update version in docs to 2.3.1

Signed-off-by: chenxu <chenxu@dmetasoul.com>

website/docs/01-Getting Started/01-setup-local-env.md

@@ -41,7 +41,7 @@ After unpacking spark package, you could find LakeSoul distribution jar from htt
 wget https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/spark/spark-3.3.2-bin-hadoop-3.tgz
 tar xf spark-3.3.2-bin-hadoop-3.tgz
 export SPARK_HOME=${PWD}/spark-3.3.2-bin-hadoop3
-wget https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-spark-2.3.0-spark-3.3.jar -P $SPARK_HOME/jars
+wget https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-spark-2.3.1-spark-3.3.jar -P $SPARK_HOME/jars
 ```
 
 :::tip

website/docs/01-Getting Started/02-docker-compose.mdx

@@ -34,7 +34,7 @@ docker run --net lakesoul-docker-compose-env_default --rm -ti \
     -v $(pwd)/lakesoul.properties:/opt/spark/work-dir/lakesoul.properties \
     --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 \
     spark-shell \
-    --packages com.dmetasoul:lakesoul-spark:2.3.0-spark-3.3 \
+    --packages com.dmetasoul:lakesoul-spark:2.3.1-spark-3.3 \
     --conf spark.sql.extensions=com.dmetasoul.lakesoul.sql.LakeSoulSparkSessionExtension \
     --conf spark.sql.catalog.lakesoul=org.apache.spark.sql.lakesoul.catalog.LakeSoulCatalog \
     --conf spark.sql.defaultCatalog=lakesoul \

website/docs/02-Tutorials/02-flink-cdc-sink/index.md

@@ -84,7 +84,7 @@ Submit a LakeSoul Flink CDC Sink job to the Flink cluster started above:
 ```bash
 ./bin/flink run -ys 1 -yjm 1G -ytm 2G \
    -c org.apache.flink.lakesoul.entry.MysqlCdc\
-   lakesoul-flink-2.3.0-flink-1.14.jar \
+   lakesoul-flink-2.3.1-flink-1.14.jar \
    --source_db.host localhost \
    --source_db.port 3306 \
    --source_db.db_name test_cdc \

website/docs/02-Tutorials/07-kafka-topics-data-to-lakesoul.md

@@ -74,7 +74,7 @@ export lakesoul_home=./pg.properties && ./bin/spark-submit \
 --driver-memory 4g \
 --executor-memory 4g \
 --master local[4] \
-./jars/lakesoul-spark-2.3.0-spark-3.3.jar \
+./jars/lakesoul-spark-2.3.1-spark-3.3.jar \
 localhost:9092 test.* /tmp/kafka/data /tmp/kafka/checkpoint/ kafka earliest false
 ```
 
@@ -151,6 +151,6 @@ export lakesoul_home=./pg.properties && ./bin/spark-submit \
 --driver-memory 4g \
 --executor-memory 4g \
 --master local[4] \
-./jars/lakesoul-spark-2.3.0-spark-3.3.jar \
+./jars/lakesoul-spark-2.3.1-spark-3.3.jar \
 localhost:9092 test.* /tmp/kafka/data /tmp/kafka/checkpoint/ kafka earliest false http://localhost:8081
 ```

website/docs/03-Usage Docs/02-setup-spark.md

@@ -8,14 +8,14 @@ To use `spark-shell`, `pyspark` or `spark-sql` shells, you should include LakeSo
 
 ### Use Maven Coordinates via --packages
 ```bash
-spark-shell --packages com.dmetasoul:lakesoul-spark:2.3.0-spark-3.3
+spark-shell --packages com.dmetasoul:lakesoul-spark:2.3.1-spark-3.3
 ```
 
 ### Use Local Packages
 You can find the LakeSoul packages from our release page: [Releases](https://github.com/lakesoul-io/LakeSoul/releases).
 Download the jar file and pass it to `spark-submit`.
 ```bash
-spark-submit --jars "lakesoul-spark-2.3.0-spark-3.3.jar"
+spark-submit --jars "lakesoul-spark-2.3.1-spark-3.3.jar"
 ```
 
