英文:
How to automate the creation of Azure Databricks cluster using python script
问题
有没有办法使用Python脚本自动创建Azure Databricks集群？
英文:
Is there any way to automate the creation of Azure Databricks Cluster creation using Python script
答案1
得分: 2
如果您不想安装任何软件包，可以直接使用Databricks REST API，只需定义一个负载并调用create cluster API，类似于以下代码：
import requests
workspace_host = "https://adb-.....azuredatabricks.net"
personal_token = "dapi...."
cluster_spec = {
"cluster_name": "my-cluster",
"node_type_id": "Standard_DS3_v2",
"spark_version": "11.3.x-scala2.12",
"num_workers": 3
}
res = requests.post(workspace_host + "/api/2.0/clusters/create",
headers={"Authorization": "Bearer " + personal_token},
json=cluster_spec)
cluster_id = res.json()['cluster_id']
但更好的方式是使用新的Databricks Python SDK，它简化了许多操作并支持更多的身份验证方法。
英文:
If you don't want to install any package, then you can use Databricks REST API directly, just define a payload, and call create cluster API. Something like this:
import requests
workspace_host = "https://adb-.....azuredatabricks.net"
personal_token = "dapi...."
cluster_spec = {
"cluster_name": "my-cluster",
"node_type_id": "Standard_DS3_v2",
"spark_version": "11.3.x-scala2.12",
"num_workers": 3
}
res = requests.post(workspace_host + "/api/2.0/clusters/create",
headers={"Authorization": "Bearer " + personal_token},
json=cluster_spec)
cluster_id = res.json()['cluster_id']
But it's better to use new Databricks SDK for Python that simplifies many operations and supporting more authentication methods.
答案2
得分: -1
可以使用Python脚本自动创建Azure Databricks集群。Azure提供了用于Python的Azure SDK。
pip install azure-mgmt-databricks
from azure.identity import DefaultAzureCredential
from azure.mgmt.databricks import DatabricksManagementClient
from azure.mgmt.databricks.models import Workspace, CreateWorkspaceParameters, Sku, ManagedResourceGroupConfiguration, ManagedResourceGroup
# 定义你的Azure订阅ID和资源组详情
subscription_id = "<your-subscription-id>"
resource_group = "<your-resource-group>"
# 创建一个Databricks管理客户端
credential = DefaultAzureCredential()
databricks_client = DatabricksManagementClient(credential, subscription_id)
# 定义集群详情
cluster_name = "<cluster-name>"
location = "<azure-region>"
workspace_name = "<databricks-workspace-name>"
node_type = "<node-type>"
worker_count = 2
# 创建一个集群
workspace = Workspace(location=location)
workspace.managed_resource_group_id = ManagedResourceGroup(id=f"/subscriptions/{subscription_id}/resourceGroups/{resource_group}")
cluster = CreateWorkspaceParameters(
sku=Sku(name=node_type, capacity=worker_count),
custom_parameters=workspace
)
databricks_client.workspaces.create_or_update(resource_group, workspace_name, cluster_name, cluster)
英文:
it is possible to automate the creation of Azure Databricks clusters using a Python script. Azure provides the Azure SDK for Python
pip install azure-mgmt-databricks
from azure.identity import DefaultAzureCredential
from azure.mgmt.databricks import DatabricksManagementClient
from azure.mgmt.databricks.models import Workspace,
CreateWorkspaceParameters, Sku, ManagedResourceGroupConfiguration,
ManagedResourceGroup
# Define your Azure subscription ID and resource group details
subscription_id = "<your-subscription-id>"
reso1urce_group = "<your-resource-group>"
# Create a Databricks management client
credential = DefaultAzureCredential()
databricks_client = DatabricksManagementClient(credential,
subscription_id)
# Define the cluster details
cluster_name = "<cluster-name>"
location = "<azure-region>"
workspace_name = "<databricks-workspace-name>"
node_type = "<node-type>"
worker_count = 2
# Create a cluster
workspace = Workspace(location=location)
workspace.managed_resource_group_id = ManagedResourceGroup(id=f"/subscriptions/{subscription_id}/resourceGroups/{resource_group}")
cluster = CreateWorkspaceParameters(
sku=Sku(name=node_type, capacity=worker_count),
custom_parameters=workspace
)
databricks_client.workspaces.create_or_update(resource_group, workspace_name, cluster_name, cluster)
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