diff --git a/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md index 3a8d66b39..fd7beb423 100644 --- a/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### 1.2 Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### 1.3 Deployment mode
@@ -82,42 +82,31 @@ Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - 3. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: +3. Verify Python version ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
-> Close the current SSH window and reconnect - - 4. Create a dedicated environment - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` +4. Create a virtual environment (execute in the ainode directory) - Type 'y' according to the prompt + ```shell + python -m venv venv + ``` - 5. Activate dedicated environment +5. Activate the virtual environment -```shell - conda activate ainode_py - ``` + ```shell + source venv/bin/activate + ``` - 6. Verify Python version -```shell - python --version - ``` - 7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package + 6. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. Configuration item modification + 7. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -127,13 +116,13 @@ > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 9. Replace Python source + 8. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. Start the AINode node + 9. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md index 87aa7e3ba..c51a589f1 100644 --- a/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### 1.2 Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### 1.3 Deployment mode
@@ -107,71 +107,59 @@ ./start-datanode.sh -d #The parameter'd 'will be started in the background ``` - 2. Check the kernel architecture of Linux +2. Check the kernel architecture of Linux ```shell uname -m - ``` + ``` - 3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) +3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - 4. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: - - ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
- > Close the current SSH window and reconnect +4. Verify Python version - 5. Create a dedicated environment +```shell + python --version + ``` +5. Create a virtual environment (execute in the ainode directory) ```shell - conda create -n ainode_py python=3.11.9 - ``` + python -m venv venv + ``` - Type 'y' according to the prompt - - 6. Activate dedicated environment +6. Activate the virtual environment ```shell - conda activate ainode_py - ``` + source venv/bin/activate + ``` - 7. Verify Python version - - ```shell - python --version - ``` - 8. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package +7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + ``` - 9. Configuration item modification +8. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + ``` Configuration item modification：[detailed information](#configuration-item-modification) > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 10. Replace Python source +9. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + ``` - 11. Start the AINode node +10. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + ``` > Return to the default environment of the system: conda deactivate ### 3.2 Configuration item modification diff --git a/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md index f515d8c05..91de30f31 100644 --- a/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### Deployment mode
@@ -82,42 +82,31 @@ Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - 3. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: + 3. Verify Python version ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
-> Close the current SSH window and reconnect - - 4. Create a dedicated environment - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` +4. Create a virtual environment (execute in the ainode directory) - Type 'y' according to the prompt + ```shell + python -m venv venv + ``` - 5. Activate dedicated environment +5. Activate the virtual environment -```shell - conda activate ainode_py - ``` + ```shell + source venv/bin/activate + ``` - 6. Verify Python version -```shell - python --version - ``` - 7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package +6. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. Configuration item modification + 7. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -127,13 +116,13 @@ > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 9. Replace Python source +8. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. Start the AINode node +9. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md index 89b9cc9c6..5374f19a2 100644 --- a/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### Deployment mode
@@ -107,71 +107,59 @@ ./start-datanode.sh -d #The parameter'd 'will be started in the background ``` - 2. Check the kernel architecture of Linux +2. Check the kernel architecture of Linux ```shell - uname -m - ``` + uname -m + ``` - 3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) +3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) - Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - - 4. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: + Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
