I am working on a Java MapReduce app that has to be able to provide an upload service for some pictures from the local machine of the user to an S3 bucket.
The thing is the app must run on an EC2 cluster, so I am not sure how I can refer to the local machine when copying the files. The method copyFromLocalFile(..) needs a path from the local machine which will be the EC2 cluster...
I'm not sure if I stated the problem correctly, can anyone understand what I mean?
Thanks
You might also investigate s3distcp: http://docs.amazonwebservices.com/ElasticMapReduce/latest/DeveloperGuide/UsingEMR_s3distcp.html
Apache DistCp is an open-source tool you can use to copy large amounts of data. DistCp uses MapReduce to copy in a distributed manner—sharing the copy, error handling, recovery, and reporting tasks across several servers. S3DistCp is an extension of DistCp that is optimized to work with Amazon Web Services, particularly Amazon Simple Storage Service (Amazon S3). Using S3DistCp, you can efficiently copy large amounts of data from Amazon S3 into HDFS where it can be processed by your Amazon Elastic MapReduce (Amazon EMR) job flow. You can also use S3DistCp to copy data between Amazon S3 buckets or from HDFS to Amazon S3.
You will need to get the files from the userMachine to at least 1 node before you will be able to use them through a MapReduce.
The FileSystem and FileUtil functions refer to paths either on the HDFS or the local disk of one of the nodes in the cluster.
It cannot reference the user's local system. (Maybe if you did some ssh setup... maybe?)
Related
Since NFS has single point of failure issue. I am thinking to build a storage layer using S3 or Google Cloud Storage as PersistentVolumn in my local k8s cluster.
After a lot of google search, I still cannot find an way. I have tried using s3 fuse to mount volume to local, and then create PV by specifying the hotPath. However, a lot of my pods (for example airflow, jenkins), complained about no write permission, or say "version being changed".
Could someone help figuring out the right way to mount S3 or GCS bucket as a PersistenVolumn from local cluster without using AWS, or GCP.
S3 is not a file system and is not intended to be used in this way.
I do not recommend to use S3 this way, because in my experience any FUSE-drivers very unstable and with I/O operations you will easily ruin you mounted disk and stuck in Transport endpoint is not connected nightmare for you and your infrastructure users. It's also may lead to high CPU usage and RAM leakage.
Useful crosslinks:
How to mount S3 bucket on Kubernetes container/pods?
Amazon S3 with s3fs and fuse, transport endpoint is not connected
How stable is s3fs to mount an Amazon S3 bucket as a local directory
i am working on a project that has a requirement to store scientific data on AWS S3 as raw data for the beginning of a data lake. we are planning JSON for application data and using S3 metadata to persist application metadata (JSON schema) and process metadata. at the moment, on site S3 is the only service that we have available to us from the AWS cloud.
the client would like a publish environment where they can get the raw data back as files. we would like to avoid building a custom catalog and security infrastructure.
i don't see anything about Apache Atlas that will connect directly to AWS S3. but we can put Apache Hive on top of AWS S3 and then put Apache Atlas and Ranger on top of that. but not sure if this is how we can publish the raw data from S3 or if that even works as Hive is more of a processing environment.
is it possible to use Apache Atlas and Ranger on top of AWS S3 directly?
I'd love to expose a Google storage bucket over HDFS to a service.
Service in question is a cluster (SOLR) that can speak only to HDFS, given I have no hadoop (nor need for it), ideally I'd like to have a docker container that would user a Google storage bucket as a backend and expose it's contents via HDFS.
If possible I'd like to avoid mounts (like fuse gcsfs), has anyone done such thing?
I think I could just do mount gcsfs and setup a single node cluster with HDFS, but is there a simpler / more robust way?
Any hints / directions are appreciated.
The Cloud Storage Connector for Hadoop is the tool you might need.
It is not a Docker image but rather an install. Further instructions can be found in the GitHub repository under README.md and INSTALL.md
If it is accessed from AWS S3 you'll need a Service Account with access to Cloud Storage and set the env variable GOOGLE_APPLICATION_CREDENTIALS to /path/to/keyfile.
To use SOLR with GCS, you need indeed a hadoop cluster and you can do that in GCP by creating a dataproc cluster then use the connector mentioned to connect your SOLR solution with GCS. for more info check this SOLR
How can we improve the upload speed of files from EC2 to S3, when the EC2 machine and S3 in different regions?
I have created a file which is of 1GB, and i need to upload the same to S3. Here the EC2 machine and S3 bucket were located in different regions(but Same Country)
Both were in US but the region is East and west
Anyone please assist on this
Unfortunately, there is not much you can do here. You are going to be limited to the available bandwidth between each datacenter.
You do have the option of moving your instance or bucket, to the other region. How much work this will be will depend on how much data you have in your bucket, or how you are currently using your instance.
A similar Question is this
There is a separate service Data pipeline, which provides reliable data transfer between S3 and EC2
We have a site where users upload files, some of them quite large. We've got multiple EC2 instances and would like to load balance them. Currently, we store the files on an EBS volume for fast access. What's the best way to replicate the files so they can be available on more than one instance?
My thought is that some automatic replication process that uploads the files to S3, and then automatically downloads them to other EC2 instances would be ideal.
EBS snapshots won't work because they replicate the entire volume, and we need to be able to replicate the directories of individual customers on demand.
You could write a shell script that would spawn s3cmd to sync your local filesystem with a S3 bucket whenever a new file is uploaded (or deleted). It would look something like:
s3cmd sync ./ s3://your-bucket/
Depends on what OS you are running on your EC2 instances:
There isn't really any need to add S3 to the mix unless you want to store them there for some other reason (like backup).
If you are running *nix the classic choice might be to run rsync and just sync between instances.
On Windows you could still use rsync or else SyncToy from Microsoft is a simple free option. Otherwise there are probably hundreds of commercial applications in this space...
If you do want to sync to S3 then I would suggest one of the S3 client apps like CloudBerry or JungleDisk, which both have sync functionality...
If you are running Windows it's also worth considering DFS (Distributed File System) which provides replication and is part of Windows Server...
The best way is to use the Amazon Cloud Front service. All of the replication is managed as part of the AWS. Content is served from several different availability zones, but does not require you to have EBS volumes in those zones.
Amazon CloudFront delivers your static and streaming content using a global network of edge locations. Requests for your objects are automatically routed to the nearest edge location, so content is delivered with the best possible performance.
http://aws.amazon.com/cloudfront/
Two ways:
Forget EBS, transfer the files to S3 and use S3 as your file-manager than EBS, add cloudfront and use the common-link everywhere.
Mount S3 bucket on any machines.
1. Amazon CloudFront is a web service for content delivery. It delivers your static and streaming content using a global network of edge locations.
http://aws.amazon.com/cloudfront/
2. You can mount S3 bucket on your linux machine. See below:
s3fs -
http://code.google.com/p/s3fs/wiki/InstallationNotes
- this did work for me. It uses FUSE file-system + rsync to sync the files
in S3. It kepes a copy of all
filenames in the local system & make
it look like a FILE/FOLDER.
That way you can share the S3 bucket on different machines.