[3.1.2-prepare][version] Modify the version to 3.1.2 (#13121)
This commit is contained in:
Kerwin
GitHub
parent
ccc3a61301
commit
116eff6663
|
|
@ -16,7 +16,7 @@
|
|||
# under the License.
|
||||
#
|
||||
HUB=apache
|
||||
TAG=3.1.1
|
||||
TAG=3.1.2
|
||||
|
||||
TZ=Asia/Shanghai
|
||||
DATABASE=postgresql
|
||||
|
|
|
|||
|
|
@ -35,11 +35,11 @@ type: application
|
|||
|
||||
# This is the chart version. This version number should be incremented each time you make changes
|
||||
# to the chart and its templates, including the app version.
|
||||
version: 3.1.1
|
||||
version: 3.1.2
|
||||
|
||||
# This is the version number of the application being deployed. This version number should be
|
||||
# incremented each time you make changes to the application.
|
||||
appVersion: 3.1.1
|
||||
appVersion: 3.1.2
|
||||
|
||||
dependencies:
|
||||
- name: postgresql
|
||||
|
|
|
|||
|
|
@ -23,7 +23,7 @@ timezone: "Asia/Shanghai"
|
|||
|
||||
image:
|
||||
registry: "dolphinscheduler.docker.scarf.sh/apache"
|
||||
tag: "3.1.1"
|
||||
tag: "3.1.2"
|
||||
pullPolicy: "IfNotPresent"
|
||||
pullSecret: ""
|
||||
master: dolphinscheduler-master
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
|
|
@ -45,7 +45,7 @@ export default {
|
|||
children: [
|
||||
{
|
||||
key: 'docs0',
|
||||
text: 'latest(3.1.1)',
|
||||
text: 'latest(3.1.2)',
|
||||
link: '/en-us/docs/latest/user_doc/about/introduction.html',
|
||||
},
|
||||
{
|
||||
|
|
|
|||
|
|
@ -30,9 +30,9 @@ Attention: DolphinScheduler itself does not depend on Hadoop, Hive, Spark, but w
|
|||
mkdir -p /opt
|
||||
cd /opt
|
||||
# decompress
|
||||
tar -zxvf apache-dolphinscheduler-3.1.1-bin.tar.gz -C /opt
|
||||
tar -zxvf apache-dolphinscheduler-3.1.2-bin.tar.gz -C /opt
|
||||
cd /opt
|
||||
mv apache-dolphinscheduler-3.1.1-bin dolphinscheduler
|
||||
mv apache-dolphinscheduler-3.1.2-bin dolphinscheduler
|
||||
```
|
||||
|
||||
```markdown
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ Start DolphinScheduler with standalone-server Docker images is the easiest way t
|
|||
you can learn DolphinScheduler's concepts and usage, with minimal cost.
|
||||
|
||||
```shell
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.1
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.2
|
||||
$ docker run --name dolphinscheduler-standalone-server -p 12345:12345 -p 25333:25333 -d apache/dolphinscheduler-standalone-server:"${DOLPHINSCHEDULER_VERSION}"
|
||||
```
|
||||
|
||||
|
|
@ -49,7 +49,7 @@ After complete the configuration, we can get the `docker-compose.yaml` file from
|
|||
form its source package, and make sure you get the right version. After download the package, you can run the commands as below.
|
||||
|
||||
```shell
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.1
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.2
|
||||
$ tar -zxf apache-dolphinscheduler-"${DOLPHINSCHEDULER_VERSION}"-src.tar.gz
|
||||
# Going to docker-compose's location
|
||||
# For Mac or Linux users
|
||||
|
|
@ -72,7 +72,7 @@ $ docker-compose --profile all up -d
|
|||
container when it up. You could start DolphinScheduler server separately if you want to reuse your exists services.