 Or you could directly put the jar into `$SPARK_HOME/jars`
@@ -26,7 +26,7 @@ Include maven dependencies in your project:
 <dependency>
     <groupId>com.dmetasoul</groupId>
     <artifactId>lakesoul</artifactId>
-    <version>2.3.0-spark-3.3</version>
+    <version>2.3.1-spark-3.3</version>
 </dependency>
 ```
 
@@ -92,7 +92,7 @@ taskmanager.memory.task.off-heap.size: 3000m
 :::
 
 ## Add LakeSoul Jar to Flink's directory
-Download LakeSoul Flink Jar from: https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-flink-2.3.0-flink-1.14.jar
+Download LakeSoul Flink Jar from: https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-flink-2.3.1-flink-1.14.jar
 
 And put the jar file under `$FLINK_HOME/lib`. After this, you could start flink session cluster or application as usual.
 
@@ -103,6 +103,6 @@ Add the following to your project's pom.xml
 <dependency>
     <groupId>com.dmetasoul</groupId>
     <artifactId>lakesoul</artifactId>
-    <version>2.3.0-flink-1.14</version>
+    <version>2.3.1-flink-1.14</version>
 </dependency>
 ```

website/docs/03-Usage Docs/05-flink-cdc-sync.md

@@ -15,7 +15,7 @@ In the Stream API, the main functions of LakeSoul Sink are:
 
 ## How to use the command line
 ### 1. Download LakeSoul Flink Jar
-It can be downloaded from the LakeSoul Release page: https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-flink-2.3.0-flink-1.14.jar.
+It can be downloaded from the LakeSoul Release page: https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-flink-2.3.1-flink-1.14.jar.
 
 The currently supported Flink version is 1.14.
 
@@ -54,7 +54,7 @@ export LAKESOUL_PG_PASSWORD=root
 #### 2.2 Start sync job
 ```bash
 bin/flink run -c org.apache.flink.lakesoul.entry.MysqlCdc \
-    lakesoul-flink-2.3.0-flink-1.14.jar \
+    lakesoul-flink-2.3.1-flink-1.14.jar \
     --source_db.host localhost \
     --source_db.port 3306 \
     --source_db.db_name default \
@@ -73,7 +73,7 @@ Description of required parameters:
 | Parameter | Meaning | Value Description |
 |----------------|------------------------------------|-------------------------------------------- |
 | -c | The task runs the main function entry class | org.apache.flink.lakesoul.entry.MysqlCdc |
-| Main package | Task running jar | lakesoul-flink-2.3.0-flink-1.14.jar |
+| Main package | Task running jar | lakesoul-flink-2.3.1-flink-1.14.jar |
 | --source_db.host | The address of the MySQL database | |
 | --source_db.port | MySQL database port | |
 | --source_db.user | MySQL database username | |

website/docs/03-Usage Docs/06-flink-lakesoul-connector.md

@@ -10,14 +10,12 @@ LakeSoul provides Flink Connector which implements the Dynamic Table interface,
 
 To setup Flink environment, please refer to [Setup Spark/Flink Job/Project](../03-Usage%20Docs/02-setup-spark.md)
 
-Introduce LakeSoul dependency: package and compile the lakesoul-flink folder to get lakesoul-flink-2.3.0-flink-1.14.jar.
-
 In order to use Flink to create LakeSoul tables, it is recommended to use Flink SQL Client, which supports direct use of Flink SQL commands to operate LakeSoul tables. In this document, the Flink SQL is to directly enter statements on the Flink SQL Client cli interface; whereas the Table API needs to be used in a Java projects.
 
 Switch to the flink folder and execute the command to start the SQLclient client.
 ```bash
 # Start Flink SQL Client
-bin/sql-client.sh embedded -j lakesoul-flink-2.3.0-flink-1.14.jar
+bin/sql-client.sh embedded -j lakesoul-flink-2.3.1-flink-1.14.jar
 ```
 
 ## 2. DDL

website/docs/03-Usage Docs/08-auto-compaction-task.md

@@ -41,7 +41,7 @@ The use the following command to start the compaction service job:
     --conf "spark.executor.extraJavaOptions=-XX:MaxDirectMemorySize=4G" \
     --conf "spark.executor.memoryOverhead=3g" \
     --class com.dmetasoul.lakesoul.spark.compaction.CompactionTask  \
-    jars/lakesoul-spark-2.3.0-spark-3.3.jar 
+    jars/lakesoul-spark-2.3.1-spark-3.3.jar 
     --threadpool.size=10
     --database=test
 ```

