这个错误通常是由于作业并行设置不正确或作业资源不足引起的。为解决此错误，请尝试以下解决步骤：

1. 调整AWS Glue作业的并行度限制，以减小并行度并减轻对资源的需求。

2. 增加作业的资源，比如增加作业的计算资源或调整分配给作业的机器学习资源的容量。

3. 确保作业的代码正确、无误，没有重复的任务或不必要的任务，这些任务会增加CPU的使用率，造成ThrottlingException。

示例代码：

1. 调整作业并行度——

import boto3

glue = boto3.client("glue")

job_name = "my-glue-job"

Get the current JobRun configuration

response = glue.get_job_run(JobName=job_name, RunId='my-run-id')

Check if the error message is due to throttling

if "Rate exceeded" in response["JobRun"]["ErrorMessage"]:

Reduce the parallelism by setting a lower Maximum Capacity

Value must be between 2 and 100

response = glue.update_job(JobName=job_name, MaxCapacity=50)

Re-run the job

response = glue.start_job_run(JobName=job_name)

2. 增加作业资源——

import boto3

glue = boto3.client('glue')

job_name = "my-glue-job"

Increase workers count

response = glue.update_job(JobName=job_name, NumberOfWorkers=5)

Increase worker type

response = glue.update_job(JobName=job_name, WorkerType='G.2X')

Increase memory allocation

response = glue.update_job(JobName=job_name, MaxCapacity=2)

Re-run the job

response = glue.start_job_run(JobName=job_name)

3. 检查代码——

import boto3

glue = boto3.client('glue')

job_name = "my