KassieZ commented on code in PR #1403:
URL: https://github.com/apache/doris-website/pull/1403#discussion_r1861715782


##########
ecosystem/dbt-doris-adapter.md:
##########
@@ -88,7 +88,7 @@ dbt-doris Materialization support three:
 2. table
 3. incremental
 
-#### View 
+#### View
 
 Using `view` as the materialization, Models will be rebuilt as views each time 
they are run through the create view as statement. (By default, the 
materialization method of dbt is view)

Review Comment:
   models will be rebuilt, model should be lowercase



##########
common_docs_zh/ecosystem/dbt-doris-adapter.md:
##########
@@ -86,15 +86,15 @@ dbt run
 可以登陆 doris,查看 my_first_dbt_model 和 my_second_dbt_model 的数据结果及建表语句。
 
 ### dbt-doris adapter 物化方式
-dbt-doris 的 物化方式(Materialization)支持一下三种:
+dbt-doris 的 物化方式(Materialization)支持以下三种:
 
 1. view
 
 2. table
 
 3. incremental
 
-**View** 
+**View**
 
 使用`view`作为物化模式,在 Models 每次运行时都会通过 create view as 语句重新构建为视图。(默认情况下,dbt 的物化方式为 
view)

Review Comment:
   语句建议加行内代码



##########
ecosystem/dbt-doris-adapter.md:
##########
@@ -236,7 +236,7 @@ The details of the above configuration items are as follows:
 
 [`seed`](https://docs.getdbt.com/faqs/seeds/build-one-seed) is a functional 
module used to load data files such as csv. It is a way to load files into the 
library and participate in model building, but there are the following 
precautions:
 1. Seeds should not be used to load raw data (for example, large CSV exports 
from a production database).
-2. Since seeds are version controlled, they are best suited to files that 
contain business-specific logic, for example a list of country codes or user 
IDs of employees. 
+2. Since seeds are version controlled, they are best suited to files that 
contain business-specific logic, for example a list of country codes or user 
IDs of employees.
 3. Loading CSVs using dbt's seed functionality is not performant for large 
files. Consider using `streamload` to load these CSVs into doris.

Review Comment:
   CSV(Comma-Separated Values). It is common to use "CSV files" or "CSV format" 
to refer to this file format instead of "CSVs".



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