docs: upgrade 0.8.1 (4paradigm#3335)

CHANGELOG.md

@@ -1,5 +1,28 @@
 # Changelog
 
+## [0.8.1] - 2023-06-28
+
+### Features
+- Support a new SQL statement `ALTER TABLE ... ADD/DROP OFFLINE_PATH ...` (#3286 @aceforeverd, #3323 @tobegit3hub)
+- Support deploying SQLs in which the involved tables have data but without pre-aggregation defined (#3288 @dl239)
+- Support new built-in functions `top_n_value_ratio_cate`, `top_n_key_ratio_cate`, `list_except_by_key` and `list_except_by_value` (#3329 @aceforeverd)
+- Add a new SDK API to merge multiple SQLs for deployment (#3297 @vagetablechicken)
+- Support mapping topic tables in the Kafka connector (#3282 @vagetablechicken)
+- Support deploying the Kafka connector in Docker and Kubernetes (#3276 @tobegit3hub)
+- Support fetching jobs from NameServer (#3293 @dl239)
+- Enhance the diagnostic tool (#3224 #3208 #3285 #3258 #3303 @zhangziheng01233)
+- Enhance the `SELECT INTO ...` statement (#2529 @vagetablechicken)
+- Improve the documents (#3308 @aceforeverd)
+- Other minor features (#3312 #3314 @vagetablechicken, #3298 @aceforeverd)
+
+### Bug Fixes
+- SQL deployment fails in some cases (#3328 @vagetablechicken)
+- Creating UDFs/UDAFs may fail as the `udf` directory does not exist by default. (#3326 @vagetablechicken)
+- Other minor bug fixes (#3281 #3284 @vagetablechicken)
+
+### Code Refactoring
+#3226 @dl239, #3294 @aceforeverd
+
 ## [0.8.0] - 2023-05-12
 
 ### Features
@@ -576,6 +599,7 @@ Removed
 - openmldb-0.2.0-linux.tar.gz targets on x86_64
 - aarch64 artifacts consider experimental
 
+[0.8.1]: https://github.com/4paradigm/OpenMLDB/compare/v0.8.0...v0.8.1
 [0.8.0]: https://github.com/4paradigm/OpenMLDB/compare/v0.7.3...v0.8.0
 [0.7.3]: https://github.com/4paradigm/OpenMLDB/compare/v0.7.2...v0.7.3
 [0.7.2]: https://github.com/4paradigm/OpenMLDB/compare/v0.7.1...v0.7.2

README.md

@@ -158,7 +158,7 @@ We really appreciate the contribution from our community.
 ## 12. Publications
 
 - [Scalable Online Interval Join on Modern Multicore Processors in OpenMLDB](docs/paper/scale_oij_icde2023.pdf). Hao Zhang, Xianzhi Zeng, Shuhao Zhang, Xinyi Liu, Mian Lu, and Zhao Zheng. In 2023 IEEE 39rd International Conference on Data Engineering (ICDE) 2023. [[code]](https://github.com/4paradigm/OpenMLDB/tree/stream)
-- [FEBench: A Benchmark for Real-Time Relational Data Feature Extraction](https://github.com/decis-bench/febench/blob/main/report/febench.pdf). Xuanhe Zhou, Cheng Chen, Kunyi Li, Bingsheng He, Mian Lu, Qiaosheng Liu, Wei Huang, Guoliang Li, Zhao Zheng, Yuqiang Chen. In submission. [[code]](https://github.com/decis-bench/febench).
+- [FEBench: A Benchmark for Real-Time Relational Data Feature Extraction](https://github.com/decis-bench/febench/blob/main/report/febench.pdf). Xuanhe Zhou, Cheng Chen, Kunyi Li, Bingsheng He, Mian Lu, Qiaosheng Liu, Wei Huang, Guoliang Li, Zhao Zheng, Yuqiang Chen. International Conference on Very Large Data Bases (VLDB) 2023. [[code]](https://github.com/decis-bench/febench).
 -  [A System for Time Series Feature Extraction in Federated Learning](https://dl.acm.org/doi/pdf/10.1145/3511808.3557176). Siqi Wang, Jiashu Li, Mian Lu, Zhao Zheng, Yuqiang Chen, and Bingsheng He. 2022. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM) 2022. [[code]](https://github.com/4paradigm/tsfe).
 - [Optimizing in-memory database engine for AI-powered on-line decision augmentation using persistent memory](http://vldb.org/pvldb/vol14/p799-chen.pdf). Cheng Chen, Jun Yang, Mian Lu, Taize Wang, Zhao Zheng, Yuqiang Chen, Wenyuan Dai, Bingsheng He, Weng-Fai Wong, Guoan Wu, Yuping Zhao, and Andy Rudoff. International Conference on Very Large Data Bases (VLDB) 2021.
 

