Update docs for version 1.2.0

README.en-US.md

@@ -32,16 +32,16 @@ Welcome everyone to join the Alink open source user group to communicate.
 
 About package names and versions:
   - PyAlink provides different Python packages for Flink versions that Alink supports: 
-  package `pyalink` always maintains Alink Python API against the latest Flink version, which is 1.10, 
-  while `pyalink-flink-***` support old-version Flink, which are `pyalink-flink-1.9` for now. 
-  - The version of python packages always follows Alink Java version, like `1.1.0`.
+  package `pyalink` always maintains Alink Python API against the latest Flink version, which is 1.11, 
+  while `pyalink-flink-***` support old-version Flink, which are `pyalink-flink-1.10` and `pyalink-flink-1.9` for now. 
+  - The version of python packages always follows Alink Java version, like `1.2.0`.
 
 Installation steps:
 
 1. Make sure the version of python3 on your computer is 3.6 or 3.7.
 2. Make sure Java 8 is installed on your computer.
 3. Use pip to install:
-  `pip install pyalink` or `pip install pyalink-flink-1.9`.
+  `pip install pyalink`, `pip install pyalink-flink-1.10` or `pip install pyalink-flink-1.9`.
 
 
 Potential issues:
@@ -50,14 +50,15 @@ Potential issues:
 If `pyalink` or `pyalink-flink-***` was/were installed, please use `pip uninstall pyalink` or `pip uninstall pyalink-flink-***` to remove them.
 
 2. If `pip install` is slow of failed, refer to [this article](https://segmentfault.com/a/1190000006111096) to change the pip source, or use the following download links:
-   - Flink 1.10：[Link](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.1.2.post0/pyalink-1.1.2.post0-py3-none-any.whl) (MD5: 6bf3a50a4437116793149ead57d9793c)
-   - Flink 1.9: [Link](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.1.2.post0/pyalink_flink_1.9-1.1.2.post0-py3-none-any.whl) (MD5: e6d2a0ba3549662d77b51a4a37483479)
+   - Flink 1.11：[Link](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.2.0/pyalink-1.2.0-py3-none-any.whl) (MD5: 8a38e8009712afcbf5ecdb297db3c8ac)
+   - Flink 1.10：[Link](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.2.0/pyalink_flink_1.10-1.2.0-py3-none-any.whl) (MD5: 8a38e8009712afcbf5ecdb297db3c8ac)
+   - Flink 1.9: [Link](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.2.0/pyalink_flink_1.9-1.2.0-py3-none-any.whl) (MD5: 2f25eec02a692661c0f0f3a89e5c2f0c)
 3. If multiple version of Python exist, you may need to use a special version of `pip`, like `pip3`;
 If Anaconda is used, the command should be run in Anaconda prompt. 
 
 ### Start using: 
 -------
-We recommend using Jupyter Notebook to use PyAlink to provide a better experience.
+You can start using PyAlink with Jupyter Notebook to provide a better experience.
 
 Steps for usage: 
 
@@ -70,7 +71,7 @@ Steps for usage:
 
    ```useLocalEnv(parallism, flinkHome=None, config=None)```.
 
