More efficient use of aws s3 sync? - amazon-web-services

Lately, we've noticed that our AWS bill has been higher than usual. It's due to adding an aws s3 sync task to our regular build process. The build process generates something around 3,000 files. After the build, we run aws s3 sync to upload them en masse into a bucket. The problem is that this is monetarily expensive. Each upload is costing us a ~$2 (we think) and this adds up to a monthly bill that raises the eyebrow.
All but maybe 1 or 2 of those files actually change from build to build. The rest are always the same. Yet aws s3 sync sees that they all changed and uploads the whole lot.
The documentation says that aws s3 sync compares the file's last modified date and byte size to determine if it should upload. The build server creates all those files brand-new every time, so the last modified date is always changed.
What I'd like to do is get it to compute a checksum or a hash on each file and then use that hash to compare the files. Amazon s3 already has the etag field which is can be an MD5 hash of the file. But the aws s3 sync command doesn't use etag.
Is there a way to use etag? Is there some other way to do this?
The end result is that I'd only like to upload the 1 or 2 files that are actually different (and save tremendous cost)

The aws s3 sync command has a --size-only parameter.
From aws s3 sync options:
--size-only (boolean) Makes the size of each key the only criteria used to decide whether to sync from source to destination.
This will likely avoid copying all files if they are updated with the same content.

As an alternative to s3 sync or cp you could use s5cmd
https://github.com/peak/s5cmd
This is able to sync files on the size and date if different, and also has speeds of up to 4.6gb/s
Example of the sync command:
AWS_REGION=eu-west-1 /usr/local/bin/s5cmd -stats cp -u -s --parents s3://bucket/folder/* /home/ubuntu

S3 charges $0.005 per 1,000 PUT requests (doc), so it's extremely unlikely that uploading 3,000 files is costing you $2 per build. Maybe $2 per day if you're running 50-100 builds a day, but that's still not much.
If you really are paying that much per build, you should enable CloudTrail events and see what is actually writing that much (for that matter, maybe you've created some sort of recursive CloudTrail event log).
The end result is that I'd only like to upload the 1 or 2 files that are actually different
Are these files the artifacts produced by your build? If yes, why not just add a build step that copies them explicitly?

The issue that I got was using wildcard * in the --include option. Using one wildcard was fine but when I added the second * such as /log., it looked like sync tried to download everything to compare, which took a lot of CPU and network bandwidth.

Related

AWS: Speed up copy of large number of very small files

I have a single bucket with a large number of very small text files (betwen 500 bytes to 1.2k). This bucket currently contains over 1.7 Million files and will be ever increasing.
The way that I add data to this bucket is by generating batches of files (in the order 50.000 files) and transfering those files into the bucket.
Now the problem is this. If I transfer the files one by one in a loop it takes an unbareably long amount of time. So if all the files a in a directory origin_directory I would do
aws s3 cp origin_directory/filename_i s3://my_bucket/filename_i
I would do this command 50000 times.
Right now I'm testing this on a set of about 280K files. Doing this would take approximately 68 hours according to my calculations. However I found out that I can sync:
aws s3 sync origin_directory s3://my_bucket/
Now this, works much much faster. (Will take about 5 hours, according to my calculations). However, the sync needs to figure out what to copy (files present in the directory and not present in the bucket). Since the files in the bucket will be ever increasing, I'm thinking that this will take longer and longer as times moves on.
However, since I delete the information after every sync, I know that the sync operation needs to transfer all files in that directory.
So my question is, is there a way to start a "batch copy" similar to the sync, without actually doing the sync?
You can use:
aws s3 cp --recursive origin_directory/ s3://my_bucket/
This is the same as a sync, but it will not check whether the files already exist.
Also, see Use of Exclude and Include Filters to learn how to specify wildcards (eg all *.txt files).
When copying a large number of files using aws s3 sync or aws s3 cp --recursive, the AWS CLI will parallelize the copying, making it much faster. You can also play with the AWS CLI S3 Configuration to potentially optimize it for your typical types of files (eg copy more files simultaneously).
try using https://github.com/mondain/jets3t
it does this same function but works in parallel, so it will complete the job much faster.

How to diff very large buckets in Amazon S3?

I have a use case where I have to back up a 200+TB, 18M object S3 bucket to another account that changes often (used in batch processing of critical data). I need to add a verification step, but due to the large size of both bucket, object count, and frequency of change this is tricky.
My current thoughts are to pull the eTags from the original bucket and archive bucket, and the write a streaming diff tool to compare the values. Has anyone here had to approach this problem and if so did you come up with a better answer?
Firstly, if you wish to keep two buckets in sync (once you've done the initial sync), you can use Cross-Region Replication (CRR).
To do the initial sync, you could try using the AWS Command-Line Interface (CLI), which has a aws s3 sync command. However, it might have some difficulties with a large number of files -- I suggest you give it a try. It uses keys, dates and filesize to determine which files to sync.
If you do wish to create your own sync app, then eTag is definitely a definitive way to compare files.
To make things simple, activate Amazon S3 Inventory, which can provide a daily listing of all files in a bucket, including eTag. You could then do a comparison between the Inventory files to discover which remaining files require synchronization.
For anyone looking for a way to solve this problem in an automated way (as was I),
I created a small python script that leverages S3 Inventories and Athena to do the comparison somewhat efficiently. (This is basically automation of John Rosenstein's suggestion)
You can find it here https://github.com/forter/s3-compare

