amazon-s3

问题 I'm trying to use tensorboard on my local machine to read tensorflow logs on S3. Everything works but tensorboard continuously throws the following errors to the console. According to this the reason is that when Tensorflow s3 client checks if directory exists it firstly run Stat on it since s3 have no possibility to check whether directory exists. Then it checks if key with such name exists and fails with such error messages. While this could be a wanted behavior for model serving to look

问题 I'm trying to create an AWS dashboard using terraform to display the S3 metrics. I was thinking of looping through all the S3 buckets stored in a list variable and generate the dashboard json. The for loop is able to add the metrics, but I'm not able to remove the trailing comma, which results in an erroneous json. Is there an easy way to fix this json using this approach? Is there a better way to do json processing? Should I be using terraform for this processing? Code snippet :- dashboard

问题 I'm trying to create an AWS dashboard using terraform to display the S3 metrics. I was thinking of looping through all the S3 buckets stored in a list variable and generate the dashboard json. The for loop is able to add the metrics, but I'm not able to remove the trailing comma, which results in an erroneous json. Is there an easy way to fix this json using this approach? Is there a better way to do json processing? Should I be using terraform for this processing? Code snippet :- dashboard

问题 I am using AmazonS3Client to Read/Write data to S3 Object Storage. In my code i am creating a new connection everytime while doing operations like Read,List Buckets, Upload, Rename, Delete etc. After deploying my application to production i encountered some performance issues. After going throughh few blogs it was recommended to use single amazonS3 client connection. My code below -> For every below CRUD operations if you see i am creating a new connection and then disposing it by using block

问题 Is there any way to provide a suffix for paths when doing a partitioned unload to S3? e.g. if I want to use the output of +several+ queries for batch jobs, where query outputs are partitioned by date. Currently I have a structure in S3 like: s3://bucket/path/queryA/key=1/ *.parquet s3://bucket/path/queryA/key=2/ *.parquet s3://bucket/path/queryB/key=1/ *.parquet s3://bucket/path/queryB/key=2/ *.parquet But ideally, I would like to have: s3://bucket/path/key=1/queryA/ *.parquet s3://bucket

问题 Is there any way to provide a suffix for paths when doing a partitioned unload to S3? e.g. if I want to use the output of +several+ queries for batch jobs, where query outputs are partitioned by date. Currently I have a structure in S3 like: s3://bucket/path/queryA/key=1/ *.parquet s3://bucket/path/queryA/key=2/ *.parquet s3://bucket/path/queryB/key=1/ *.parquet s3://bucket/path/queryB/key=2/ *.parquet But ideally, I would like to have: s3://bucket/path/key=1/queryA/ *.parquet s3://bucket

问题 Many AWS reference architectures for serverless real-time analytics, suggest pushing processed data from Lambda to S3 through Kinesis Firehose. e.g. https://aws.amazon.com/blogs/big-data/create-real-time-clickstream-sessions-and-run-analytics-with-amazon-kinesis-data-analytics-aws-glue-and-amazon-athena/ Why can’t we push data from Lambda to S3 directly? Isn't it better to avoid complexity and additional cost by skipping the mediator Kinesis Firehose component? Is there any problem with

问题 Many AWS reference architectures for serverless real-time analytics, suggest pushing processed data from Lambda to S3 through Kinesis Firehose. e.g. https://aws.amazon.com/blogs/big-data/create-real-time-clickstream-sessions-and-run-analytics-with-amazon-kinesis-data-analytics-aws-glue-and-amazon-athena/ Why can’t we push data from Lambda to S3 directly? Isn't it better to avoid complexity and additional cost by skipping the mediator Kinesis Firehose component? Is there any problem with

问题 Many AWS reference architectures for serverless real-time analytics, suggest pushing processed data from Lambda to S3 through Kinesis Firehose. e.g. https://aws.amazon.com/blogs/big-data/create-real-time-clickstream-sessions-and-run-analytics-with-amazon-kinesis-data-analytics-aws-glue-and-amazon-athena/ Why can’t we push data from Lambda to S3 directly? Isn't it better to avoid complexity and additional cost by skipping the mediator Kinesis Firehose component? Is there any problem with

问题 My S3 bucket hosts a static website. I do not have cloudfront set up. I recently updated the files in my S3 bucket. While the files got updated, I confirmed manually in the bucket. It still serves an older version of the files. Is there some sort of caching or versioning that happens on Static websites hosted on S3? I haven't been able to find any solution on SO so far. Note: Cloudfront is NOT enabled. 回答1: Is there some sort of caching or versioning that happens on Static websites hosted on