How to use metaflow to get metadata from s3? - netflix-metaflow

The official tutorials of metaflow show that analysis can be done using jupyter notebook and metadata after running a script. Also I know metaflow automatically writes metadata to s3. Then how can I get metadata from s3 using jupyter notebook? The only way I can think of is to use boto3. I guess there might be better tools available.

By default, Metaflow stores metadata in your local file system. In order to leverage S3, you have to configure Metaflow to actually use AWS resources.
Here's a high-level overview for Metaflow, just so you are familiar with it.
Learn Metaflow in 10 mins - A hands-on tutorial
Here are specific guidelines for connecting it to AWS.
Metaflow on AWS

You should be able to use the python client provided by metaflow to access the data.
example:
from metaflow import Step
print(Step('DebugFlow/2/a').task.data.x)
Where DebugFlow is the flow name, 2 is the run number, a is the step name, and x is the variable name of the artifact/metadata you are trying to load.
This is documented here:
https://docs.metaflow.org/metaflow/client#accessing-data

Related

Prefect: Is is possible to access storage like NAS with multiple machines in Prefect?

I have set up a Prefect backend server on a remote machine. I was able to connect local agents from different other machines to the server by modifying the config.toml in the .prefect folder:
[server]
endpoint = "http://server_ip:port/graphql"
[server.ui]
apollo_url = "http://server_ip:port/graphql"
As it stands, I can create a local agent on each machine, register flows and run them on the respective machines. Now I would like to have a central computer where I can develop and register my flows.
Unfortunately, when I run a flow on Machine B, registered on Machine A, I get a "Module not Found" error message. I have read that the error comes from machines only looking for the flows in their local storage.
Without using Git, GCS, etc., is it possible to use, for example, a NAS where all flows are stored and which all machines can use to access the flows?
if so, how must flows, agents, and storage be configured? Unfortunately, I have not found any good documentation on this.
Many applications use Docker agents and have similar problems, or use remote storage directly.
There is no native NAS storage interface available in the core library, but we provide recipes and guidance on how you may solve the ModuleNorFoundError - check out this Discourse wiki page which dives into how you may solve that
I was able to find a solution to my answer. The prerequisite is shared storage (e.g. a NAS), which is accessible on all machines under the same path. In this storage, the flows are stored in the form of .py files. Flows and used local Agents do not need any special preparations.
I simply registered my flows with
prefect register --project "PREFECT_PROJECT_NAME" --path "PATH_TO_.py"
in CLI.
I was able to deploy all my flows from machine A and execute them from/schedule them on any other machine

How to download file from url and store it in aws s3 bucket?

as stated, I'm trying to download this dataset of zip folders containing images: https://data.broadinstitute.org/bbbc/BBBC006/ and store them in an s3 bucket so I can later unzip them in the bucket, reorganize them, and pull them in smaller chunks into a vm for some computation. Problem is, I don't know how to get the data from https://data.broadinstitute.org/bbbc/BBBC006/BBBC006_v1_images_z_00.zip for example or any of the other ones, to then send it s3
this is my first time using aws or really any cloud platform so please bear with me :]
Amazon EC2 provides a virtual computer just like a normal Linux or Windows computer.
Amazon S3 is a block storage service where you can upload/download files.
If you wish to copy files from a website to Amazon S3, you will need to write an application or script that will:
Download the files from the website
Upload them to Amazon S3
If you wish to do it from a script, you could use the AWS Command-Line Interface (CLI).
Or, you could do it from a programming language, see: SDKs and Programming Toolkits for AWS

Is there a way to upload data from FTP server to Amazon S3? [duplicate]