"Realtime" syncing of large numbers of log files to S3

I have a large number of logfiles from a service that I need to regularly run analysis on via EMR/Hive. There are thousands of new files per day, and they can technically come out of order relative to the file name (e.g. a batch of files comes a week after the date in the file name).
I did an initial load of the files via Snowball, then set up a script that syncs the entire directory tree once per day using the 'aws s3 sync' cli command. This is good enough for now, but I will need a more realtime solution in the near future. The issue with this approach is that it takes a very long time, on the order of 30 minutes per day. And using a ton of bandwidth all at once! I assume this is because it needs to scan the entire directory tree to determine what files are new, then sends them all at once.
A realtime solution would be beneficial in 2 ways. One, I can get the analysis I need without waiting up to a day. Two, the network use would be lower and more spread out, instead of spiking once a day.
It's clear that 'aws s3 sync' isn't the right tool here. Has anyone dealt with a similar situation?
One potential solution could be:
Set up a service on the log-file side that continuously syncs (or aws s3 cp) new files based on the modified date. But wouldn't that need to scan the whole directory tree on the log server as well?
For reference, the log-file directory structure is like:
/var/log/files/done/{year}/{month}/{day}/{source}-{hour}.txt
There is also a /var/log/files/processing/ directory for files being written to.
Any advice would be appreciated. Thanks!
You could have a Lambda function triggered automatically as a new object is saved on your S3 bucket. Check Using AWS Lambda with Amazon S3 for details. The event passed to the Lambda function will contain the file name, allowing you to target only the new files in the syncing process.
If you'd like wait until you have, say 1,000 files, in order to sync in batch, you could use AWS SQS and the following workflow (using 2 Lambda functions, 1 CloudWatch rule and 1 SQS queue):
S3 invokes Lambda whenever there's a new file to sync
Lambda stores the filename in SQS
CloudWatch triggers another Lambda function every X minutes/hours to check how many files are there in SQS for syncing. Once there's 1,000 or more, it retrieves those filenames and run the syncing process.
Keep in mind that Lambda has a hard timeout of 5 minutes. If you sync job takes too long, you'll need to break it in smaller chunks.
You could set the bucket up to log HTTP requests to a separate bucket, then parse the log to look for newly created files and their paths. One troublespot, as well as PUT requests, you have to look for the multipart upload ops which are a sequence of POSTs. Best to log for a few days to see what gets created before putting any effort in to this approach

AWS S3 Sync very slow when copying to large directories

When syncing data to an empty directory in S3 using AWS-CLI, it's almost instant. However, when syncing to a large directory (several million folders), it takes a very long time before even starting to upload / sync the files.
Is there an alternative method? It looks like it's trying to take account of all files in an S3 directory before syncing - I don't need that, and uploading the data without checking beforehand would be fine.
The sync command will need to enumerate all of the files in the bucket to determine whether a local file already exists in the bucket and if it is the same as the local file. The more documents you have in the bucket, the longer it's going to take.
If you don't need this sync behavior just use a recursive copy command like:
aws s3 cp --recursive . s3://mybucket/
and this should copy all of the local files in the current directory to the bucket in S3.
If you use the unofficial s3cmd from S3 Tools, you can use the --no-check-md5 option while using sync to disable the MD5 sums comparison to significantly speed up the process.
--no-check-md5 Do not check MD5 sums when comparing files for [sync].
Only size will be compared. May significantly speed up
transfer but may also miss some changed files.
Source: https://s3tools.org/usage
Example: s3cmd --no-check-md5 sync /directory/to/sync s3://mys3bucket/

aws s3 mv/sync command

I have about 2 million files nested in subfoldrs in a bucket and want to move all of them to another bucket. Spending much of time on searching ... i found a solution to use AWS CLI mv/sync command. use move command or use sync command and then delete all the files after successfully synced.
aws s3 mv s3://mybucket/ s3://mybucket2/ --recursive
or it can be as
aws s3 sync s3://mybucket/ s3://mybucket2/
But the problem is how would i know that how many files/folders have moved or synced and how much time would it take...
And what if some exception occurs(machine/server stops/ internet disconnection due to any reason )...i have to again execute the command or it will for surely complete and move/sync all files. How can i be sure about the number of files moved/synced and files not moved/synced.
or can i have something like that
I move limited number of files e.g 100 thousand.. and repeat until all files are moved...
or move files on the basis of uploaded time.. e.g files uploaded from starting date to ending date
if yes .. how?
To sync them use:
aws s3 sync s3://mybucket/ s3://mybucket2/
You can repeat the command, after it finish (or fail) without issue. This will check if anything is missing/different to the target s3 bucket and will process it again.
The time depends on what size are the files, how much objects you have. Amazon counts directories as an object, so they matter too.