|
||||
|
||||
```shell
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.1
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.2
|
||||
# Initialize the database, make sure database <DATABASE> already exists
|
||||
$ docker run -d --name dolphinscheduler-tools \
|
||||
-e DATABASE="postgresql" \
|
||||
|
|
@ -133,5 +133,5 @@ and use `admin` and `dolphinscheduler123` as default username and password in th
|
|||
|
||||
You can modify some environment variables to change configurations when you are starting servers through Docker. We have
|
||||
an example in [using exists PostgreSQL ZooKeeper](#using-exists-postgresql-zookeeper) to change database and ZooKeeper configurations,
|
||||
and you could find all environment variables in [all environment variables](https://github.com/apache/dolphinscheduler/blob/3.1.1/script/env/dolphinscheduler_env.sh) <!-- markdown-link-check-disable-line -->
|
||||
and you could find all environment variables in [all environment variables](https://github.com/apache/dolphinscheduler/blob/3.1.2/script/env/dolphinscheduler_env.sh) <!-- markdown-link-check-disable-line -->
|
||||
and change them if you want.
|
||||
|
|
|
|||
|
|
@ -61,13 +61,13 @@ The MLflow plugin currently supports and will support the following:
|
|||
|
||||
**Task Parameter**
|
||||
|
||||
| **Parameter** | **Description** |
|
||||
|----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| Register Model | Register the model or not. If register is selected, the following parameters are expanded. |
|
||||
| model name | The registered model name is added to the original model version and registered as Production. |
|
||||
| Data Path | The absolute path of the file or folder. Ends with .csv for file or contain train.csv and test.csv for folder(In the suggested way, users should build their own test sets for model evaluation). |
|
||||
| Parameters | Parameter when initializing the algorithm/AutoML model, which can be empty. For example, parameters `n_estimators=200;learning_rate=0.2` for flaml. The convention will be passed with '; 'shards each parameter, using the name before the equal sign as the parameter name, and using the name after the equal sign to get the corresponding parameter value through `python eval()`. The detailed parameter list is as follows: <ul><li>[flaml](https://microsoft.github.io/FLAML/docs/reference/automl#automl-objects)</li><li>[autosklearn](https://automl.github.io/auto-sklearn/master/api.html)</li></ul> |
|
||||
| AutoML tool | The AutoML tool used, currently supports [autosklearn](https://github.com/automl/auto-sklearn) and [flaml](https://github.com/microsoft/FLAML). |
|
||||
| **Parameter** | **Description** |
|
||||
|----------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| Register Model | Register the model or not. If register is selected, the following parameters are expanded. |
|
||||
| model name | The registered model name is added to the original model version and registered as Production. |
|
||||
| Data Path | The absolute path of the file or folder. Ends with .csv for file or contain train.csv and test.csv for folder(In the suggested way, users should build their own test sets for model evaluation). |
|
||||
| Parameters | Parameter when initializing the algorithm/AutoML model, which can be empty. For example, parameters `n_estimators=200;learning_rate=0.2` for flaml. The convention will be passed with '; 'shards each parameter, using the name before the equal sign as the parameter name, and using the name after the equal sign to get the corresponding parameter value through `python eval()`. The detailed parameter list is as follows: <ul><li>[flaml](https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML)</li><li>[autosklearn](https://automl.github.io/auto-sklearn/master/api.html)</li></ul> |