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/01-Getting Started/01-setup-local-env.md

@@ -31,10 +31,10 @@ https://dlcdn.apache.org/spark/spark-3.3.2/spark-3.3.2-bin-without-hadoop.tgz
 
 LakeSoul 发布 jar 包可以从 GitHub Releases 页面下载：https://github.com/lakesoul-io/LakeSoul/releases 。下载后请将 Jar 包放到 Spark 安装目录下的 jars 目录中：
 ```bash
-wget https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-spark-2.3.0-spark-3.3.jar -P $SPARK_HOME/jars
+wget https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-spark-2.3.1-spark-3.3.jar -P $SPARK_HOME/jars
 ```
 
-如果访问 Github 有问题，也可以从如下链接下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-spark-2.3.0-spark-3.3.jar
+如果访问 Github 有问题，也可以从如下链接下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-spark-2.3.1-spark-3.3.jar
 
 :::tip
 从 2.1.0 版本起，LakeSoul 自身的依赖已经通过 shade 方式打包到一个 jar 包中。之前的版本是多个 jar 包以 tar.gz 压缩包的形式发布。

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/01-Getting Started/02-docker-compose.mdx

@@ -34,7 +34,7 @@ docker run --net lakesoul-docker-compose-env_default --rm -ti \
     -v $(pwd)/lakesoul.properties:/opt/spark/work-dir/lakesoul.properties \
     --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 \
     spark-shell \
-    --packages com.dmetasoul:lakesoul-spark:2.3.0-spark-3.3 \
+    --packages com.dmetasoul:lakesoul-spark:2.3.1-spark-3.3 \
     --conf spark.sql.extensions=com.dmetasoul.lakesoul.sql.LakeSoulSparkSessionExtension \
     --conf spark.sql.catalog.lakesoul=org.apache.spark.sql.lakesoul.catalog.LakeSoulCatalog \
     --conf spark.sql.defaultCatalog=lakesoul \

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/02-Tutorials/02-flink-cdc-sink/index.md

@@ -84,7 +84,7 @@ $FLINK_HOME/bin/start-cluster.sh
 ```bash
 ./bin/flink run -ys 1 -yjm 1G -ytm 2G \
    -c org.apache.flink.lakesoul.entry.MysqlCdc \
-   lakesoul-flink-2.3.0-flink-1.14.jar \
+   lakesoul-flink-2.3.1-flink-1.14.jar \
    --source_db.host localhost \
    --source_db.port 3306 \
    --source_db.db_name test_cdc \
@@ -99,7 +99,7 @@ $FLINK_HOME/bin/start-cluster.sh
    --server_time_zone UTC
 ```
 
-其中 lakesoul-flink 的 jar 包可以从 [Github Release](https://github.com/lakesoul-io/LakeSoul/releases/) 页面下载。如果访问 Github 有问题，也可以通过这个链接下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-flink-2.3.0-flink-1.14.jar
+其中 lakesoul-flink 的 jar 包可以从 [Github Release](https://github.com/lakesoul-io/LakeSoul/releases/) 页面下载。如果访问 Github 有问题，也可以通过这个链接下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-flink-2.3.1-flink-1.14.jar
 
 在 http://localhost:8081 Flink 作业页面中，点击 Running Job，进入查看 LakeSoul 作业是否已经处于 `Running` 状态。
 

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/02-Tutorials/07-kafka-topics-data-to-lakesoul.md

