Hadoop Distributed File System – a Solution to Big Data?
Posted by Casey Schmidt
The Hadoop Distributed File System (HDFS) is part of a comprehensive business solution to storing big data for analysis. It is a function of Hadoop and it stores the data for companies wishing to maintain large amounts of data. If you’re looking for an answer to the big data storage dilemma, HDFS is right for you. Here’s a guide to help you understand it better.
What Is Hadoop Distributed File System?
The Hadoop Distributed File System (HDFS) is the way Hadoop programs store data. It is instrumental in solving big data issues for companies. HDFS transforms singular data into large quantities of connecting pathways. It essentially enables companies to expand storage drastically.
HDFS is a core part of Hadoop – which contains different main modules. One of them converts the data format. The second action (HDFS) stores the data and is the most important function within Hadoop. These steps are crucial to solving big data problems for enterprises. Before we explain HDFS further, it’s important to understand what Hadoop is and why HDFS became part of its process.
What Is Hadoop?
Hadoop is a collection of open source software that companies use to handle their big data processes. These programs are available to essentially everyone. Furthermore, all who use them are capable of adjusting their function. Ultimately, Hadoop maintains data storage.
Hadoop is a way for companies to analyze big data. It is dynamic and modifiable when necessary. Data systems change, making it valuable in that it can be altered to fit the new changes. It allows companies to use large networks of systems to manage large quantities of data.
Hadoop as a Solution?
Hadoop first and foremost is a way for large data sets to be stored for analysis. It is intended to be the next viable option instead of a single-storage solution such as a hard drive. This helped it transform the way data was stored, because it’s more efficient to distribute the data onto numerous physical storage locations rather than just one giant receptacle. The reason for this is because the more places the data is stored, the quicker it can be retrieved.
Think of it like driving down a one-lane freeway. Eventually cars pile up. The Hadoop creates multiple lane freeways that let data cruise the freeway quickly. With Hadoop, companies are saving money by essentially pooling their storage resources where the Hadoop can function. This is where HDFS comes in.
Where Does HDFS Fit Into This Equation?
The Hadoop stores data using the distributed file system. The company computers and other hardware are connected using HDFS, allowing the data files to be stored across an array of systems rather than in a single location.
There are many benefits to this, one such benefit is it acts as a backup of sorts. Imagine if you had twenty one dollar bills in your pocket versus one twenty dollar bill in your pocket. If you dropped the twenty, you would be out twenty dollars. If you dropped a one, you would still have nineteen dollars. The system works similarly in that technical and hardware failures aren’t a data death sentence.
The HDFS is a large part of the solution for companies attempting to manage big data efficiently. As the nature of Hadoop evolves, keep in mind its core functions to understand the changes.