-   Among them, the parameter  ```parallism```  indicates the degree of parallelism used for execution;```flinkHome``` is the full path of flink,and the default flink-1.9.0 path of PyAlink is used; ```config``` is the configuration parameter accepted by Flink. After running, the following output appears, indicating that the initialization of the running environment is successful.
+   Among them, the parameter  ```parallism```  indicates the degree of parallelism used for execution;```flinkHome``` is the full path of flink, and usually no need to set; ```config``` is the configuration parameter accepted by Flink. After running, the following output appears, indicating that the initialization of the running environment is successful.
 ```
 JVM listening on ***
 Python listening on ***
@@ -87,19 +88,19 @@ print(df)
 
 ### Write code: 
 ------
-In PyAlink, the interface provided by the algorithm component is basically the same as the Java API, that is, an algorithm component is created through the default construction method, then the parameters are set through ```setXXX```, and other components are connected through ```link / linkTo / linkFrom```.
+In PyAlink, the interface provided by the algorithm component is basically the same as the Java APIs, that is, an algorithm component is created through the default construction method, then the parameters are set through ```setXXX```, and other components are connected through ```link / linkTo / linkFrom```.
 
-Here, Jupyter's auto-completion mechanism can be used to provide writing convenience.
+Here, Jupyter Notebook's auto-completion mechanism can be used to provide writing convenience.
 
 For batch jobs, you can trigger execution through methods such as ```print / collectToDataframe / collectToDataframes``` of batch components or ```BatchOperator.execute ()```; for streaming jobs, start the job with ```StreamOperator.execute ()```.
 
 ### More usage: 
 ------
- - [PyAlink Tutorial](docs/pyalink/pyalink-overview.md)
  - [Interchange between DataFrame and Operator](docs/pyalink/pyalink-dataframe.md)
  - [StreamOperator data preview](docs/pyalink/pyalink-stream-operator-preview.md)
  - [UDF/UDTF/SQL usage](docs/pyalink/pyalink-udf.md)
  - [Use with PyFlink](docs/pyalink/pyalink-pyflink.md)
+ - [PyAlink Q&A](docs/pyalink/pyalink-qa.md)
 
 ## Java API Manual
 
@@ -126,12 +127,31 @@ Pipeline pipeline = new Pipeline().add(va).add(kMeans);
 pipeline.fit(data).transform(data).print();
 ```
 