README_cn.md

@@ -147,7 +147,7 @@ OpenMLDB 的整体架构设计是为了达到特征平台从开发到部署的
 ## 12. 学术论文
 
 - [Scalable Online Interval Join on Modern Multicore Processors in OpenMLDB](docs/paper/scale_oij_icde2023.pdf). Hao Zhang, Xianzhi Zeng, Shuhao Zhang, Xinyi Liu, Mian Lu, and Zhao Zheng. In 2023 IEEE 39rd International Conference on Data Engineering (ICDE) 2023. [[code]](https://github.com/4paradigm/OpenMLDB/tree/stream)
-- [FEBench: A Benchmark for Real-Time Relational Data Feature Extraction](https://github.com/decis-bench/febench/blob/main/report/febench.pdf). Xuanhe Zhou, Cheng Chen, Kunyi Li, Bingsheng He, Mian Lu, Qiaosheng Liu, Wei Huang, Guoliang Li, Zhao Zheng, Yuqiang Chen. In submission. [[code]](https://github.com/decis-bench/febench).
+- [FEBench: A Benchmark for Real-Time Relational Data Feature Extraction](https://github.com/decis-bench/febench/blob/main/report/febench.pdf). Xuanhe Zhou, Cheng Chen, Kunyi Li, Bingsheng He, Mian Lu, Qiaosheng Liu, Wei Huang, Guoliang Li, Zhao Zheng, Yuqiang Chen. International Conference on Very Large Data Bases (VLDB) 2023. [[code]](https://github.com/decis-bench/febench).
 - [A System for Time Series Feature Extraction in Federated Learning](https://dl.acm.org/doi/pdf/10.1145/3511808.3557176). Siqi Wang, Jiashu Li, Mian Lu, Zhao Zheng, Yuqiang Chen, and Bingsheng He. 2022. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM) 2022. [[code]](https://github.com/4paradigm/tsfe).
 - [Optimizing in-memory database engine for AI-powered on-line decision augmentation using persistent memory](http://vldb.org/pvldb/vol14/p799-chen.pdf). Cheng Chen, Jun Yang, Mian Lu, Taize Wang, Zhao Zheng, Yuqiang Chen, Wenyuan Dai, Bingsheng He, Weng-Fai Wong, Guoan Wu, Yuping Zhao, and Andy Rudoff. International Conference on Very Large Data Bases (VLDB) 2021.
 

