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Update ex-ug-import-from-kafka.md #890

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14 changes: 9 additions & 5 deletions docs-2.0/nebula-exchange/use-exchange/ex-ug-import-from-kafka.md
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Expand Up @@ -76,6 +76,10 @@

### 步骤 2：修改配置文件

!!! note

如果部分数据存储在Kafka的value域内，需要自行修改源码，从Kafka中获取value域，将value通过from_json函数解析，然后作为Dataframe返回。

编译Exchange后，复制`target/classes/application.conf`文件设置Kafka数据源相关的配置。在本示例中，复制的文件名为`kafka_application.conf`。各个配置项的详细说明请参见[配置说明](../parameter-reference/ex-ug-parameter.md)。

```conf
Expand Down Expand Up @@ -142,8 +146,8 @@
# 消息类别。
topic: "topic_name1"

# kafka数据有固定的字段名称：key、value、topic、partition、offset、timestamp、timestampType。
# 如果需要指定多个列名称，用英文逗号（,）隔开。
# Kafka数据有固定的域名称：key、value、topic、partition、offset、timestamp、timestampType。
# Spark读取为DataFrame后，如果需要指定多个字段，用英文逗号（,）隔开。
# 在fields里指定字段名称，例如用key对应Nebula中的name， value对应Nebula中的age，示例如下：
fields: [key,value]
nebula.fields: [name,age]
Expand Down Expand Up @@ -205,8 +209,8 @@
# 消息类别。
topic: "topic_name3"

# kafka数据有固定的字段名称：key、value、topic、partition、offset、timestamp、timestampType。
# 如果需要指定多个列名称，用英文逗号（,）隔开。
# Kafka数据有固定的域名称：key、value、topic、partition、offset、timestamp、timestampType。
# Spark读取为DataFrame后，如果需要指定多个字段，用英文逗号（,）隔开。
# 在fields里指定字段名称，例如用key对应Nebula中的degree，示例如下：
fields: [key]
nebula.fields: [degree]
Expand Down Expand Up @@ -293,4 +297,4 @@ GO FROM "player100" OVER follow;

### 步骤 5：（如有）在Nebula Graph中重建索引

导入数据后，用户可以在Nebula Graph中重新创建并重建索引。详情请参见[索引介绍](../../3.ngql-guide/14.native-index-statements/README.md)。
导入数据后，用户可以在Nebula Graph中重新创建并重建索引。详情请参见[索引介绍](../../3.ngql-guide/14.native-index-statements/README.md)。