+### With Flink-1.11
+```xml
+<dependency>
+    <groupId>com.alibaba.alink</groupId>
+    <artifactId>alink_core_flink-1.11_2.11</artifactId>
+    <version>1.2.0</version>
+</dependency>
+<dependency>
+    <groupId>org.apache.flink</groupId>
+    <artifactId>flink-streaming-scala_2.11</artifactId>
+    <version>1.11.0</version>
+</dependency>
+<dependency>
+    <groupId>org.apache.flink</groupId>
+    <artifactId>flink-table-planner_2.11</artifactId>
+    <version>1.11.0</version>
+</dependency>
+```
+
 ### With Flink-1.10
 ```xml
 <dependency>
     <groupId>com.alibaba.alink</groupId>
     <artifactId>alink_core_flink-1.10_2.11</artifactId>
-    <version>1.1.2</version>
+    <version>1.2.0</version>
 </dependency>
 <dependency>
     <groupId>org.apache.flink</groupId>
@@ -151,7 +171,7 @@ pipeline.fit(data).transform(data).print();
 <dependency>
     <groupId>com.alibaba.alink</groupId>
     <artifactId>alink_core_flink-1.9_2.11</artifactId>
-    <version>1.1.2</version>
+    <version>1.2.0</version>
 </dependency>
 <dependency>
     <groupId>org.apache.flink</groupId>
@@ -171,8 +191,8 @@ Run Alink Algorithm with a Flink Cluster
 
 1. Prepare a Flink Cluster:
 ```shell
-  wget https://archive.apache.org/dist/flink/flink-1.10.0/flink-1.10.0-bin-scala_2.11.tgz
-  tar -xf flink-1.10.0-bin-scala_2.11.tgz && cd flink-1.10.0
+  wget https://archive.apache.org/dist/flink/flink-1.11.0/flink-1.11.0-bin-scala_2.11.tgz
+  tar -xf flink-1.11.0-bin-scala_2.11.tgz && cd flink-1.11.0
   ./bin/start-cluster.sh
 ```
 
@@ -185,7 +205,7 @@ Run Alink Algorithm with a Flink Cluster
 3. Run Java examples:
 ```shell
   ./bin/flink run -p 1 -c com.alibaba.alink.ALSExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
-  # ./bin/flink run -p 2 -c com.alibaba.alink.GBDTExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
-  # ./bin/flink run -p 2 -c com.alibaba.alink.KMeansExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
+  # ./bin/flink run -p 1 -c com.alibaba.alink.GBDTExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
+  # ./bin/flink run -p 1 -c com.alibaba.alink.KMeansExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
 ```
 

README.md

@@ -31,37 +31,37 @@
 包名和版本说明：
 
   - PyAlink 根据 Alink 所支持的 Flink 版本提供不同的 Python 包：
-其中，`pyalink` 包对应为 Alink 所支持的最新 Flink 版本，而 `pyalink-flink-***` 为旧版本的 Flink 版本，当前提供 `pyalink-flink-1.9`。
-  - Python 包的版本号与 Alink 的版本号一致，例如`1.1.0`。
+其中，`pyalink` 包对应为 Alink 所支持的最新 Flink 版本，当前为 1.11，而 `pyalink-flink-***` 为旧版本的 Flink 版本，当前提供 `pyalink-flink-1.10` 和 `pyalink-flink-1.9`。
+  - Python 包的版本号与 Alink 的版本号一致，例如`1.2.0`。
 
 安装步骤：
 1. 确保使用环境中有Python3，版本限于 3.6 和 3.7。
 2. 确保使用环境中安装有 Java 8。
 3. 使用 pip 命令进行安装：
-  `pip install pyalink` 或者 `pip install pyalink-flink-1.9`。
+  `pip install pyalink`、`pip install pyalink-flink-1.10` 或者 `pip install pyalink-flink-1.9`。
 
 安装注意事项：
 
 1. `pyalink` 和 `pyalink-flink-***` 不能同时安装，也不能与旧版本同时安装。
 如果之前安装过 `pyalink` 或者 `pyalink-flink-***`，请使用`pip uninstall pyalink` 或者 `pip uninstall pyalink-flink-***` 卸载之前的版本。
 2. 出现`pip`安装缓慢或不成功的情况，可以参考[这篇文章](https://segmentfault.com/a/1190000006111096)修改pip源，或者直接使用下面的链接下载 whl 包，然后使用 `pip` 安装：
-   - Flink 1.10：[链接](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.1.2.post0/pyalink-1.1.2.post0-py3-none-any.whl) (MD5: 6bf3a50a4437116793149ead57d9793c)  
-   - Flink 1.9: [链接](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.1.2.post0/pyalink_flink_1.9-1.1.2.post-py3-none-any.whl) (MD5: e6d2a0ba3549662d77b51a4a37483479)  
+   - Flink 1.11：[链接](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.2.0/pyalink-1.2.0-py3-none-any.whl) (MD5: 8a38e8009712afcbf5ecdb297db3c8ac)
+   - Flink 1.10：[链接](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.2.0/pyalink_flink_1.10-1.2.0-py3-none-any.whl) (MD5: 8a38e8009712afcbf5ecdb297db3c8ac)  
+   - Flink 1.9: [链接](https://alink-release.oss-cn-beijing.aliyuncs.com/v1.2.0/pyalink_flink_1.9-1.2.0-py3-none-any.whl) (MD5: 2f25eec02a692661c0f0f3a89e5c2f0c)  
 3. 如果有多个版本的 Python，可能需要使用特定版本的 `pip`，比如 `pip3`；如果使用 Anaconda，则需要在 Anaconda 命令行中进行安装。
 
 ### 开始使用：
 -------
-我们推荐通过 Jupyter Notebook 来使用 PyAlink，能获得更好的使用体验。
+可以通过 Jupyter Notebook 来开始使用 PyAlink，能获得更好的使用体验。
 
 使用步骤：
 1. 在命令行中启动Jupyter：`jupyter notebook`，并新建 Python 3 的 Notebook 。
 2. 导入 pyalink 包：`from pyalink.alink import *`。
 3. 使用方法创建本地运行环境：
 `useLocalEnv(parallism, flinkHome=None, config=None)`。
-其中，参数 `parallism` 表示执行所使用的并行度；`flinkHome` 为 flink 的完整路径，默认使用 PyAlink 自带的 flink-1.9.0 路径；`config`为Flink所接受的配置参数。运行后出现如下所示的输出，表示初始化运行环境成功：
+其中，参数 `parallism` 表示执行所使用的并行度；`flinkHome` 为 flink 的完整路径，一般情况不需要设置；`config`为Flink所接受的配置参数。运行后出现如下所示的输出，表示初始化运行环境成功：
 ```
 JVM listening on ***
-Python listening on ***
 ```
 4. 开始编写 PyAlink 代码，例如：
 ```python
@@ -76,18 +76,18 @@ print(df)
 ### 编写代码：
 ------
 在 PyAlink 中，算法组件提供的接口基本与 Java API 一致，即通过默认构造方法创建一个算法组件，然后通过 `setXXX` 设置参数，通过 `link/linkTo/linkFrom` 与其他组件相连。
-这里利用 Jupyter 的自动补全机制可以提供书写便利。
+这里利用 Jupyter Notebook 的自动补全机制可以提供书写便利。
 
