diff --git a/docs/content.zh/docs/connectors/datastream/formats/hadoop.md b/docs/content.zh/docs/connectors/datastream/formats/hadoop.md
index e2b2c9fd85794..d18cc73f5cec5 100644
--- a/docs/content.zh/docs/connectors/datastream/formats/hadoop.md
+++ b/docs/content.zh/docs/connectors/datastream/formats/hadoop.md
@@ -30,10 +30,9 @@ under the License.
 
 ## Project Configuration
 
-Support for Hadoop is contained in the `flink-hadoop-compatibility`
-Maven module.
+对 Hadoop 的支持位于 `flink-hadoop-compatibility` Maven 模块中。
 
-Add the following dependency to your `pom.xml` to use hadoop
+将以下依赖添加到 `pom.xml` 中使用 hadoop
 
 ```xml
 <dependency>
@@ -43,8 +42,7 @@ Add the following dependency to your `pom.xml` to use hadoop
 </dependency>
 ```
 
-If you want to run your Flink application locally (e.g. from your IDE), you also need to add
-a `hadoop-client` dependency such as:
+如果你想在本地运行你的 Flink 应用（例如在 IDE 中），你需要按照如下所示将 `hadoop-client` 依赖也添加到 `pom.xml`：
 
 ```xml
 <dependency>
@@ -57,20 +55,13 @@ a `hadoop-client` dependency such as:
 
 ## Using Hadoop InputFormats
 
-To use Hadoop `InputFormats` with Flink the format must first be wrapped
-using either `readHadoopFile` or `createHadoopInput` of the
-`HadoopInputs` utility class.
-The former is used for input formats derived
-from `FileInputFormat` while the latter has to be used for general purpose
-input formats.
-The resulting `InputFormat` can be used to create a data source by using
-`ExecutionEnvironmen#createInput`.
+在 Flink 中使用 Hadoop `InputFormats`，必须首先使用 `HadoopInputs` 工具类的 `readHadoopFile` 或 `createHadoopInput` 包装 Input Format。
+前者用于从 `FileInputFormat` 派生的 Input Format，而后者必须用于通用的 Input Format。
+生成的 `InputFormat` 可通过使用 `ExecutionEnvironmen#createInput` 创建数据源。
 
-The resulting `DataStream` contains 2-tuples where the first field
-is the key and the second field is the value retrieved from the Hadoop
-InputFormat.
+生成的 `DataStream` 包含 2 元组，其中第一个字段是键，第二个字段是从 Hadoop `InputFormat` 接收的值。
 
-The following example shows how to use Hadoop's `TextInputFormat`.
+下面的示例展示了如何使用 Hadoop 的 `TextInputFormat`。
 
 {{< tabs "baa59ec9-046e-4fe3-a2db-db5ee09d0635" >}}
 {{< tab "Java" >}}
@@ -82,7 +73,7 @@ DataStream<Tuple2<LongWritable, Text>> input =
     env.createInput(HadoopInputs.readHadoopFile(new TextInputFormat(),
                         LongWritable.class, Text.class, textPath));
 
-// Do something with the data.
+// 对数据进行一些处理。
 [...]
 ```
 
@@ -96,7 +87,7 @@ val input: DataStream[(LongWritable, Text)] =
   env.createInput(HadoopInputs.readHadoopFile(
                     new TextInputFormat, classOf[LongWritable], classOf[Text], textPath))
 
-// Do something with the data.
+// 对数据进行一些处理。
 [...]
 ```
 
@@ -105,32 +96,29 @@ val input: DataStream[(LongWritable, Text)] =
 
 ## Using Hadoop OutputFormats
 
-Flink provides a compatibility wrapper for Hadoop `OutputFormats`. Any class
-that implements `org.apache.hadoop.mapred.OutputFormat` or extends
-`org.apache.hadoop.mapreduce.OutputFormat` is supported.
-The OutputFormat wrapper expects its input data to be a DataSet containing
-2-tuples of key and value. These are to be processed by the Hadoop OutputFormat.
+Flink 为 Hadoop `OutputFormats` 提供了一个兼容性包装器。支持任何实现 `org.apache.hadoop.mapred.OutputFormat` 或扩展 `org.apache.hadoop.mapreduce.OutputFormat` 的类。
+`OutputFormat` 包装器期望其输入数据是包含键和值的 2-元组的 DataSet。这些将由 Hadoop `OutputFormat` 处理。
 
-The following example shows how to use Hadoop's `TextOutputFormat`.
+下面的示例展示了如何使用 Hadoop 的 `TextOutputFormat`。
 
 {{< tabs "d4af1c52-0e4c-490c-8c35-e3d60b1b52ee" >}}
 {{< tab "Java" >}}
 
 ```java
-// Obtain the result we want to emit
+// 获取我们希望发送的结果
 DataStream<Tuple2<Text, IntWritable>> hadoopResult = [...]
 
-// Set up the Hadoop TextOutputFormat.
+// 设置 the Hadoop TextOutputFormat。
 HadoopOutputFormat<Text, IntWritable> hadoopOF =
-  // create the Flink wrapper.
+  // 创建 Flink wrapper.
   new HadoopOutputFormat<Text, IntWritable>(
-    // set the Hadoop OutputFormat and specify the job.
+    // 设置 Hadoop OutputFormat 并指定 job。
     new TextOutputFormat<Text, IntWritable>(), job
   );
 hadoopOF.getConfiguration().set("mapreduce.output.textoutputformat.separator", " ");
 TextOutputFormat.setOutputPath(job, new Path(outputPath));
 
-// Emit data using the Hadoop TextOutputFormat.
+// 使用 Hadoop TextOutputFormat 发送数据。
 hadoopResult.output(hadoopOF);
 ```
 
@@ -138,7 +126,7 @@ hadoopResult.output(hadoopOF);
 {{< tab "Scala" >}}
 
 ```scala
-// Obtain your result to emit.
+// 获取我们希望发送的结果
 val hadoopResult: DataStream[(Text, IntWritable)] = [...]
 
 val hadoopOF = new HadoopOutputFormat[Text,IntWritable](