demo/java_quickstart/demo/pom.xml

@@ -29,7 +29,7 @@
     <dependency>
       <groupId>com.4paradigm.openmldb</groupId>
       <artifactId>openmldb-jdbc</artifactId>
-      <version>0.8.0</version>
+      <version>0.8.1</version>
     </dependency>
     <dependency>
       <groupId>org.testng</groupId>

demo/jd-recommendation/README.md

@@ -11,7 +11,7 @@ For full instructions, please refer to [website page](http://openmldb.ai/docs/zh
 ## OpenMLDB Feature Extraction
 
 ```
-docker run -dit --name=openmldb --network=host -v $demodir:/work/oneflow_demo 4pdosc/openmldb:0.8.0 bash
+docker run -dit --name=openmldb --network=host -v $demodir:/work/oneflow_demo 4pdosc/openmldb:0.8.1 bash
 docker exec -it openmldb bash
 ```
 

demo/predict-taxi-trip-duration/README.md

@@ -28,7 +28,7 @@ w2 as (PARTITION BY passenger_count ORDER BY pickup_datetime ROWS_RANGE BETWEEN
 
 **Start docker**
 ```
-docker run -it 4pdosc/openmldb:0.8.0 bash
+docker run -it 4pdosc/openmldb:0.8.1 bash
 ```
 **Initialize environment**
 ```bash
@@ -138,7 +138,7 @@ python3 predict.py
 **Start docker**
 
 ```bash
-docker run -it 4pdosc/openmldb:0.8.0 bash
+docker run -it 4pdosc/openmldb:0.8.1 bash
 ```
 **Initialize environment**
 

demo/talkingdata-adtracking-fraud-detection/README.md

@@ -15,7 +15,7 @@ We recommend you to use docker to run the demo. OpenMLDB and dependencies have b
 **Start docker**
 
 ```
-docker run -it 4pdosc/openmldb:0.8.0 bash
+docker run -it 4pdosc/openmldb:0.8.1 bash
 ```
 
 #### Run locally

docs/en/deploy/compile.md

@@ -7,7 +7,7 @@
 This section describes the steps to compile and use OpenMLDB inside its official docker image [hybridsql](https://hub.docker.com/r/4pdosc/hybridsql).
 The docker image has packed required tools and dependencies, so there is no need to set them up separately. To compile without the official docker image, refer to the section [Detailed Instructions for Build](#detailed-instructions-for-build) below.
 
-Keep in mind that you should always use the same version of both compile image and [OpenMLDB version](https://github.com/4paradigm/OpenMLDB/releases). This section demonstrates compiling for [OpenMLDB v0.8.0](https://github.com/4paradigm/OpenMLDB/releases/tag/v0.8.0) under `hybridsql:0.8.0` ，If you prefer to compile on the latest code in `main` branch, pull `hybridsql:latest` image instead.
+Keep in mind that you should always use the same version of both compile image and [OpenMLDB version](https://github.com/4paradigm/OpenMLDB/releases). This section demonstrates compiling for [OpenMLDB v0.8.1](https://github.com/4paradigm/OpenMLDB/releases/tag/v0.8.1) under `hybridsql:0.8.1` ，If you prefer to compile on the latest code in `main` branch, pull `hybridsql:latest` image instead.
 
 1. Pull the docker image
 
@@ -21,11 +21,11 @@ Keep in mind that you should always use the same version of both compile image a
    docker run -it 4pdosc/hybridsql:0.8 bash
    ```
 
-3. Download the OpenMLDB source code inside the docker container, and setting the branch into v0.8.0
+3. Download the OpenMLDB source code inside the docker container, and setting the branch into v0.8.1
 
    ```bash
    cd ~
-   git clone -b v0.8.0 https://github.com/4paradigm/OpenMLDB.git
+   git clone -b v0.8.1 https://github.com/4paradigm/OpenMLDB.git
    ```
 
 4. Compile OpenMLDB
@@ -151,7 +151,7 @@ The built jar packages are in the `target` path of each submodule. If you want t
 1. Downloading the pre-built OpenMLDB Spark distribution:
 