|
||||
| AutoML tool | The AutoML tool used, currently supports [autosklearn](https://github.com/automl/auto-sklearn) and [flaml](https://github.com/microsoft/FLAML). |
|
||||
|
||||
#### Custom projects
|
||||
|
||||
|
|
|
|||
|
|
@ -4,6 +4,10 @@
|
|||
|
||||
#### Setup instructions, are available for each stable version of Apache DolphinScheduler below:
|
||||
|
||||
### Versions: 3.1.2
|
||||
|
||||
#### Links： [3.1.2 Document](../3.1.2/user_doc/about/introduction.md)
|
||||
|
||||
### Versions: 3.1.1
|
||||
|
||||
#### Links： [3.1.1 Document](../3.1.1/user_doc/about/introduction.md)
|
||||
|
|
|
|||
|
|
@ -30,9 +30,9 @@
|
|||
mkdir -p /opt
|
||||
cd /opt
|
||||
# 解压缩
|
||||
tar -zxvf apache-dolphinscheduler-3.1.1-bin.tar.gz -C /opt
|
||||
tar -zxvf apache-dolphinscheduler-3.1.2-bin.tar.gz -C /opt
|
||||
cd /opt
|
||||
mv apache-dolphinscheduler-3.1.1-bin dolphinscheduler
|
||||
mv apache-dolphinscheduler-3.1.2-bin dolphinscheduler
|
||||
```
|
||||
|
||||
```markdown
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@
|
|||
你可以最快速的体验到 DolphinScheduler 的大部分功能，了解主要和概念和内容。
|
||||
|
||||
```shell
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.1
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.2
|
||||
$ docker run --name dolphinscheduler-standalone-server -p 12345:12345 -p 25333:25333 -d apache/dolphinscheduler-standalone-server:"${DOLPHINSCHEDULER_VERSION}"
|
||||
```
|
||||
|
||||
|
|
@ -43,7 +43,7 @@ $ docker run --name dolphinscheduler-standalone-server -p 12345:12345 -p 25333:2
|
|||
源码包对应的值为 "Total Source Code"。当下载完源码后就可以运行命令进行部署了。
|
||||
|
||||
```shell
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.1
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.2
|
||||
$ tar -zxf apache-dolphinscheduler-"${DOLPHINSCHEDULER_VERSION}"-src.tar.gz
|
||||
# Mac Linux 用户
|
||||
$ cd apache-dolphinscheduler-"${DOLPHINSCHEDULER_VERSION}"-src/deploy/docker
|
||||
|
|
@ -65,7 +65,7 @@ $ docker-compose --profile all up -d
|
|||
ZooKeeper 且不想启动新的服务，可以使用这个方式分别启动 DolphinScheduler 容器。
|
||||
|
||||
```shell
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.1
|
||||
$ DOLPHINSCHEDULER_VERSION=3.1.2
|
||||
# 初始化数据库，其确保数据库 <DATABASE> 已经存在
|
||||
$ docker run -d --name dolphinscheduler-tools \
|
||||
-e DATABASE="postgresql" \
|
||||
|
|
@ -126,4 +126,4 @@ $ docker run -d --name dolphinscheduler-alert-server \
|
|||
## 环境变量
|
||||
|
||||
可以通过环境变量来修改 Docker 运行的配置，我们在沿用已有的 PostgreSQL 和 ZooKeeper 服务中就通过环境变量修改了 Docker 的数据库配置和
|
||||
注册中心配置，关于全部的配置环境可以查看[全部的配置文件](https://github.com/apache/dolphinscheduler/blob/3.1.1/script/env/dolphinscheduler_env.sh) 了解 <!-- markdown-link-check-disable-line -->
|
||||
注册中心配置，关于全部的配置环境可以查看[全部的配置文件](https://github.com/apache/dolphinscheduler/blob/3.1.2/script/env/dolphinscheduler_env.sh) 了解 <!-- markdown-link-check-disable-line -->
|
||||
|
|
|
|||
|
|
@ -57,13 +57,13 @@ MLflow 组件用于执行 MLflow 任务，目前包含Mlflow Projects，和MLflo
|
|||
|
||||
|
||||
|
||||
| **任务参数** | **描述** |
|
||||
|----------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| 注册模型 | 是否注册模型，若选择注册，则会展开以下参数 |
|
||||
| 注册的模型名称 | 注册的模型名称，会在原来的基础上加上一个模型版本，并注册为Production |
|
||||
| 数据路径 | 文件/文件夹的绝对路径，若文件需以.csv结尾（自动切分训练集与测试集），文件夹需包含train.csv和test.csv（建议方式，用户应自行构建测试集用于模型评估） |
|
||||
