Amazon Forecast boto3 服务员

Question

我正在为 Amazon Forecast 编写一个 boto3 服务员。专门用于数据集导入作业。为此，我正在使用 DescribeDataset 操作。这个想法是等到导入作业处于活动状态时，才能在同一个 Lambda 函数或另一个函数中创建一个预测器。

描述数据集参考 https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/forecast.html#ForecastService.Client.describe_dataset

参数的选择/接受器中的预期

Status (string) --
The status of the dataset. States include:
ACTIVE
CREATE_PENDING , CREATE_IN_PROGRESS , CREATE_FAILED
DELETE_PENDING , DELETE_IN_PROGRESS , DELETE_FAILED
UPDATE_PENDING , UPDATE_IN_PROGRESS , UPDATE_FAILED
The UPDATE states apply while data is imported to the dataset from a call to the CreateDatasetImportJob operation and reflect the status of the dataset import job. For example, when the import job status is CREATE_IN_PROGRESS, the status of the dataset is UPDATE_IN_PROGRESS.

我使用以下链接作为配置服务员的指南。 https://www.2ndwatch.com/blog/use-waiters-boto3-write/

这看起来很简单，但在创建服务员时并没有什么可做的。我对 boto3 和 Lambda 很陌生。我是否犯了简单的错误、遗漏了某些内容或误解了服务员的工作方式？

感谢任何帮助。

waiter.wait() 的 DatasetArn 参数是正确的

在 Lambda 中测试以下代码后，我收到以下错误。我在目标和相关导入作业开始后不久手动运行测试。导入作业激活后执行成功。

{
  "errorMessage": "2020-06-15T15:13:21.144Z a9c5019d-94c8-4332-863e-3bac2a6c8b7f Task timed out after 3.00 seconds"
}

import boto3
from botocore.exceptions import WaiterError
from botocore.waiter import WaiterModel
from botocore.waiter import create_waiter_with_client

forecast = boto3.client('forecast')

def lambda_handler(event, context):
    delay = 10
    max_attempts = 15

    waiter_name = 'TargetImportJobStatus'
    waiter_config = {
        'version': 2,
        'waiters': {
            'TargetImportJobStatus': {
                'operation': 'DescribeDataset',
                'delay': delay,
                'maxAttempts': max_attempts,
                'acceptors': [
                    {
                        'matcher': 'path',
                        'expected': 'ACTIVE',
                        'argument': 'Status',
                        'state': 'success'
                    },
                    {
                        'matcher': 'path',
                        'expected': 'UPDATE_PENDING',
                        'argument': 'Status',
                        'state': 'retry'

                    },
                    {
                        'matcher': 'path',
                        'expected': 'UPDATE_IN_PROGRESS',
                        'argument': "Status",
                        'state': 'retry'
                    },
                    {
                        'matcher': 'path',
                        'expected': 'UPDATE_FAILED',
                        'argument': 'Status',
                        'state': 'failure'
                    }
                ],
            }
        }
    }

    waiter_model = WaiterModel(waiter_config)
    custom_waiter = create_waiter_with_client(waiter_name, waiter_model, forecast)    

    try:
        custom_waiter.wait(
            DatasetArn=target_dataset_arn
        )


    except WaiterError as e:
        print(e)

    w_name = 'RelatedImportJobStatus'
    w_config = {
        'version': 2,
        'waiters': {
            'RelatedImportJobStatus': {
                'operation': 'DescribeDataset',
                'delay': delay,
                'maxAttempts': max_attempts,
                'acceptors': [
                    {
                        'matcher': 'path',
                        'expected': 'ACTIVE',
                        'argument': 'Status',
                        'state': 'success'
                    },
                    {
                        'matcher': 'path',
                        'expected': 'UPDATE_PENDING',
                        'argument': 'Status',
                        'state': 'retry'

                    },
                    {
                        'matcher': 'path',
                        'expected': 'UPDATE_IN_PROGRESS',
                        'argument': 'Status',
                        'state': 'retry'
                    },
                    {
                        'matcher': 'path',
                        'expected': 'UPDATE_FAILED',
                        'argument': 'Status',
                        'state': 'failure'
                    }
                ],
            }
        }
    }

    w_model = WaiterModel(waiter_config)
    w_waiter = create_waiter_with_client(waiter_name, waiter_model, forecast)    

    try:
        w_waiter.wait(
            DatasetArn=related_dataset_arn
        )


    except WaiterError as e:
        print(e)

Answer 1

解决了。超时更改为 15 分钟，延迟=30，max_attempts=30