 对于批式作业，可以通过批式组件的 `print/collectToDataframe/collectToDataframes` 等方法或者 `BatchOperator.execute()` 来触发执行；对于流式作业，则通过 `StreamOperator.execute()` 来启动作业。
 
 
 ### 更多用法：
 ------
-  - [PyAlink 使用介绍](docs/pyalink/pyalink-overview.md)
   - [DataFrame 与 Operator 互转](docs/pyalink/pyalink-dataframe.md)
   - [StreamOperator 数据预览](docs/pyalink/pyalink-stream-operator-preview.md)
   - [UDF/UDTF/SQL 使用](docs/pyalink/pyalink-udf.md)
   - [与 PyFlink 一同使用](docs/pyalink/pyalink-pyflink.md)
+  - [PyAlink 常见问题](docs/pyalink/pyalink-qa.md)
 
 ## Java 接口使用介绍
 ----------
@@ -116,12 +116,31 @@ Pipeline pipeline = new Pipeline().add(va).add(kMeans);
 pipeline.fit(data).transform(data).print();
 ```
 
+### Flink-1.11 的 Maven 依赖
+```xml
+<dependency>
+    <groupId>com.alibaba.alink</groupId>
+    <artifactId>alink_core_flink-1.11_2.11</artifactId>
+    <version>1.2.0</version>
+</dependency>
+<dependency>
+    <groupId>org.apache.flink</groupId>
+    <artifactId>flink-streaming-scala_2.11</artifactId>
+    <version>1.11.0</version>
+</dependency>
+<dependency>
+    <groupId>org.apache.flink</groupId>
+    <artifactId>flink-table-planner_2.11</artifactId>
+    <version>1.11.0</version>
+</dependency>
+```
+
 ### Flink-1.10 的 Maven 依赖
 ```xml
 <dependency>
     <groupId>com.alibaba.alink</groupId>
     <artifactId>alink_core_flink-1.10_2.11</artifactId>
-    <version>1.1.2</version>
+    <version>1.2.0</version>
 </dependency>
 <dependency>
     <groupId>org.apache.flink</groupId>
@@ -141,7 +160,7 @@ pipeline.fit(data).transform(data).print();
 <dependency>
     <groupId>com.alibaba.alink</groupId>
     <artifactId>alink_core_flink-1.9_2.11</artifactId>
-    <version>1.1.2</version>
+    <version>1.2.0</version>
 </dependency>
 <dependency>
     <groupId>org.apache.flink</groupId>
@@ -162,8 +181,8 @@ pipeline.fit(data).transform(data).print();
 
 1. 准备Flink集群
 ```shell
-  wget https://archive.apache.org/dist/flink/flink-1.10.0/flink-1.10.0-bin-scala_2.11.tgz
-  tar -xf flink-1.10.0-bin-scala_2.11.tgz && cd flink-1.10.0
+  wget https://archive.apache.org/dist/flink/flink-1.11.0/flink-1.10.0-bin-scala_2.11.tgz
+  tar -xf flink-1.11.0-bin-scala_2.11.tgz && cd flink-1.11.0
   ./bin/start-cluster.sh
 ```
 
@@ -176,6 +195,6 @@ pipeline.fit(data).transform(data).print();
 3. 运行Java示例
 ```shell
   ./bin/flink run -p 1 -c com.alibaba.alink.ALSExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
-  # ./bin/flink run -p 2 -c com.alibaba.alink.GBDTExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
-  # ./bin/flink run -p 2 -c com.alibaba.alink.KMeansExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
+  # ./bin/flink run -p 1 -c com.alibaba.alink.GBDTExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
+  # ./bin/flink run -p 1 -c com.alibaba.alink.KMeansExample [path_to_Alink]/examples/target/alink_examples-1.1-SNAPSHOT.jar
 ```