Featured Post

How to Work With Tuple in Python

Image
Tuple in python is one of the streaming datasets. The other streaming datasets are List and Dictionary. Operations that you can perform on it are shown here for your reference. Writing tuple is easy. It has values of comma separated, and enclosed with parenthesis '()'. The values in the tuple are immutable, which means you cannot replace with new values. #1. How to create a tuple Code: my_tuple=(1,2,3,4,5) print(my_tuple) Output: (1, 2, 3, 4, 5) ** Process exited - Return Code: 0 ** Press Enter to exit terminal #2. How to read tuple values Code: print(my_tuple[0]) Output: 1 ** Process exited - Return Code: 0 ** Press Enter to exit terminal #3. How to add two tuples Code: a=(1,6,7,8) c=(3,4,5,6,7,8) d=print(a+c) Output: (1, 6, 7, 8, 3, 4, 5, 6, 7, 8) ** Process exited - Return Code: 0 ** Press Enter to exit terminal #4.  How to count tuple values Here the count is not counting values; count the repetition of a given value. Code: sample=(1, 6, 7, 8, 3, 4, 5, 6, 7, 8) print(sample

The best solution Ceph Data Storage for big data

#The best solution Ceph Data Storage for big data:
#The best solution Ceph Data Storage for big data:
The power of Ceph can transform your organization’s IT infrastructure and your ability to manage vast amounts of data. If your organization runs applications with different storage interface needs, Ceph is for you! Ceph’s foundation is the Reliable Autonomic Distributed Object Store (RADOS), which provides your applications with object, block, and file system storage in a single unified storage cluster—making Ceph flexible, highly reliable and easy for you to manage.

Ceph’s RADOS provides you with extraordinary data storage scalability—thousands of client hosts or KVMs accessing petabytes to exabytes of data. Each one of your applications can use the object, block or file system interfaces to the same RADOS cluster simultaneously, which means your Ceph storage system serves as a flexible foundation for all of your data storage needs. You can use Ceph for free, and deploy it on economical commodity hardware. Ceph is a better way to store data.

OBJECT-BASED STORAGE
Organizations prefer object-based storage when deploying large scale storage systems, because it stores data more efficiently. Object-based storage systems separate the object namespace from the underlying storage hardware—this simplifies data migration.

WHY IT MATTERS
By decoupling the namespace from the underlying hardware, object-based storage systems enable you to build much larger storage clusters. You can scale out object-based storage systems using economical commodity hardware, and you can replace hardware easily when it malfunctions or fails.

THE CEPH DIFFERENCE
Ceph’s CRUSH algorithm liberates storage clusters from the scalability and performance limitations imposed by centralized data table mapping. It replicates and re-balance data within the cluster dynamically—elminating this tedious task for administrators, while delivering high-performance and infinite scalability.

Comments

Popular posts from this blog

7 AWS Interview Questions asked in Infosys, TCS

How to Decode TLV Quickly

Hyperledger Fabric: 20 Real Interview Questions