@@ -72,7 +72,7 @@ export lakesoul_home=./pg.properties && ./bin/spark-submit \
 --driver-memory 4g \
 --executor-memory 4g \
 --master local[4] \
-./jars/lakesoul-spark-2.3.0-spark-3.3.jar \
+./jars/lakesoul-spark-2.3.1-spark-3.3.jar \
 localhost:9092 test.* /tmp/kafka/data /tmp/kafka/checkpoint/ kafka earliest false
 ```
 
@@ -149,6 +149,6 @@ export lakesoul_home=./pg.properties && ./bin/spark-submit \
 --driver-memory 4g \
 --executor-memory 4g \
 --master local[4] \
-./jars/lakesoul-spark-2.3.0-spark-3.3.jar \
+./jars/lakesoul-spark-2.3.1-spark-3.3.jar \
 localhost:9092 test.* /tmp/kafka/data /tmp/kafka/checkpoint/ kafka earliest false http://localhost:8081
 ```

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/03-Usage Docs/02-setup-spark.md

@@ -8,30 +8,30 @@ LakeSoul 目前支持 Spark 3.3 + Scala 2.12.
 
 ### 使用 `--packages` 传 Maven 仓库和包名
 ```bash
-spark-shell --packages com.dmetasoul:lakesoul-spark:2.3.0-spark-3.3
+spark-shell --packages com.dmetasoul:lakesoul-spark:2.3.1-spark-3.3
 ```
 
 ### 使用打包好的 LakeSoul 包
 可以从 [Releases](https://github.com/lakesoul-io/LakeSoul/releases) 页面下载已经打包好的 LakeSoul Jar 包。
 下载 jar 并传给 `spark-submit` 命令：
 ```bash
-spark-submit --jars "lakesoul-spark-2.3.0-spark-3.3.jar"
+spark-submit --jars "lakesoul-spark-2.3.1-spark-3.3.jar"
 ```
 
 ### 直接将 Jar 包放在 Spark 环境中
 可以将 Jar 包下载后，放在 $SPARK_HOME/jars 中。
 
-Jar 包可以从 Github Release 页面下载：https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-spark-2.3.0-spark-3.3.jar
+Jar 包可以从 Github Release 页面下载：https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-spark-2.3.1-spark-3.3.jar
 
-或者从国内地址下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-spark-2.3.0-spark-3.3.jar
+或者从国内地址下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-spark-2.3.1-spark-3.3.jar
 
 ## 设置 Java/Scala 项目
 增加以下 Maven 依赖项:
 ```xml
 <dependency>
     <groupId>com.dmetasoul</groupId>
     <artifactId>lakesoul-spark</artifactId>
-    <version>2.3.0-spark-3.3</version>
+    <version>2.3.1-spark-3.3</version>
 </dependency>
 ```
 
@@ -116,7 +116,7 @@ taskmanager.memory.task.off-heap.size: 3000m
 
 
 ## 添加 LakeSoul Jar 到 Flink 部署的目录
-从以下地址下载 LakeSoul Flink Jar：https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-flink-2.3.0-flink-1.14.jar
+从以下地址下载 LakeSoul Flink Jar：https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-flink-2.3.1-flink-1.14.jar
 