- > Close the current SSH window and reconnect + 4. Verify Python version - 5. Create a dedicated environment +```shell + python --version + ``` +5. Create a virtual environment (execute in the ainode directory) ```shell - conda create -n ainode_py python=3.11.9 - ``` - - Type 'y' according to the prompt + python -m venv venv + ``` - 6. Activate dedicated environment +6. Activate the virtual environment ```shell - conda activate ainode_py - ``` + source venv/bin/activate + ``` - 7. Verify Python version - - ```shell - python --version - ``` - 8. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package + 7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + ``` - 9. Configuration item modification + 8. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + ``` Configuration item modification：[detailed information](#configuration-item-modification) > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 10. Replace Python source + 9. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + ``` - 11. Start the AINode node + 10. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + ``` > Return to the default environment of the system: conda deactivate ### Configuration item modification diff --git a/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md index f515d8c05..91de30f31 100644 --- a/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### Deployment mode
@@ -82,42 +82,31 @@ Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - 3. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: + 3. Verify Python version ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
-> Close the current SSH window and reconnect - - 4. Create a dedicated environment - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` +4. Create a virtual environment (execute in the ainode directory) - Type 'y' according to the prompt + ```shell + python -m venv venv + ``` - 5. Activate dedicated environment +5. Activate the virtual environment -```shell - conda activate ainode_py - ``` + ```shell + source venv/bin/activate + ``` - 6. Verify Python version -```shell - python --version - ``` - 7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package +6. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. Configuration item modification + 7. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -127,13 +116,13 @@ > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 9. Replace Python source +8. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. Start the AINode node +9. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md index 89b9cc9c6..5374f19a2 100644 --- a/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### Deployment mode
@@ -107,71 +107,59 @@ ./start-datanode.sh -d #The parameter'd 'will be started in the background ``` - 2. Check the kernel architecture of Linux +2. Check the kernel architecture of Linux ```shell - uname -m - ``` + uname -m + ``` - 3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) +3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) - Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - - 4. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: + Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
- > Close the current SSH window and reconnect + 4. Verify Python version - 5. Create a dedicated environment +```shell + python --version + ``` +5. Create a virtual environment (execute in the ainode directory) ```shell - conda create -n ainode_py python=3.11.9 - ``` - - Type 'y' according to the prompt + python -m venv venv + ``` - 6. Activate dedicated environment +6. Activate the virtual environment ```shell - conda activate ainode_py - ``` + source venv/bin/activate + ``` - 7. Verify Python version - - ```shell - python --version - ``` - 8. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package + 7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + ``` - 9. Configuration item modification + 8. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + ``` Configuration item modification：[detailed information](#configuration-item-modification) > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 10. Replace Python source + 9. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + ``` - 11. Start the AINode node + 10. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + ``` > Return to the default environment of the system: conda deactivate ### Configuration item modification diff --git a/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md index 3a8d66b39..fd7beb423 100644 --- a/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### 1.2 Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### 1.3 Deployment mode
@@ -82,42 +82,31 @@ Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - 3. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: +3. Verify Python version ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
