the docs says,
For example, your application can achieve at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per prefix in a bucket. There are no limits to the number of prefixes in a bucket. You can increase your read or write performance by parallelizing reads. For example, if you create 10 prefixes in an Amazon S3 bucket to parallelize reads, you could scale your read performance to 55,000 read requests per second.
But, it doesn't clearly mentions the concept of prefixes.
For eg,
Lets say I have 3 files and their corresponding keys are:
a/a1.txt
b/b1.txt
2.txt
As per my understanding, there is no concept of folders in S3. So, S3 will create something like this on my bucket.
|- a/
|- a1.txt
|- 2.txt
|- b/
|- b1.txt
I did came across this blog but it made things more confusing for me.
My questions:-
Does every Object created in S3 that ends with '/' is a prefix?
In other words, Does every folder that we see in the S3 web console is a prefix?
Although S3 is theoretically a flat store, many of its operations have special handling for prefixes with a set delimiter, usually /. For instance this help page discusses how the "folders" on the S3 console web interface are built by looking at the prefixes you've used.
An important point to remember here is that these folders are not objects themselves, so in your example, there is no key of a or b stored in the bucket.
If you create a bucket and immediately add an object with a key of a/b/c/d/e.txt then:
the bucket will contain exactly one object, with key a/b/c/d/e.txt
some APIs and UIs will infer a prefix for that key of a/b/c/d, as a way of grouping related keys
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 was wondering if there is any difference between the below two paths. The first path has a fixed string in between. Will it have any kind of performance impact? S3 documentation mentions that they allow 3,500 PUT/COPY/POST/DELETE or 5,500 GET/HEAD requests per second per prefix in a bucket. And since both path below have a random prefix therefore we should be fine.
random_uuid/<some_fixed_string>/random_uuid
vs
random_uuid/random_uuid
Any pointers or help will be appreciated
S3 has a flat hierarchy and there are actually no folders. The names:
random_uuid/<some_fixed_string>/random_uuid
random_uuid/random_uuid
are both keys and the folder-subfolder hierarchy is imposed by the client. In S3 the items are simply stored with a key name and the '/' doesn't mean anything. Therefore they should be fully equivalent.
I am moving a largish number of jpgs (several hundred thousand) from a static filesystem to amazon s3.
On the old filesytem, I grouped files into subfolders to keep the total number of files / folder manageable.
For example, a file
4aca29c7c0a76c1cbaad40b2693e6bef.jpg
would be saved to:
/4a/ca/29/4aca29c7c0a76c1cbaad40b2693e6bef.jpg
From what I understand, s3 doesn't respect hierarchial namespaces. So if I were to use 'folders' on s3, the object, including the /'s, would really just be in a flat namesapce.
Still, according to the docs, amazon recommends mimicking a structured filesytem when working with s3.
So I am wondering: Is there anything to be gained using the above folder structure to organize files on s3? Or in this case am I better off just adding the files to s3 without any kind of 'folder' structure.
Performance is not impacted by the use (or non-use) of folders.
Some systems can use folders for easier navigation of the files. For example, Amazon Athena can scan specific sub-directories when querying data rather than having to read every file.
If your bucket is being used for one specific purpose, there is no reason to use folders. However, if it contains different types of data, then you might consider at least a top-level set of folders to keep data separated.
Another potential reason for using folders is for security. A bucket policy can grant access to buckets based upon a prefix (which is a folder name). However, this is likely not relevant for your use-case.
Using "folders" has no performance impact on S3, either way. It doesn't make it faster, and it doesn't make it slower.
The value of delimiting your object keys with / is in organization, both machine-friendly and human-friendly.
If you're trolling through a bucket in the console, troubleshooting, those meaningless noise-filled keys are a hassle to paginate through, only a few dozen at a time.
The console automatically groups objects into imaginary folders based on the / delimiters, so you can find your object to inspect it (check headers, metadata, etc.) is much easier if you can just click on 4a then ca then 29.
