Hadoop Explained: Introduction, Architecture, & It’s Uses

Hadoop Development

Today, We are going to reveal everything about Hadoop, Architecture, components, and ecosystem. So, it’s time for us to dive deeper into Hadoop’s introduction and discover its beauty.

What is Hadoop?

Over the years and the increase in data generation, larger volumes, and more formats emerged. Therefore, multiple processors require to process the data and save time. However, as per Hadoop application developers, a single storage unit became the bottleneck due to the network overhead. However, it led to using a distributed storage unit for each processor, which facilitated access to data.

The method is known as parallel processing with distributed storage: multiple computers run several storage devices. This article gives you a complete overview of Hadoop’s, architecture and it’s components.

What is Hadoop Architecture?

Hadoop has a master-slave topology. In this topology, we have a master node and several slave nodes. The role of the master node is to assign a task to multiple slave nodes and manage resources. According to mobile app developers, slave nodes do the actual computing. The slave nodes store the real data, while in the masters, we have metadata. It means that it stores data about data.

Hadoop Architecture

Quick Glimpse on Hadoop Architecture


NameNode renders all files and directories that are used in the namespace.


DataNode helps you manage the state of an HDFS node and allows you to interact with the blocks.


The master node allows you to perform parallel data processing using Hadoop MapReduce.

Slave Node:

Slave nodes are the additional machines in the Hadoop cluster that allow you to store data for complex calculations. Also, the entire slave node comes with a Task Tracker and a DataNode. It permits you to synchronize the processes with NameNode and Job Tracker, respectively.

In Hadoop, the master or slave system can be configured in the cloud or on-premises

What is Hadoop Hive?

Facebook developed Hive, it is a data warehouse that builds on top of Hadoop. However, it  provides a simple language known as Hive-SQL, similar to SQL for queries, data summarization, and analysis. Hive streamlines queries through indexing.

As a leading application development company called AppStudio, Hive simplifies Hadoop by running more than 7,500 Hive jobs daily for reporting and machine learning.

The Sqoop component will use to import data from external sources into related Hadoop components such as Hive. Additionally, one can use it to export data from Hadoop to other external structured data stores.

What is Hadoop Yarn?

Hadoop YARN (Yet Another Resource Negotiator) is the cluster’s resource management layer and is responsible for resource allocation and job scheduling. Introduced in Hadoop 2.0, YARN is the middle layer between HDFS and MapReduce in the Hadoop architecture.

YARN elements include:

  • Resource manager
  • ApplicationMaster
  • NodeManagers

What is Hadoop Cluster?

A Hadoop cluster is a collection of computers. Also, it is known as nodes. However, when all the networks perform together so, these kinds of parallel calculations convert on big data sets. Hadoop clusters are specifically designed to store huge amounts of structured and unstructured data in computing environments.

Also, what distinguishes Hadoop ecosystems from other groups of computers is their unique structure and architecture. Hadoop clusters consist of a network of connected master and slave nodes using low-cost, highly available hardware. The ability to scale linearly and quickly add or subtract nodes based on volume demands makes them suitable for big data analytics jobs with highly variable data sets.

What is Hadoop Used For?

Financial Negotiation and Forecasting

Hadoop is used in the commercial field. It has a complex algorithm that scans markets with predefined conditions and criteria to find trading opportunities. It can work without human interaction so if no one is around to monitor things as required by end-users. Hadoop is use in high-frequency commerce. Many business decisions will make solely via algorithms.

Improving Healthcare And Public Health

Hadoop is used in the medical field and also to improve public health. Many health-related applications are based on Hadoop. However, they monitor day-to-day activities for this; they had a lot of public data based on this. Moreover, as per healthcare app developers, it deduces facts that can be used in medicine to improve the country’s health.

Enhancing Science And Research

The uses of Hadoop also play a significant role in the field of science and research. Many decisions have been made from the extraction of a large amount of relevant data to conclude. Also, Hadoop helps to find the result with less effort compared to the last time.

Concluding Thoughts

As we know, Hadoop helps banks save customers’ money and, ultimately, their wealth and reputation. But the advantages of Hadoop offer much more than this, and many companies can benefit from this. Overall, after understanding what Hadoop is, please take the next step, and let’s discuss your project with us. Thus, our experts will guide you in the best way.


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