What Is Hadoop? A Guide To The Java-Based Big Data Program

Hadoop is part of the Apache project that is sponsored by the Apache Software Foundation. Essentially, Hadoop is an open-sourced software framework that supports the processing and storage of large data sets, unlike php tools which are primarily for development. This java-based program has many complex operations that are difficult to grasp. In order to better understand this big data tool, it is important that you know the many terms associated with its operations. If you are an IT professional interested in learning more about the inner workings of Hadoop, you have come to the right place. We are here to help you answer the question, what is Hadoop?

Hadoop Modules

Hadoop is comprised of four modules. Each of these modules is responsible for a particular task that is essential for computer system performance for devices tasked with big data analysis. These four modules include the Distributed File System, MapReduce, Hadoop Common and YARN. If you are familiar with these four Hadoop modules, you are that much closer to understanding what exactly Hadoop does.

What Are Computer Clusters?

A computer cluster is a set of connected computers that work together so that they can be viewed as a single system. Unlike grid computers and flash drives, computer clusters are controlled and scheduled to perform the same task through a particular software program. They are linked through a Local Area Network to act as a more powerful machine than one single computer. This helps Hadoop to process big data more efficiently.

What Are Network Nodes?

Network nodes are connection points that can receive, create, store or send data along distributed network routes, much like transmissions within semiconductors. In computer networks nodes can be a physical piece of data communication equipment, such as a modem, or they can be virtual. Hadoop makes it possible to run applications and handle thousands of terabytes of data by using thousands of commodity hardware nodes.

How Are Hadoop Files Stored?

If you want to know Hadoop, you obviously have to know how Hadoop files are stored, at least in a general sense. To this end, Hadoop allows for the storage of incredibly large files. It also makes it possible to store many of these large files. Hadoop is capable of this because it does not utilize just one single node or server for storage. This is important to know, because it is not a task that only large corporations, like HP Enterprise, have to worry about.

What Is A Framework?

In computer systems, a framework is often a layered structure that indicates what kind of programs can or should be built and how they would interrelate. Some computer system frameworks may also include actual programs. Hadoop’s framework operates on three core components: MapReduce, HDFS and YARN. Each of these components contribute to Hadoop’s ability to process, store and organize large sets of data, like the iPad sales data.

What Is A Distributed File System?

HDFS stands for Hadoop Distributed File System. A distributed file system is a file system with data stored on a server. This allows clients to access and process data stored on the server as if it were on their own computer, like iFax. DFS makes it convenient for users to share information and files among user on a particular network, similarly to how Hadoop operates.

What Is MapReduce?

MapReduce is not something that will be helpful navigating Abbey Roads, it is actually a programming model and associated implementation process for processing and generating large sets of data. For Hadoop, MapReduce serves two important functions: it distributes work to various nodes within a cluster or map, and it organizes and reduces the results from each node to fit and answer a particular query from the user.

What Are Data Transfer Rates?

Data transfer rates are the speed at which data can be transmitted from one device or Vax computer to another. This speed is often measured in megabits or megabytes per second. Hadoop’s job is to reduce data transfer rates as much as possible, making large amount of data more accessible to the user. This is done using computer clusters, nodes and much more.

Hadoop is a program, unlike vbrick systems, designed to make managing big data easier. The java-based framework is incredibly powerful, but it can also be incredibly difficult to understand. To familiarize yourself with Hadoop, it is important to make note of each of the definitions above. That way, you can understand exactly how the program operates.

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