-> Close the current SSH window and reconnect - - 4. Create a dedicated environment - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` +4. Create a virtual environment (execute in the ainode directory) - Type 'y' according to the prompt + ```shell + python -m venv venv + ``` - 5. Activate dedicated environment +5. Activate the virtual environment -```shell - conda activate ainode_py - ``` + ```shell + source venv/bin/activate + ``` - 6. Verify Python version -```shell - python --version - ``` - 7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package + 6. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. Configuration item modification + 7. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -127,13 +116,13 @@ > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 9. Replace Python source + 8. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. Start the AINode node + 9. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md index 87aa7e3ba..c51a589f1 100644 --- a/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode is the third type of endogenous node provided by IoTDB after the Configurable Node and DataNode. This node extends its ability to perform machine learning analysis on time series by interacting with the DataNode and Configurable Node of the IoTDB cluster. It supports the introduction of existing machine learning models from external sources for registration and the use of registered models to complete time series analysis tasks on specified time series data through simple SQL statements. The creation, management, and inference of models are integrated into the database engine. Currently, machine learning algorithms or self-developed models are available for common time series analysis scenarios, such as prediction and anomaly detection. ### 1.2 Delivery Method - It is an additional package outside the IoTDB cluster, with independent installation and activation. + It is an additional package outside the IoTDB cluster, with independent installation. ### 1.3 Deployment mode
@@ -107,71 +107,59 @@ ./start-datanode.sh -d #The parameter'd 'will be started in the background ``` - 2. Check the kernel architecture of Linux +2. Check the kernel architecture of Linux ```shell uname -m - ``` + ``` - 3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) +3. Import Python environment [Download](https://repo.anaconda.com/miniconda/) Recommend downloading the py311 version application and importing it into the iotdb dedicated folder in the user's root directory - 4. Switch to the iotdb dedicated folder to install the Python environment - - Taking Miniconda 3-py311_24.5.0-0-Lux-x86_64 as an example: - - ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > Type "Enter", "Long press space", "Enter", "Yes", "Yes" according to the prompt
- > Close the current SSH window and reconnect +4. Verify Python version - 5. Create a dedicated environment +```shell + python --version + ``` +5. Create a virtual environment (execute in the ainode directory) ```shell - conda create -n ainode_py python=3.11.9 - ``` + python -m venv venv + ``` - Type 'y' according to the prompt - - 6. Activate dedicated environment +6. Activate the virtual environment ```shell - conda activate ainode_py - ``` + source venv/bin/activate + ``` - 7. Verify Python version - - ```shell - python --version - ``` - 8. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package +7. Download and import AINode to a dedicated folder, switch to the dedicated folder and extract the installation package ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + ``` - 9. Configuration item modification +8. Configuration item modification ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + ``` Configuration item modification：[detailed information](#configuration-item-modification) > ain_seed_config_node=iotdb-1:10710 (Cluster communication node IP: communication node port)
> ain_inference_rpc_address=iotdb-3 (IP address of the server running AINode) - 10. Replace Python source +9. Replace Python source ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + ``` - 11. Start the AINode node +10. Start the AINode node ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + ``` > Return to the default environment of the system: conda deactivate ### 3.2 Configuration item modification diff --git a/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md index 46578b158..906cf2ee6 100644 --- a/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 1.2 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 1.3 部署模式
@@ -80,42 +80,32 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 -3. 切换至iotdb专用文件夹安装Python环境 -以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +3. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
-> 关闭当前SSH窗口重新连接 - - 4. 创建专用环境 - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` - 根据提示键入“y” +4. 创建虚拟环境（在 ainode 目录下执行）： - 5. 激活专用环境 + ```shell + python -m venv venv + ``` -```shell - conda activate ainode_py - ``` +5. 激活虚拟环境： - 6. 验证Python版本 + ```shell + source venv/bin/activate + ``` -```shell - python --version - ``` - 7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 +6. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. 配置项修改 +7. 配置项修改 ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -124,13 +114,13 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 9. 更换Python源 +8. 更换Python源 ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. 启动AINode节点 +9. 启动AINode节点 ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md index 34c05d4e8..7fff11b9c 100644 --- a/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/zh/UserGuide/Master/Tree/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 1.2 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 1.3 部署模式
