AWS DMS本身不支持将数据流式传输到S3 Glacier，但是可以使用Lambda函数将数据从DMS传输到S3 Glacier。以下是解决方法的代码示例：

1. 创建Lambda函数

创建一个Lambda函数，将以下源代码复制到Lambda中。

import boto3
import os
import json
from io import BytesIO
import gzip

s3_res = boto3.resource('s3')

def lambda_handler(event, context):
    # Capture the DynamoDB stream event
    input_data = event['Records']

    # S3 bucket configuration - replace with your bucket & folder name
    bucket_name = 'my-glacier-bucket'
    folder_name = 'my_data_folder'

    # Create a new S3 object
    client = boto3.client('s3')
    key = folder_name + '/ssm-' + str(time.time()) + '.json.gz'

    byte_data = json.dumps(input_data).encode('UTF-8')

    # Compress data using GZIP compression
    gzip_data = BytesIO()
    with gzip.GzipFile(fileobj=gzip_data, mode='wb') as gz:
        gz.write(byte_data)
    data = gzip_data.getvalue()

    # Upload compressed data to S3 Glacier
    client.upload_archive(vaultName=bucket_name, body=data)

    # Log output to CloudWatch
    print('Data uploaded to S3 Glacier.')

    # Return success message
    return 'Success'

2. 将Lambda函数连接到DMS任务

在DMS任务中设置Lambda函数作为目标端点，并将输入映射到Lambda函数的输入参数。在AWS管理控制台中启动DMS任务之前，请确保按照以下格式创建表映射：

{
    "TableName": "my_table_name",
    "TableMappings": [
        {
            "Type": "Include",
            "SourceSchema": "my_source_schema",
            "SourceTable": "my_source_table",
            "TargetTable": "my_target_table",
            "TargetSchema": "my_target_schema",
            "MappingProperties": {}
        }
    ],
    "TargetEndpointArn": "arn:aws:dms:us-east-1:123456789012:endpoint:QJLTZ7VV5YB6OQF435DG5PR73M",
    "ReplicationInstanceArn": "arn:aws:dms:us-east-1:123456789012:rep:3H5PB45D9JPYSOI25LVGNAE5GI",
    "MigrationType": "full-load",
    "TableMappingsEnabled": true,
    "StreamEnabled":