amazon-web-services

问题 I have the following script: Parameters: bucket: Type: CommaDelimitedList Description: "Name of the Amazon S3 bucket that contains your file" Default: "my-bucket" fileuri: Type: String Description: "Path to the file in S3" Default: "https://my-bucket.s3.eu-west-2.amazonaws.com/oauth-private.key" authrole: Type: String Description: "Role with permissions to download the file from Amazon S3" Default: "aws-elasticbeanstalk-ec2-role" files: /var/app/current/storage/oauth-private.key: mode:

问题 I have a bucket policy that I customized from the AWS S3 docs, instead of range of IP addresses, I changed it for just one IP. The bucket name is : www.joaquinamenabar.com. The IP address 66.175.217.48 corresponds to the sub-domain: https://letsdance.joaquinamenabar.com/ { "Version": "2012-10-17", "Id": "S3PolicyId1", "Statement": [ { "Sid": "IPAllow", "Effect": "Allow", "Principal": "*", "Action": "s3:*", "Resource": "arn:aws:s3:::www.joaquinamenabar.com/*", "Condition": { "IpAddress": {"aws

问题 My goal is to have an AWS System Manager Document download a script from S3 and then run that script on the selected EC2 instance. In this case, it will be a Linux OS. According to AWS documentation for aws:downloadContent the sourceInfo Input is of type StringMap. The example code looks like this: { "schemaVersion": "2.2", "description": "aws:downloadContent", "parameters": { "sourceType": { "description": "(Required) The download source.", "type": "String" }, "sourceInfo": { "description":

问题 I am using django and deployed my application on aws_lambda . Everything worked fine until i wanted to save the content of the database in a google spreadsheet The problem is how to access/get the json.file (that would normally be located in the same folder as where i am using it) now that i am using aws_lambda in production views.py # how i would normally do it, locally scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"] credentials =

问题 My goal is to take daily snapshots of an RDS table and put it in a DynamoDB table. The table should only contain data from a single day. For this have a Data Pipeline set up to query a RDS table and publish the results into S3 in CSV format. Then a HiveActivity imports this CSV into a DynamoDB table by creating external tables for the file and an existing DynamoDB table. This works great, but older entries from the previous day still exist in the DynamoDB table. I want to do this within Data

问题 I am trying to upload multiple image to amazon s3 bucket. The size of the images which i am trying to upload is nearly 300KB each. I am using loop to upload the images. But it's taking more time compared to ios. I am using the below code to upload the images to S3. val uploadObserver = transferUtility!!.upload(bucketname, , "img_$timeStamp.jpg", File(fileUri.path!!), md, CannedAccessControlList.PublicRead) uploadObserver.setTransferListener(object : TransferListener { override fun

问题 as part of ETL to Redshift, in one of the source tables, there are 2 columns: original_timestamp - TIMESTAMP : which is the local time when the record was inserted in whichever region original_timezone_offset - Varchar : which is the offset to UTC The data looks something like this: original_timestamp original_timezone_offset 2011-06-22 11:00:00.000000 -0700 2014-11-29 17:00:00.000000 -0800 2014-12-02 22:00:00.000000 +0900 2011-06-03 09:23:00.000000 -0700 2011-07-28 03:00:00.000000 -0700 2011

问题 as part of ETL to Redshift, in one of the source tables, there are 2 columns: original_timestamp - TIMESTAMP : which is the local time when the record was inserted in whichever region original_timezone_offset - Varchar : which is the offset to UTC The data looks something like this: original_timestamp original_timezone_offset 2011-06-22 11:00:00.000000 -0700 2014-11-29 17:00:00.000000 -0800 2014-12-02 22:00:00.000000 +0900 2011-06-03 09:23:00.000000 -0700 2011-07-28 03:00:00.000000 -0700 2011

问题 We are using sagemaker instance to connect to EMR in AWS. We are having some pyspark scripts that unloads athena tables and processes them as part of pipeline. We are using athena tables using glue catalog but when we try to run the job via spark submit, our job fails Code snippet from pyspark import SparkContext, SparkConf from pyspark.context import SparkContext from pyspark.sql import Row, SQLContext, SparkSession import pyspark.sql.dataframe def process_data(): conf = SparkConf()

问题 I'm trying to get powershell to write results to AWS S3 and I can't figure out the syntax. Below is the line that is giving me trouble. If I run this without everything after the ">>" the results print on the screen. Write-host "Thumbprint=" $i.Thumbprint " Expiration Date="$i.NotAfter " InstanceID ="$instanceID.Content" Subject="$i.Subject >> Write-S3Object -BucketName arn:aws:s3:::eotss-ssl-certificatemanagement 回答1: Looks like you have an issue with >> be aware that you can't pass the