| 参数 | 初始化AutoML训练器时的参数，可为空，如针对 flaml 设置`time_budget=30;estimator_list=['lgbm']`。约定传入后会以; 切分各个参数，等号前的名字作为参数名，等号后的名字将以python eval执行得到对应的参数值。详细的参数列表如下: [flaml](https://microsoft.github.io/FLAML/docs/reference/automl#automl-objects)，[autosklearn](https://automl.github.io/auto-sklearn/master/api.html) |
|
||||
| AutoML工具 | 使用的AutoML工具，目前支持 [autosklearn](https://github.com/automl/auto-sklearn)，[flaml](https://github.com/microsoft/FLAML) |
|
||||
| **任务参数** | **描述** |
|
||||
|----------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| 注册模型 | 是否注册模型，若选择注册，则会展开以下参数 |
|
||||
| 注册的模型名称 | 注册的模型名称，会在原来的基础上加上一个模型版本，并注册为Production |
|
||||
| 数据路径 | 文件/文件夹的绝对路径，若文件需以.csv结尾（自动切分训练集与测试集），文件夹需包含train.csv和test.csv（建议方式，用户应自行构建测试集用于模型评估） |
|
||||
| 参数 | 初始化AutoML训练器时的参数，可为空，如针对 flaml 设置`time_budget=30;estimator_list=['lgbm']`。约定传入后会以; 切分各个参数，等号前的名字作为参数名，等号后的名字将以python eval执行得到对应的参数值。详细的参数列表如下: [flaml](https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML)，[autosklearn](https://automl.github.io/auto-sklearn/master/api.html) |
|
||||
| AutoML工具 | 使用的AutoML工具，目前支持 [autosklearn](https://github.com/automl/auto-sklearn)，[flaml](https://github.com/microsoft/FLAML) |
|
||||
|
||||
#### Custom projects
|
||||
|
||||
|
|
|
|||
|
|
@ -4,6 +4,10 @@
|
|||
|
||||
#### 以下是Apache DolphinScheduler每个稳定版本的设置说明。
|
||||
|
||||
### Versions: 3.1.2
|
||||
|
||||
#### Links： [3.1.2 文档](../3.1.2/user_doc/about/introduction.md)
|
||||
|
||||
### Versions: 3.1.1
|
||||
|
||||
#### Links： [3.1.1 文档](../3.1.1/user_doc/about/introduction.md)
|
||||
|
|
|
|||
|
|
@ -989,7 +989,7 @@ CREATE TABLE t_ds_version
|
|||
-- Records of t_ds_version
|
||||
-- ----------------------------
|
||||
INSERT INTO t_ds_version
|
||||
VALUES ('1', '3.1.1');
|
||||
VALUES ('1', '3.1.2');
|
||||
|
||||
|
||||
-- ----------------------------
|
||||
|
|
|
|||
|
|
@ -980,7 +980,7 @@ CREATE TABLE `t_ds_version` (
|
|||
-- ----------------------------
|
||||
-- Records of t_ds_version
|
||||
-- ----------------------------
|
||||
INSERT IGNORE INTO `t_ds_version` VALUES ('1', '3.1.1');
|
||||
INSERT IGNORE INTO `t_ds_version` VALUES ('1', '3.1.2');
|
||||
|
||||
|
||||
-- ----------------------------
|
||||
|
|
|
|||
|
|
@ -971,7 +971,7 @@ INSERT INTO t_ds_queue(queue_name, queue, create_time, update_time)
|
|||
VALUES ('default', 'default', '2018-11-29 10:22:33', '2018-11-29 10:22:33');
|
||||
|
||||
-- Records of t_ds_queue,default queue name : default
|
||||
INSERT INTO t_ds_version(version) VALUES ('3.1.1');
|
||||
INSERT INTO t_ds_version(version) VALUES ('3.1.2');
|
||||
|
||||
--
|
||||
-- Table structure for table t_ds_plugin_define
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
3.1.1
|
||||
3.1.2
|
||||
|
|
|
|||
|
|
@ -0,0 +1,16 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
/*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
|
@ -87,4 +87,4 @@ If you are interested in how to release **PyDolphinScheduler**, you could go and
|
|||
|
||||
## What's more
|
||||
|
||||
For more detail information, please go to see **PyDolphinScheduler** latest(unreleased) [document](https://dolphinscheduler.apache.org/python/dev/index.html)
|
||||
For more detail information, please go to see **PyDolphinScheduler** latest(unreleased) [document](https://dolphinscheduler.apache.org/python/main/index.html)
|
||||
|
|
|
|||
|
|
@ -206,7 +206,6 @@ log4j-1.2-api-2.17.2.jar
|
|||
logback-classic-1.2.11.jar
|
||||
logback-core-1.2.11.jar
|
||||
logging-interceptor-4.9.3.jar
|
||||
lz4-1.3.0.jar
|
||||
mapstruct-1.3.1.Final.jar
|
||||
metrics-core-4.2.11.jar
|
||||
micrometer-core-1.9.3.jar
|
||||
|
|
|
|||
Loading…
Reference in New Issue