 并将 jar 文件放在 `$FLINK_HOME/lib` 下。在此之后，您可以像往常一样启动 flink 会话集群或应用程序。
 
@@ -136,6 +136,6 @@ export HADOOP_CLASSPATH=`$HADOOP_HOME/bin/hadoop classpath`
 <dependency>
      <groupId>com.dmetasoul</groupId>
      <artifactId>lakesoul</artifactId>
-     <version>2.3.0-flink-1.14</version>
+     <version>2.3.1-flink-1.14</version>
 </dependency>
 ```

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/03-Usage Docs/05-flink-cdc-sync.md

@@ -13,9 +13,9 @@ LakeSoul 自 2.1.0 版本起，实现了 Flink CDC Sink，能够支持 Table API
 
 ## 命令行使用方法
 ### 1. 下载 LakeSoul Flink Jar
-可以在 LakeSoul Release 页面下载：https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.0/lakesoul-flink-2.3.0-flink-1.14.jar。
+可以在 LakeSoul Release 页面下载：https://github.com/lakesoul-io/LakeSoul/releases/download/v2.3.1/lakesoul-flink-2.3.1-flink-1.14.jar。
 
-如果访问 Github 有问题，也可以通过这个链接下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-flink-2.3.0-flink-1.14.jar。
+如果访问 Github 有问题，也可以通过这个链接下载：https://dmetasoul-bucket.obs.cn-southwest-2.myhuaweicloud.com/releases/lakesoul/lakesoul-flink-2.3.1-flink-1.14.jar。
 
 目前支持的 Flink 版本为 1.14。
 
@@ -52,7 +52,7 @@ export LAKESOUL_PG_PASSWORD=root
 #### 2.2 启动同步作业
 ```bash
 bin/flink run -c org.apache.flink.lakesoul.entry.MysqlCdc \
-    lakesoul-flink-2.3.0-flink-1.14.jar \
+    lakesoul-flink-2.3.1-flink-1.14.jar \
     --source_db.host localhost \
     --source_db.port 3306 \
     --source_db.db_name default \
@@ -71,7 +71,7 @@ bin/flink run -c org.apache.flink.lakesoul.entry.MysqlCdc \
 | 参数      | 含义                                                                        | 取值说明    |
 |----------------|--------------------------------------------------------------------------------------|---------------------------------------------|
 | -c      | 任务运行main函数入口类                                                                        | org.apache.flink.lakesoul.entry.MysqlCdc    |
-| 主程序包           | 任务运行jar包                                                                     | lakesoul-flink-2.3.0-flink-1.14.jar                  |
+| 主程序包           | 任务运行jar包                                                                     | lakesoul-flink-2.3.1-flink-1.14.jar                  |
 | --source_db.host      | MySQL 数据库的地址                                                     |                                             |
 | --source_db.port      | MySQL 数据库的端口                                                     |                                             |
 | --source_db.user      | MySQL 数据库的用户名                                                     |                                             |

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/03-Usage Docs/06-flink-lakesoul-connector.md

@@ -8,16 +8,14 @@ LakeSoul 提供了 Flink Connector，实现了 Flink Dynamic Table 接口，可
 
 ## 1. 环境准备
 
-设置 LakeSoul 元数据，请参考 [设置 Spark/Flink 工程/作业](../03-Usage%20Docs/02-setup-spark.md)
-
-Flink引入 LakeSoul 依赖的方法：将 lakesoul-flink 文件夹打包编译后得到 lakesoul-flink-2.3.0-flink-1.14.jar。
+设置 LakeSoul 元数据以及依赖包，请参考 [设置 Spark/Flink 工程/作业](../03-Usage%20Docs/02-setup-spark.md)
 
 为了使用 Flink 创建 LakeSoul 表，推荐使用 Flink SQL Client，支持直接使用 Flink SQL 命令操作 LakeSoul 表，本文档中 Flink SQL 是在 Flink SQL Client 界面直接输入语句；Table API 需要在 Java 项目中编写使用。
 
 切换到 Flink 文件夹下，执行命令开启 SQL Client 客户端。
 ```bash
 # 启动 Flink SQL Client
-bin/sql-client.sh embedded -j lakesoul-flink-2.3.0-flink-1.14.jar
+bin/sql-client.sh embedded -j lakesoul-flink-2.3.1-flink-1.14.jar
 ```
 
 ## 2. DDL

website/i18n/zh-Hans/docusaurus-plugin-content-docs/current/03-Usage Docs/08-auto-compaction-task.md

@@ -40,7 +40,7 @@ trigger 和 pg 函数在数据库初始化的时候已经配置，默认压缩
     --conf "spark.executor.extraJavaOptions=-XX:MaxDirectMemorySize=4G" \
     --conf "spark.executor.memoryOverhead=3g" \
     --class com.dmetasoul.lakesoul.spark.compaction.CompactionTask  \
-    jars/lakesoul-spark-2.3.0-spark-3.3.jar 
+    jars/lakesoul-spark-2.3.1-spark-3.3.jar 
     --threadpool.size=10
     --database=test
 ```