neo4j, Hive, MySQL 等多种源分布式导入，需要有 Spark 集群；数据量十亿级以上
-- 使用 [Spark-connector](../connector/nebula-spark-connector.md)/[Flink-connector](../connector/nebula-flink-connector.md) 导入：有相应组件 (Spark/Flink)，撰写少量代码；
+- 使用 [Importer 导入](use-importer.md)：导入单机多个 CSV 文件，大小没有限制，格式灵活。适合十亿条数据以内的场景。
+- 使用 [Exchange 导入](nebula-exchange/about-exchange/ex-ug-what-is-exchange.md)：从 Neo4j、Hive、MySQL 等多种源分布式导入，需要有 Spark 集群。适合十亿条数据以上的场景。
+- 使用 [Spark-connector](nebula-spark-connector.md)/[Flink-connector](nebula-flink-connector.md) 读写 API：这种方式需要编写少量代码来使用 Spark/Flink 连接器提供的 API。
 - 使用 [C++/GO/Java/Python SDK](../20.appendix/6.eco-tool-version.md)：编写程序的方式导入，需要有一定编程和调优能力。
 
 下图给出了几种方式的定位：
 
  ![image](https://docs-cdn.nebula-graph.com.cn/figures/write-choice.png)
 
+## 导出工具
+
+- 使用 [Spark-connector](nebula-spark-connector.md)/[Flink-connector](nebula-flink-connector.md) 读写 API：这种方式需要编写少量代码来使用 Spark/Flink 连接器提供的 API。
+- 使用 Exchange 导出功能将数据导出至 CSV 文件或另一个图空间（支持不同 {{nebula.name}} 集群）中。
+
+  !!! enterpriseonly
+
+        仅企业版 Exchange 提供导出功能。如需企业版，请[联系我们](https://discuss-cdn.nebula-graph.com.cn/uploads/default/original/3X/d/1/d1e1b0e55e29776ee60e3f34c843474ec884393d.jpeg)。