 ```bash
-wget https://github.com/4paradigm/spark/releases/download/v3.2.1-openmldb0.8.0/spark-3.2.1-bin-openmldbspark.tgz
+wget https://github.com/4paradigm/spark/releases/download/v3.2.1-openmldb0.8.1/spark-3.2.1-bin-openmldbspark.tgz
 ```
 
 Alternatively, you can also download the source code and compile from scratch:

docs/en/deploy/install_deploy.md

@@ -9,7 +9,7 @@
   * The number of cores is recommended to be no less than 4 cores. If the CPU does not support the AVX2 instruction set in the Linux environment, the deployment package needs to be recompiled from the source code.
 
 ## Deployment Package
-The precompiled OpenMLDB deployment package is used by default in this documentation ([Linux](https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz) , [macOS](https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-darwin.tar.gz)), the supported operating system requirements are: CentOS 7, Ubuntu 20.04, macOS >= 10.15. If the user wishes to compile by himself (for example, for OpenMLDB source code development, the operating system or CPU architecture is not in the support list of the precompiled deployment package, etc.), the user can choose to compile and use in the docker container or compile from the source code. For details, please refer to our [compile documentation](compile.md).
+The precompiled OpenMLDB deployment package is used by default in this documentation ([Linux](https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz) , [macOS](https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-darwin.tar.gz)), the supported operating system requirements are: CentOS 7, Ubuntu 20.04, macOS >= 10.15. If the user wishes to compile by himself (for example, for OpenMLDB source code development, the operating system or CPU architecture is not in the support list of the precompiled deployment package, etc.), the user can choose to compile and use in the docker container or compile from the source code. For details, please refer to our [compile documentation](compile.md).
 
 ## Configure Environment (Linux)
 
@@ -91,9 +91,9 @@ OpenMLDB standalone version needs to deploy a nameserver and a tablet. The names
 ### Download the OpenMLDB Release Package
 
 ```
-wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz
-tar -zxvf openmldb-0.8.0-linux.tar.gz
-cd openmldb-0.8.0-linux
+wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz
+tar -zxvf openmldb-0.8.1-linux.tar.gz
+cd openmldb-0.8.1-linux
 ```
 
 ### Configuration
@@ -163,9 +163,9 @@ Environment Requirements:
 ### Download the OpenMLDB Deployment Package
 
 ```
-wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz
-tar -zxvf openmldb-0.8.0-linux.tar.gz
-cd openmldb-0.8.0-linux
+wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz
+tar -zxvf openmldb-0.8.1-linux.tar.gz
+cd openmldb-0.8.1-linux
 ```
 
 ### Configuration
@@ -175,7 +175,7 @@ which are listed below.
 
 | Environment Variables             | Default Values                                          | Definitons                                                                                            |
 |-----------------------------------|---------------------------------------------------------|-------------------------------------------------------------------------------------------------------|
-| OPENMLDB_VERSION                  | 0.8.0                                                   | OpenMLDB version                                                                                      |
+| OPENMLDB_VERSION                  | 0.8.1                                                   | OpenMLDB version                                                                                      |
 | OPENMLDB_MODE                     | standalone                                              | standalone or cluster mode                                                                            |
 | OPENMLDB_HOME                     | root directory of the release folder                    | openmldb root path                                                                                    |
 | SPARK_HOME                        | $OPENMLDB_HOME/spark                                    | the root path of openmldb spark release. if not exists, download from online                          |
@@ -311,10 +311,10 @@ Deploy the Zookeeper cluster [refer to here](https://zookeeper.apache.org/doc/r3
 #### 1. Download the OpenMLDB Deployment Package
 
 ```
-wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz
-tar -zxvf openmldb-0.8.0-linux.tar.gz
-mv openmldb-0.8.0-linux openmldb-tablet-0.8.0
-cd openmldb-tablet-0.8.0
+wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz
+tar -zxvf openmldb-0.8.1-linux.tar.gz
+mv openmldb-0.8.1-linux openmldb-tablet-0.8.1
+cd openmldb-tablet-0.8.1
 ```
 
 #### 2. Modify the Configuration File: conf/tablet.flags
@@ -361,10 +361,10 @@ Repeat the above steps to deploy multiple tablets.
 #### 1. Download the OpenMLDB Deployment Package
 