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Is there a way to connect to an Amazon S3 bucket with FTP or SFTP rather than the built-in Amazon file transfer interface in the AWS console? Seems odd that this isn't a readily available option.
There are three options.
You can use a native Amazon Managed SFTP service (aka AWS Transfer for SFTP), which is easier to set up.
Or you can mount the bucket to a file system on a Linux server and access the files using the SFTP as any other files on the server (which gives you greater control).
Or you can just use a (GUI) client that natively supports S3 protocol (what is free).
Managed SFTP Service
In your Amazon AWS Console, go to AWS Transfer for SFTP and create a new server.
In SFTP server page, add a new SFTP user (or users).
Permissions of users are governed by an associated AWS role in IAM service (for a quick start, you can use AmazonS3FullAccess policy).
The role must have a trust relationship to transfer.amazonaws.com.
For details, see my guide Setting up an SFTP access to Amazon S3.
Mounting Bucket to Linux Server
Just mount the bucket using s3fs file system (or similar) to a Linux server (e.g. Amazon EC2) and use the server's built-in SFTP server to access the bucket.
Install the s3fs
Add your security credentials in a form access-key-id:secret-access-key to /etc/passwd-s3fs
Add a bucket mounting entry to fstab:
<bucket> /mnt/<bucket> fuse.s3fs rw,nosuid,nodev,allow_other 0 0
For details, see my guide Setting up an SFTP access to Amazon S3.
Use S3 Client
Or use any free "FTP/SFTP client", that's also an "S3 client", and you do not have setup anything on server-side. For example, my WinSCP or Cyberduck.
WinSCP has even scripting and .NET/PowerShell interface, if you need to automate the transfers.
Update
S3 now offers a fully-managed SFTP Gateway Service for S3 that integrates with IAM and can be administered using aws-cli.
There are theoretical and practical reasons why this isn't a perfect solution, but it does work...
You can install an FTP/SFTP service (such as proftpd) on a linux server, either in EC2 or in your own data center... then mount a bucket into the filesystem where the ftp server is configured to chroot, using s3fs.
I have a client that serves content out of S3, and the content is provided to them by a 3rd party who only supports ftp pushes... so, with some hesitation (due to the impedance mismatch between S3 and an actual filesystem) but lacking the time to write a proper FTP/S3 gateway server software package (which I still intend to do one of these days), I proposed and deployed this solution for them several months ago and they have not reported any problems with the system.
As a bonus, since proftpd can chroot each user into their own home directory and "pretend" (as far as the user can tell) that files owned by the proftpd user are actually owned by the logged in user, this segregates each ftp user into a "subdirectory" of the bucket, and makes the other users' files inaccessible.
There is a problem with the default configuration, however.
Once you start to get a few tens or hundreds of files, the problem will manifest itself when you pull a directory listing, because ProFTPd will attempt to read the .ftpaccess files over, and over, and over again, and for each file in the directory, .ftpaccess is checked to see if the user should be allowed to view it.
You can disable this behavior in ProFTPd, but I would suggest that the most correct configuration is to configure additional options -o enable_noobj_cache -o stat_cache_expire=30 in s3fs:
-o stat_cache_expire (default is no expire)
specify expire time(seconds) for entries in the stat cache
Without this option, you'll make fewer requests to S3, but you also will not always reliably discover changes made to objects if external processes or other instances of s3fs are also modifying the objects in the bucket. The value "30" in my system was selected somewhat arbitrarily.
-o enable_noobj_cache (default is disable)
enable cache entries for the object which does not exist. s3fs always has to check whether file(or sub directory) exists under object(path) when s3fs does some command, since s3fs has recognized a directory which does not exist and has files or subdirectories under itself. It increases ListBucket request and makes performance bad. You can specify this option for performance, s3fs memorizes in stat cache that the object (file or directory) does not exist.
This option allows s3fs to remember that .ftpaccess wasn't there.
Unrelated to the performance issues that can arise with ProFTPd, which are resolved by the above changes, you also need to enable -o enable_content_md5 in s3fs.
-o enable_content_md5 (default is disable)
verifying uploaded data without multipart by content-md5 header. Enable to send "Content-MD5" header when uploading a object without multipart posting. If this option is enabled, it has some influences on a performance of s3fs when uploading small object. Because s3fs always checks MD5 when uploading large object, this option does not affect on large object.
This is an option which never should have been an option -- it should always be enabled, because not doing this bypasses a critical integrity check for only a negligible performance benefit. When an object is uploaded to S3 with a Content-MD5: header, S3 will validate the checksum and reject the object if it's corrupted in transit. However unlikely that might be, it seems short-sighted to disable this safety check.
Quotes are from the man page of s3fs. Grammatical errors are in the original text.
Answer from 2014 for the people who are down-voting me:
Well, S3 isn't FTP. There are lots and lots of clients that support S3, however.
Pretty much every notable FTP client on OS X has support, including Transmit and Cyberduck.
If you're on Windows, take a look at Cyberduck or CloudBerry.
Updated answer for 2019:
AWS has recently released the AWS Transfer for SFTP service, which may do what you're looking for.
Or spin Linux instance for SFTP Gateway in your AWS infrastructure that saves uploaded files to your Amazon S3 bucket.
Supported by Thorntech
Amazon has released SFTP services for S3, but they only do SFTP (not FTP or FTPES) and they can be cost prohibitive depending on your circumstances.
I'm the Founder of DocEvent.io, and we provide FTP/S Gateways for your S3 bucket without having to spin up servers or worry about infrastructure.
There are also other companies that provide a standalone FTP server that you pay by the month that can connect to an S3 bucket through the software configuration, for example brickftp.com.
Lastly there are also some AWS Marketplace apps that can help, here is a search link. Many of these spin up instances in your own infrastructure - this means you'll have to manage and upgrade the instances yourself which can be difficult to maintain and configure over time.
WinSCp now supports S3 protocol
First, make sure your AWS user with S3 access permissions has an “Access key ID” created. You also have to know the “Secret access key”. Access keys are created and managed on Users page of IAM Management Console.
Make sure New site node is selected.
On the New site node, select Amazon S3 protocol.
Enter your AWS user Access key ID and Secret access key
Save your site settings using the Save button.
Login using the Login button.
Filezilla just released a Pro version of their FTP client. It connects to S3 buckets in a streamlined FTP like experience. I use it myself (no affiliation whatsoever) and it works great.
As other posters have pointed out, there are some limitations with the AWS Transfer for SFTP service. You need to closely align requirements. For example, there are no quotas, whitelists/blacklists, file type limits, and non key based access requires external services. There is also a certain overhead relating to user management and IAM, which can get to be a pain at scale.
We have been running an SFTP S3 Proxy Gateway for about 5 years now for our customers. The core solution is wrapped in a collection of Docker services and deployed in whatever context is needed, even on-premise or local development servers. The use case for us is a little different as our solution is focused data processing and pipelines vs a file share. In a Salesforce example, a customer will use SFTP as the transport method sending email, purchase...data to an SFTP/S3 enpoint. This is mapped an object key on S3. Upon arrival, the data is picked up, processed, routed and loaded to a warehouse. We also have fairly significant auditing requirements for each transfer, something the Cloudwatch logs for AWS do not directly provide.
As other have mentioned, rolling your own is an option too. Using AWS Lightsail you can setup a cluster, say 4, of $10 2GB instances using either Route 53 or an ELB.
In general, it is great to see AWS offer this service and I expect it to mature over time. However, depending on your use case, alternative solutions may be a better fit.