@@ -105,70 +105,60 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， ./start-datanode.sh -d #-d参数将在后台进行启动 ``` - 2. 检查Linux的内核架构 +2. 检查Linux的内核架构 ```shell - uname -m - ``` + uname -m + ``` - 3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) +3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) - 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 + 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 - 4. 切换至iotdb专用文件夹安装Python环境 - 以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +4. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
- > 关闭当前SSH窗口重新连接 + python --version + ``` - 5. 创建专用环境 +5. 创建虚拟环境（在 ainode 目录下执行）： ```shell - conda create -n ainode_py python=3.11.9 - ``` + python -m venv venv + ``` - 根据提示键入“y” - - 6. 激活专用环境 +6. 激活虚拟环境： ```shell - conda activate ainode_py - ``` - - 7. 验证Python版本 + source venv/bin/activate + ``` - ```shell - python --version - ``` - 8. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 +7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell - unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + unzip iotdb-enterprise-ainode-1.3.3.2.zip + ``` - 9. 配置项修改 +8. 配置项修改 ```shell - vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties + ``` 配置项修改：[详细信息](#配置项修改) > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 10. 更换Python源 +9. 更换Python源 ```shell - pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ + ``` - 11. 启动AINode节点 +10. 启动AINode节点 ```shell - nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & + ``` > 回到系统默认环境：conda deactivate ### 3.2 配置项修改 diff --git a/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md index 5f558135e..da95a66a6 100644 --- a/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 部署模式
@@ -80,42 +80,30 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 -3. 切换至iotdb专用文件夹安装Python环境 - -以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +3. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
-> 关闭当前SSH窗口重新连接 - - 4. 创建专用环境 - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` - 根据提示键入“y” - - 5. 激活专用环境 +4. 创建虚拟环境（在 ainode 目录下执行）： -```shell - conda activate ainode_py - ``` + ```shell + python -m venv venv + ``` - 6. 验证Python版本 +5. 激活虚拟环境： -```shell - python --version - ``` - 7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 + ```shell + source venv/bin/activate + ``` +6. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. 配置项修改 +7. 配置项修改 ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -124,13 +112,13 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 9. 更换Python源 +8. 更换Python源 ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. 启动AINode节点 +9. 启动AINode节点 ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md index df3a98b00..adeb7cb03 100644 --- a/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/zh/UserGuide/V1.3.x/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 部署模式
@@ -105,70 +105,59 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， ./start-datanode.sh -d #-d参数将在后台进行启动 ``` - 2. 检查Linux的内核架构 +2. 检查Linux的内核架构 ```shell uname -m - ``` + ``` - 3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) +3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 - 4. 切换至iotdb专用文件夹安装Python环境 - - 以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +4. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
- > 关闭当前SSH窗口重新连接 + python --version + ``` - 5. 创建专用环境 +5. 创建虚拟环境（在 ainode 目录下执行）： ```shell - conda create -n ainode_py python=3.11.9 - ``` + python -m venv venv + ``` - 根据提示键入“y” - - 6. 激活专用环境 +6. 激活虚拟环境： ```shell - conda activate ainode_py - ``` + source venv/bin/activate + ``` - 7. 验证Python版本 - - ```shell - python --version - ``` - 8. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 +7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + ``` - 9. 配置项修改 +8. 配置项修改 ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + ``` 配置项修改：[详细信息](#配置项修改) > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 10. 更换Python源 +9. 更换Python源 ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + ``` - 11. 启动AINode节点 +10. 启动AINode节点 ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + ``` > 回到系统默认环境：conda deactivate ### 配置项修改 diff --git a/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md index 4a044b0a6..da95a66a6 100644 --- a/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活）。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 部署模式
@@ -80,42 +80,30 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 -3. 切换至iotdb专用文件夹安装Python环境 - -以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +3. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
-> 关闭当前SSH窗口重新连接 - - 4. 创建专用环境 - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` - 根据提示键入“y” - - 5. 激活专用环境 +4. 创建虚拟环境（在 ainode 目录下执行）： -```shell - conda activate ainode_py - ``` + ```shell + python -m venv venv + ``` - 6. 验证Python版本 +5. 激活虚拟环境： -```shell - python --version - ``` - 7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 + ```shell + source venv/bin/activate + ``` +6. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. 配置项修改 +7. 配置项修改 ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -124,13 +112,13 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 9. 更换Python源 +8. 更换Python源 ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. 启动AINode节点 +9. 启动AINode节点 ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md index df3a98b00..adeb7cb03 100644 --- a/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/zh/UserGuide/dev-1.3/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 部署模式
