Found 21 Articles for Hadoop

Introduction Big Data has become a buzzword in the technology industry over the past decade. With vast amounts of data being generated every second, it's essential to manage and process it efficiently. That’s where Hadoop and Spark come into play. Both are powerful big data processing frameworks that can handle large datasets at scale. Hadoop Overview History and Development Hadoop was created by Doug Cutting and Mike Cafarella in 2005 while they were working at Yahoo. The project was named after a toy elephant that belonged to Cutting's son. Initially designed to handle large amounts of unstructured data, Hadoop has ... Read More

You must meet specific requirements and put security hardening into place before you can set up Hadoop. Install the essential software prerequisites first, such as Java Development Kit (JDK) and Secure Shell (SSH). Before establishing the network settings, verify that the DNS resolution and firewall rules are accurate. Then, make sure that access is safe by creating user accounts for Hadoop services and assigning the proper permissions. Harden Hadoop's security by activating Kerberos-based authentication and authorisation systems and setting up SSL/TLS for secure communication. To further safeguard sensitive data housed in Hadoop clusters, update security patches on a regular basis ... Read More

Hive is an open-source data warehousing framework built on top of Apache Hadoop. It allows users to query large datasets stored in Hadoop using a SQL-like language called HiveQL. Hive provides an interface for data analysts and developers to work with Hadoop without having to write complex MapReduce jobs. In this article, we will discuss how to install and configure Hive with high availability. High availability (HA) is a critical requirement for any production system. HA ensures that system is always available, even in event of hardware or software failures. In context of Hive, HA means that Hive server is ... Read More

Apache Hadoop is an open-source framework that allows for distributed processing of large data sets. It can be installed and configured on a single node, which can be useful for development and testing purposes. In this article, we will discuss how to install and configure Apache Hadoop on a single node running CentOS 8. Step 1: Install Java Apache Hadoop requires Java to be installed on system. To install Java, run following command − sudo dnf install java-11-openjdk-devel Step 2: Install Apache Hadoop Apache Hadoop can be downloaded from official Apache website. latest stable version at time of writing ... Read More

Introduction In today’s world humans are generating data in huge quantities from platforms like social media, health care, etc., and with this data, we have to extract information to increase business and develop our society. For handling this data and extraction of information from data we use two important technologies named Hadoop and Mahout. Hadoop and Mahout are two important technologies in the field of big data analytics, but they have different functionalities and use cases. Hadoop is primarily used for batch processing, while Mahout is used for building machine-learning models. Ultimately, the choice depends on the user's needs. In ... Read More

In era of digitalization, data has become most valuable asset for businesses. Organizations today generate an enormous amount of data on a daily basis. This data can be anything, from customer interactions to financial transactions, product information, and more. Managing and storing this massive amount of data requires a robust and efficient infrastructure, which is where big data servers come in. Big data servers are a type of server infrastructure designed to store, process and manage large volumes of data. In this article, we will delve deeper into what big data servers are, how they work, and some popular examples. ... Read More

Hadoop is an open-source framework that is used for distributed storage and processing of large datasets. It provides a reliable, scalable, and efficient way to manage Big Data. CentOS/RHEL 8 is a popular Linux distribution that can be used to deploy a Hadoop server. However, deploying Hadoop on CentOS/RHEL 8 can be a complex process, and there are several best practices that should be followed to ensure a successful deployment. In this article, we will discuss best practices for deploying a Hadoop server on CentOS/RHEL 8. We will cover following sub-headings − Pre-requisites for Deploying Hadoop on CentOS/RHEL 8 ... Read More

Globally, Development in Cloud Computing always goes towards almost all IT investments. On the other hand, many businesses have started storing and analyzing the ever-increasing amounts of data in Hadoop. What is Cloud Computing? Cloud Computing always simplify for referring to the internet. Rather than keeping them on the local hard disc, Cloud Computing is the best for moving your applications, computer data, and files to an external server in the cloud. Main Advantages of cloud Computing are Elasticity − Cloud computing provides elasticity by allowing organizations to consume only the necessary resources. To accommodate rising or falling computer ... Read More

There are currently numerous Big Data technologies on the marketplace that are having a major impact on the emerging technological stacks for handling Big Data. Apache Hadoop is one such platform that has been the center of Big Data discussions. Hadoop is the biggest technology in the Big Data business. Teradata is a system for managing relational databases and a leading data warehousing solution that offers analytics solutions for managing data. It is used to store and process vast quantities of structured data securely. Technology has revolutionized how data is generated, processed, and used. With a large amount of computer-generated ... Read More

Big Data and Hadoop are the two most frequently used phrases today. Both are interconnected in such a way that Big Data cannot be handled without the assistance of Hadoop. Big Data is a term used to describe a collection of large and complex data sets that are difficult to store and process using conventional database management technologies or traditional data processing applications. Collecting, selecting, storing, searching, exchanging, transferring, evaluating, and visualizing the data is part of the challenge. We are surrounded by a huge amount of information in today's digital environment. The fast expansion of the Internet and the ... Read More