I have S3 bucket which has thousands of folders having millions of files.
The problem is, many files has special characters like Comma, #, £ which is causing broken url.
Is there any way I can remove specific special characters from all the files?
I have tried using cli command aws s3 mv <source_file_name> <new_file_name>, But there also I am not able to access some of the files because of special characters.
Is there a way or script which can be useful?
Related
I Have a bucket with 3 million objects. I Even don't know how many folders are there in my S3 bucket and even don't know the names of folders in my bucket.I want to show only list of folders of AWS s3. Is there any way to get list of all folders ?
I would use AWS CLI for this. To get started - have a look here.
Then it is a matter of almost standard linux commands (ls):
aws s3 ls s3://<bucket_name>/path/to/search/folder/ --recursive | grep '/$' > folders.txt
where:
grep command just reads what aws s3 ls command has returned and searches for entries with ending /.
ending > folders.txt saves output to a file.
Note: grep (if I'm not wrong) is unix only utility command. But I believe, you can achieve this on windows as well.
Note 2: depending on the number of files there this operation might (will) take a while.
Note 3: usually in systems like AWS S3, term folder is there only for user to maintain visual similarity with standard file systems however inside it does treat it as a part of a key. You can see in your (web) console when you filter by "prefix".
Amazon S3 buckets with large quantities of objects are very difficult to use. The API calls that list bucket contents are limited to returning 1000 objects per API call. While it is possible to request 'folders' (by using Delimiter='/' and looking at CommonPrefixes), this would take repeated calls to obtain the hierarchy.
Instead, I would recommend using Amazon S3 Inventory, which can provide a daily or weekly CSV file listing all objects. You can then play with that CSV file from code (or possibly Excel? Might be too big?) to obtain your desired listings.
Just be aware that doing anything on that bucket will not be fast.
I am reading data from S3 bucket using Athena and the data from following file is correct.
# aws s3 ls --human s3://some_bucket/email_backup/email1/
2020-08-17 07:00:12 0 Bytes
2020-08-17 07:01:29 5.0 GiB email_logs_old1.csv.gz
When I change the path to _updated as shown below, I get an error.
# aws s3 ls --human s3://some_bucket/email_backup_updated/email1/
2020-08-22 12:01:36 5.0 GiB email_logs_old1.csv.gz
2020-08-22 11:41:18 5.0 GiB
This is because of the extra file without name in the same location. I have no idea how I managed to upload a file without a name. I will like to know how to repeat it (so that I can avoid it)
All S3 files have a name (in fact the full path is actually the object key, which is the metadata to define your object name).
If you see a blank named file in the path of s3://some_bucket/email_backup_updated/email1/ you have likely created a file named s3://some_bucket/email_backup_updated/email1/.
As I mentioned earlier S3 objects use key, for this reason the file hierarchy does not exist. You simply are filtering by prefix instead.
You should be able to validate this by performing the following without the trailing slash aws s3 ls --human s3://some_bucket/email_backup_updated/email1.
If you add an extra non-breaking space at the end of the destination path, the file will be copied to S3 but with a blank name. for e.g.
aws s3 cp t.txt s3://some_bucket_123/email_backup_updated/email1/
(Note the non-breaking space after email1/ )
\xa0 is actually non-breaking space in Latin1, also chr(160). The non breaking space itself is the name of the file!
Using the same logic, I can remove the "space" file by adding the non-breaking space at the end.
aws s3 rm s3://some_bucket_123/email_backup_updated/email1/
I can also login to console and remove it from User Interface.
I have a s3 bucket which is mapped to a domian say xyz.com . When ever a user register on xyz.com a file is created and stored in s3 bucket. Now i have 1000 of files in s3 and I want to replace some text in those files. All files have common name in start ex abc-{rand}.txt
The safest way of doing this would be to regenerate them again through the same process you originally used.
Personally I would try to avoid find and replace as it could lead to modifying parts that you did not intend.
Run multiple generations in parallel and override the existing files. This will ensure the files you generate will match your expectation and will not need to be modified again.
As a suggestion enable versioning before any of these interactions if you want the ability to rollback quickly in a scenario where it needs to be reverted.
Sadly, you can't do this in place in S3. You have to download them, change their content and re-upload.
This is because S3 is an object storage system, not regular file system.
To simply working with S3 files, you can use third part tool s3fs-fuse. The tool will make the S3 appear like a filesystem on your os.
I have many folders in Google Cloud Storage that contain square brackets in the name. gsutil sees square brackets as wild cards and I am unable to download the project. Can I download folders another way?
I tried using the escape character and quotes. These do not work.
gsutil cp gs://myBucket/[Projects]Number1 /Volumes/DriveName/Desktop
The result is to download files from Google Cloud Storage to my local computer.
gsutil doesn't have a way to escape wildcard characters in file / object names. There's an open issue about this: https://github.com/GoogleCloudPlatform/gsutil/issues/220
Basically, you'll have to use a different tool (or write some code) to handle such files/objects.
I have hundreds of files I need to "Rename". They all start with the same few letters, and I need to replace these letters with the year - so easy for a find/replace tool. When I rename and save them now it throws me back to the beginning of the listing hundreds of files away.
A find & Replace would mean I could do a batch renaming in one go. I searched for a way to do this, but no luck.
If only the page would not refresh, even S3 browser throws me back to the beginning.
Thanks for your thoughts ~