@@ -105,70 +105,59 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， ./start-datanode.sh -d #-d参数将在后台进行启动 ``` - 2. 检查Linux的内核架构 +2. 检查Linux的内核架构 ```shell uname -m - ``` + ``` - 3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) +3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 - 4. 切换至iotdb专用文件夹安装Python环境 - - 以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +4. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
- > 关闭当前SSH窗口重新连接 + python --version + ``` - 5. 创建专用环境 +5. 创建虚拟环境（在 ainode 目录下执行）： ```shell - conda create -n ainode_py python=3.11.9 - ``` + python -m venv venv + ``` - 根据提示键入“y” - - 6. 激活专用环境 +6. 激活虚拟环境： ```shell - conda activate ainode_py - ``` + source venv/bin/activate + ``` - 7. 验证Python版本 - - ```shell - python --version - ``` - 8. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 +7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + ``` - 9. 配置项修改 +8. 配置项修改 ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + ``` 配置项修改：[详细信息](#配置项修改) > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 10. 更换Python源 +9. 更换Python源 ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + ``` - 11. 启动AINode节点 +10. 启动AINode节点 ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + ``` > 回到系统默认环境：conda deactivate ### 配置项修改 diff --git a/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md b/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md index 46578b158..906cf2ee6 100644 --- a/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md +++ b/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_apache.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 1.2 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 1.3 部署模式
@@ -80,42 +80,32 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 -3. 切换至iotdb专用文件夹安装Python环境 -以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +3. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` -> 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
-> 关闭当前SSH窗口重新连接 - - 4. 创建专用环境 - -```shell - conda create -n ainode_py python=3.11.9 + python --version ``` - 根据提示键入“y” +4. 创建虚拟环境（在 ainode 目录下执行）： - 5. 激活专用环境 + ```shell + python -m venv venv + ``` -```shell - conda activate ainode_py - ``` +5. 激活虚拟环境： - 6. 验证Python版本 + ```shell + source venv/bin/activate + ``` -```shell - python --version - ``` - 7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 +6. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell unzip iotdb-enterprise-ainode-1.3.3.2.zip ``` - 8. 配置项修改 +7. 配置项修改 ```shell vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties @@ -124,13 +114,13 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 9. 更换Python源 +8. 更换Python源 ```shell pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ ``` - 10. 启动AINode节点 +9. 启动AINode节点 ```shell nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & diff --git a/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md b/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md index 34c05d4e8..7fff11b9c 100644 --- a/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md +++ b/src/zh/UserGuide/latest/Deployment-and-Maintenance/AINode_Deployment_timecho.md @@ -27,7 +27,7 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点，该节点通过与 IoTDB 集群的 DataNode、ConfigNode 的交互，扩展了对时间序列进行机器学习分析的能力，支持从外部引入已有机器学习模型进行注册，并使用注册的模型在指定时序数据上通过简单 SQL 语句完成时序分析任务的过程，将模型的创建、管理及推理融合在数据库引擎中。目前已提供常见时序分析场景（例如预测与异常检测）的机器学习算法或自研模型。 ### 1.2 交付方式 - 是 IoTDB 集群外的额外套件，独立安装包，独立激活。 + 是 IoTDB 集群外的额外套件，独立安装包。 ### 1.3 部署模式
@@ -105,70 +105,60 @@ AINode 是 IoTDB 在 ConfigNode、DataNode 后提供的第三种内生节点， ./start-datanode.sh -d #-d参数将在后台进行启动 ``` - 2. 检查Linux的内核架构 +2. 检查Linux的内核架构 ```shell - uname -m - ``` + uname -m + ``` - 3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) +3. 导入Python环境[下载](https://repo.anaconda.com/miniconda/) - 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 + 推荐下载py311版本应用，导入至用户根目录下 iotdb专用文件夹 中 - 4. 切换至iotdb专用文件夹安装Python环境 - 以 Miniconda3-py311_24.5.0-0-Linux-x86_64 为例： +4. 验证Python版本 ```shell - bash ./Miniconda3-py311_24.5.0-0-Linux-x86_64.sh - ``` - > 根据提示键入“回车”、“长按空格”、“回车”、“yes”、“yes”
- > 关闭当前SSH窗口重新连接 + python --version + ``` - 5. 创建专用环境 +5. 创建虚拟环境（在 ainode 目录下执行）： ```shell - conda create -n ainode_py python=3.11.9 - ``` + python -m venv venv + ``` - 根据提示键入“y” - - 6. 激活专用环境 +6. 激活虚拟环境： ```shell - conda activate ainode_py - ``` - - 7. 验证Python版本 + source venv/bin/activate + ``` - ```shell - python --version - ``` - 8. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 +7. 下载导入AINode到专用文件夹，切换到专用文件夹并解压安装包 ```shell - unzip iotdb-enterprise-ainode-1.3.3.2.zip - ``` + unzip iotdb-enterprise-ainode-1.3.3.2.zip + ``` - 9. 配置项修改 +8. 配置项修改 ```shell - vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties - ``` + vi iotdb-enterprise-ainode-1.3.3.2/conf/iotdb-ainode.properties + ``` 配置项修改：[详细信息](#配置项修改) > ain_seed_config_node=iotdb-1:10710（集群通讯节点IP:通讯节点端口）
> ain_inference_rpc_address=iotdb-3（运行AINode的服务器IP） - 10. 更换Python源 +9. 更换Python源 ```shell - pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ - ``` + pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/ + ``` - 11. 启动AINode节点 +10. 启动AINode节点 ```shell - nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & - ``` + nohup bash iotdb-enterprise-ainode-1.3.3.2/sbin/start-ainode.sh > myout.file 2>& 1 & + ``` > 回到系统默认环境：conda deactivate ### 3.2 配置项修改