 ```
-wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz
-tar -zxvf openmldb-0.8.0-linux.tar.gz
-mv openmldb-0.8.0-linux openmldb-ns-0.8.0
-cd openmldb-ns-0.8.0
+wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz
+tar -zxvf openmldb-0.8.1-linux.tar.gz
+mv openmldb-0.8.1-linux openmldb-ns-0.8.1
+cd openmldb-ns-0.8.1
 ```
 
 #### 2. Modify the Configuration File: conf/nameserver.flags
@@ -411,10 +411,10 @@ Before running, make sure that the OpenMLDB cluster has been started, otherwise
 #### 1. Download the OpenMLDB Deployment Package
 
 ```
-wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz
-tar -zxvf openmldb-0.8.0-linux.tar.gz
-mv openmldb-0.8.0-linux openmldb-apiserver-0.8.0
-cd openmldb-apiserver-0.8.0
+wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz
+tar -zxvf openmldb-0.8.1-linux.tar.gz
+mv openmldb-0.8.1-linux openmldb-apiserver-0.8.1
+cd openmldb-apiserver-0.8.1
 ```
 
 #### 2. Modify the Configuration File: conf/apiserver.flags
@@ -454,12 +454,12 @@ TaskManager can be deployed in single server. You can deploy multiple instances
 #### 1. Download the OpenMLDB Spark Distribution that is Optimized for Feature Engineering
 
 ```
-wget https://github.com/4paradigm/spark/releases/download/v3.2.1-openmldb0.8.0/spark-3.2.1-bin-openmldbspark.tgz
+wget https://github.com/4paradigm/spark/releases/download/v3.2.1-openmldb0.8.1/spark-3.2.1-bin-openmldbspark.tgz
 tar -zxvf spark-3.2.1-bin-openmldbspark.tgz
-wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.0/openmldb-0.8.0-linux.tar.gz
-tar -zxvf openmldb-0.8.0-linux.tar.gz
-mv openmldb-0.8.0-linux openmldb-taskmanager-0.8.0
-cd openmldb-taskmanager-0.8.0
+wget https://github.com/4paradigm/OpenMLDB/releases/download/v0.8.1/openmldb-0.8.1-linux.tar.gz
+tar -zxvf openmldb-0.8.1-linux.tar.gz
+mv openmldb-0.8.1-linux openmldb-taskmanager-0.8.1
+cd openmldb-taskmanager-0.8.1
 ```
 
 #### 2. Modify the Configuration File conf/taskmanager.properties

docs/en/quickstart/java_sdk.md

@@ -9,12 +9,12 @@ Configure maven pom
 <dependency>
     <groupId>com.4paradigm.openmldb</groupId>
     <artifactId>openmldb-jdbc</artifactId>
-    <version>0.8.0</version>
+    <version>0.8.1</version>
 </dependency>
 <dependency>
     <groupId>com.4paradigm.openmldb</groupId>
     <artifactId>openmldb-native</artifactId>
-    <version>0.8.0</version>
+    <version>0.8.1</version>
 </dependency>
 ```
 ### Package Installation on Mac
@@ -24,15 +24,15 @@ Configure maven pom
 <dependency>
     <groupId>com.4paradigm.openmldb</groupId>
     <artifactId>openmldb-jdbc</artifactId>
-    <version>0.8.0</version>
+    <version>0.8.1</version>
 </dependency>
 <dependency>
     <groupId>com.4paradigm.openmldb</groupId>
     <artifactId>openmldb-native</artifactId>
-    <version>0.8.0-macos</version>
+    <version>0.8.1-macos</version>
 </dependency>
 ```
-Note that since `openmldb-native` contains the C++ static library compiled by OpenMLDB, by default it is a Linux's static library. On macOS, the version of the above openmldb-native needs to be changed to `0.8.0-macos`, and the version of openmldb-jdbc remains unchanged.
+Note that since `openmldb-native` contains the C++ static library compiled by OpenMLDB, by default it is a Linux's static library. On macOS, the version of the above openmldb-native needs to be changed to `0.8.1-macos`, and the version of openmldb-jdbc remains unchanged.
 
 The macOS native relase only supports macos-12. If you want use in macos-11 or macos 10.15, you should build openmldb-native from source in macos-11/macos-10.15, see [Build Java SDK](../deploy/compile.md#build-java-sdk-with-multi-processes) for details.
 

docs/en/quickstart/openmldb_quickstart.md

@@ -17,7 +17,7 @@ If you wan to compile and install it by yourself, you can refer to our [installa
 Pull the image (image download size is about 1GB, after decompression is about 1.7 GB) and start the docker container:
 