The S3 ListObjects APIs support requesting all the objects with a certain key prefix, but they also support finding all the common prefixes before the next delimiter, so you can send API requests to list prefix 4a/ca/ with delimiter / and it will only return the "folders" one level deep, which it refers to as "common prefixes."
This is less meaningful if your object keys are fully opaque and convey nothing more about the objects, as opposed to using key prefixes like images/ and thumbnails/ and videos/.
Having been an admin and working with S3 for a number of years, and having worked with buckets with key naming schemes designed by different teams, I would definitely recommend using some / delimiters for organization purposes. The buckets without them become more of a hassle to navigate over time.
Note that the console does allow you to "create folders," but this is more of the illusion -- there is no need to actually do this, unless you're loading a bucket manually. When you create a folder in the console, it just creates an empty object with a / at the end.
So,
Let's say I have a folder called /example in S3. This folder contains a file called a.txt.
using AWS CLI, how do I upload a local folder, also called example, and replace the current S3 /example atomically. The local folder contains a file called b.txt.
So, I want the behaviour to be that the new S3 /example folder only contains b.txt.
Basically, is there a way to atomically replace an entire folder in S3 with a new one via the AWS CLI?
Thank you!
No, you can't do that.
For starters, S3 is an eventual consistent platform. That means that right after you do a write, you can still get old data back from S3. Practically, this converges quickly (seconds), but there is no upper bound. (They do provide consistency guarantees is some sequence of operations, but generally speaking, it's not strongly consistent)
Secondly, S3 does not have a concept of "folder" or "directory". S3 namespace is flat. The only thing that object /example/a.txt and /example/b.txt have in common is that they start with the same string, just like /foobar.txt and /foobaz.txt begin with the same string. (The User Interface does cheat a bit by treating the / character differently, and giving the illusion of directories)
I've inherited a project at work. Its essentially a niche content repository, and we use S3 to store the content. The project was severely outdated, and I'm in the process of a thorough update.
For some unknown and undocumented reason, the content is stored in an AWS S3 bucket with the pattern web_cl_000000$DB_ID$CONTENT_NAME So, one particular folder can be named web_cl_0000003458zyxwv. This makes no sense, and requires a bit of transformation logic to construct a URL to serve up the content!
I can write a Python script using the boto3 library to do an item-by-item rename, but would like to know if there's a faster way to do so. There are approximately 4M items in that bucket, which will take quite a long time.
That isn't possible, because the folders are an illusion derived from the strings between / delimiters in the object keys.
Amazon S3 has a flat structure with no hierarchy like you would see in a typical file system. However, for the sake of organizational simplicity, the Amazon S3 console supports the folder concept as a means of grouping objects. Amazon S3 does this by using key name prefixes for objects. (emphasis added)
http://docs.aws.amazon.com/AmazonS3/latest/UG/FolderOperations.html
The console contributes to the illusion by allowing you to "create" a folder, but all that actually does is create a 0-byte object with / as its last character, which the console will display as a folder whether there are other objects with that prefix or not, making it easier to upload objects manually with some organization.
But any tool or technique that allows renaming folders in S3 will in fact be making a copy of each object with the modified name, then deleting the old object, because S3 does not actually support rename or move, either -- objects in S3, including their key and metadata, are actually immutable. Any "change" is handled at the API level with a copy/overwrite or copy-then-delete.
Worth noting, S3 should be able to easily sustain 100 such requests per second, so with asynchronous requests or multi-threaded code, or even several processes each handling a shard of the keyspace, you should be able to do the whole thing in a few hours.
Note also that the less sorted (more random) the new keys are in the requests, the harder you can push S3 during a mass-write operation like this. Sending the requests so that the new keys are in lexical order will be the most likely scenario in which you might see 503 Slow Down errors... in which case, you just back off and retry... but if the new keys are not ordered, S3 can more easily accommodate a large number of requests.