要使用C#和编程访问创建ETL作业流的AWS Glue,可以按照以下步骤进行操作:
using Amazon;
using Amazon.Glue;
using Amazon.Glue.Model;
var glueClient = new AmazonGlueClient(RegionEndpoint.USWest2);
这里的RegionEndpoint可以根据您的实际情况进行更改。
var jobFlowInput = new JobFlowInput
{
Name = "MyJobFlow",
Steps = new List
{
new StepConfig
{
Name = "Step1",
Action = new Action
{
JobCommand = new JobCommand
{
Name = "MyJob1",
ScriptLocation = "s3://my-bucket/scripts"
}
}
},
new StepConfig
{
Name = "Step2",
Action = new Action
{
JobCommand = new JobCommand
{
Name = "MyJob2",
ScriptLocation = "s3://my-bucket/scripts"
}
}
}
}
};
这里的Name是作业流的名称,Steps是作业流中每个步骤的列表。在每个步骤中,您可以指定作业名称和脚本位置。
var createJobFlowRequest = new CreateJobRequest
{
JobInput = jobFlowInput
};
var createJobFlowResponse = await glueClient.CreateJobAsync(createJobFlowRequest);
var jobFlowId = createJobFlowResponse.JobId;
这里使用CreateJobAsync方法创建作业流,并从响应中获取作业流的ID。
var describeJobFlowRequest = new DescribeJobRequest
{
JobFlowId = jobFlowId
};
DescribeJobResponse describeJobFlowResponse;
do
{
describeJobFlowResponse = await glueClient.DescribeJobAsync(describeJobFlowRequest);
var status = describeJobFlowResponse.Job.Status.State;
Console.WriteLine($"Job Flow Status: {status}");
await Task.Delay(TimeSpan.FromSeconds(10)); // 每10秒钟检查一次作业流状态
}
while (describeJobFlowResponse.Job.Status.State != JobStatus.COMPLETED);
这里使用DescribeJobAsync方法获取作业流的状态,并通过循环每10秒钟检查作业流的状态,直到作业流完成。
这就是使用C#和编程访问创建ETL作业流的AWS Glue的解决方法。您可以根据自己的需求进行修改和扩展。