 ```bash
-docker run -it 4pdosc/openmldb:0.8.0 bash
+docker run -it 4pdosc/openmldb:0.8.1 bash
 ```
 
 ```{important}

docs/en/reference/ip_tips.md

@@ -38,12 +38,12 @@ Expose the port through `-p` when starting the container, and the client can acc
 
 The stand-alone version needs to expose the ports of three components (nameserver, tabletserver, apiserver):
 ```
-docker run -p 6527:6527 -p 9921:9921 -p 8080:8080 -it 4pdosc/openmldb:0.8.0 bash
+docker run -p 6527:6527 -p 9921:9921 -p 8080:8080 -it 4pdosc/openmldb:0.8.1 bash
 ```
 
 The cluster version needs to expose the zk port and the ports of all components:
 ```
-docker run -p 2181:2181 -p 7527:7527 -p 10921:10921 -p 10922:10922 -p 8080:8080 -p 9902:9902 -it 4pdosc/openmldb:0.8.0 bash
+docker run -p 2181:2181 -p 7527:7527 -p 10921:10921 -p 10922:10922 -p 8080:8080 -p 9902:9902 -it 4pdosc/openmldb:0.8.1 bash
 ```
 
 ```{tip}
@@ -57,7 +57,7 @@ If the OpenMLDB service process is distributed, the "port number is occupied" ap
 #### Host Network
 Or more conveniently, use host networking without port isolation, for example:
 ```
-docker run --network host -it 4pdosc/openmldb:0.8.0 bash
+docker run --network host -it 4pdosc/openmldb:0.8.1 bash
 ```
 But in this case, it is easy to find that the port is occupied by other processes in the host. If occupancy occurs, change the port number carefully.
 

docs/en/use_case/JD_recommendation_en.md

@@ -52,7 +52,7 @@ Oneflow-serving：https://github.com/Oneflow-Inc/serving/tree/ce5d667468b6b3ba66
 Pull the OpenMLDB docker image and run.
 
 ```bash
-docker run -dit --name=openmldb --network=host -v $demodir:/work/oneflow_demo 4pdosc/openmldb:0.8.0 bash
+docker run -dit --name=openmldb --network=host -v $demodir:/work/oneflow_demo 4pdosc/openmldb:0.8.1 bash
 docker exec -it openmldb bash
 ```
 

docs/en/use_case/airflow_provider_demo.md

@@ -34,7 +34,7 @@ For the newest version, please visit [GitHub example_dags](https://github.com/4p
 - Please project the previously downloaded files to the path `/work/airflow/dags`, where Airflow will access for the DAG.
 
 ```
-docker run -p 8080:8080 -v `pwd`/airflow_demo_files:/work/airflow/dags -it 4pdosc/openmldb:0.8.0 bash
+docker run -p 8080:8080 -v `pwd`/airflow_demo_files:/work/airflow/dags -it 4pdosc/openmldb:0.8.1 bash
 ```
 
 #### 0.3 Download and Install the Airflow and the Airflow OpenMLDB Provider