Use Cygnus to store historical data from Orion ContextBroker in a local Hadoop database

We are currently working in a project where we use Orion ContextBroker to store information from different sensors and Wirecloud to show them in a web page.
We want to store historical data from these sensors in order to show them in a graph. I have looked around the Fiware documentation and they recommend to store the data in a Cosmos instance of Fi-lab, through Cygnus.
The thing is that we would like to store that historical data in a local Hadoop based server we have in our company, not in Cosmos, because we are running this project in a local net where we don't have internet access, and also to have that information stored in our local server.
Is it possible to configure Cygnus to redirect the output data to my file system? If so, which files must be configured in order to achieve this?
Thank you
The answer is yes. Cygnus is meant to persist context data in whatever HDFS-based filesystem (as the one used by Cosmos), thus nothing special has to be done when configuring Cygnus.
If you download the lastest version (0.7.0 at the moment of writting this), you will need to configure:
A cygnus_instance_default.conf file from cygnus_instance.conf.template. This is the instance configuration. From 0.7.1 is possible to have multiple instance configurations that are run in a parallel way, and they all have to called cygnus_instance_<whatever>.conf.
A agent.conf file from agent.conf.template. This is the Flume specific configuration that you will find in the README.md.

Mounting Page Blob as a VHD in a batch file

This is a follow-up to my stackoverflow post: how do I mount a page blob as a VHD on worker role instance? After the drive is mounted, I will pass that as the value of --dbpath parameter to mongo instance.
In a nutshell, I'm trying to start a single mongo instance with the data directory on azure blob (for durability). I'm building on the HelloWorld example on Azure's site-- instead of starting Tomcat instance, I will start mongo instance.
I suggest you follow this guide: http://www.codeproject.com/Articles/81413/Windows-Azure-Drives-Part-1-Configure-and-Mounting. This guide explains how to mount the drive but it also shows how you can save the drive letter as an environment variable.
This is interesting for when you're starting the mongo instance, you can just use this environment variable together with --dbpath. Maybe it would be best to encapsulate all the code in a console application so that you can simply start it before starting the mongo instance.
I’m not sure if you can mount a drive in Java. Currently this feature is not available in Windows Azure Storage Client for Java: https://github.com/WindowsAzure/azure-sdk-for-java. There’s no native (C++) API either. So you may need to use .NET to mount the drive, and then start your Java process from your .NET application. For now, you can also submit a feature request on http://www.mygreatwindowsazureidea.com/forums/34192-windows-azure-feature-voting.
Best Regards,
Ming Xu.