Showing posts with label Hadoop file system. Show all posts
Showing posts with label Hadoop file system. Show all posts

Thursday, May 17, 2012

HBase Security for the Enterprise

Trend Micro developed the new security features in HBase 0.92 and has the first known deployment of secure HBase in production. We will share our motivations, use cases, experiences, and provide a 10 minute tutorial on how to set up a test secure HBase cluster and a walk through of a simple usage example. The tutorial will be carried out live on an on-demand EC2 cluster, with a video backup in case of network or EC2 unavailability.

Source : here

Friday, November 11, 2011

The Hadoop Distributed File System


Distributed File System Basics

A distributed file system is designed to hold a large amount of data and provide access to this data to many clients distributed across a network. There are a number of distributed file systems that solve this problem in different ways.
NFS, the Network File System, is the most ubiquitous distributed file system. It is one of the oldest still in use. While its design is straightforward, it is also very constrained. NFS provides remote access to a single logical volume stored on a single machine. An NFS server makes a portion of its local file system visible to external clients. The clients can then mount this remote file system directly into their own Linux file system, and interact with it as though it were part of the local drive.
One of the primary advantages of this model is its transparency. Clients do not need to be particularly aware that they are working on files stored remotely. The existing standard library methods like open(),close(), fread(), etc. will work on files hosted over NFS.
But as a distributed file system, it is limited in its power. The files in an NFS volume all reside on a single machine. This means that it will only store as much information as can be stored in one machine, and does not provide any reliability guarantees if that machine goes down (e.g., by replicating the files to other servers). Finally, as all the data is stored on a single machine, all the clients must go to this machine to retrieve their data. This can overload the server if a large number of clients must be handled. Clients must also always copy the data to their local machines before they can operate on it.

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