Hadoop is an Apache open-source project that provides software for reliable and scalable distributed computing. The core consists of a distributed file system (HDFS) and a resource manager (YARN). Various other open-source projects, such as Apache Hive use Apache Hadoop as persistence layer.
Do I need Big Data? And if so, how much? Many companies follow the hype of big data without understanding the implications of the technology. Read the full article and you will understand.
In this tutorial, we'll learn Big Data Ingestion Options. Try and experience it right in this article.
Apache Sqoop — One smart tool for Big Data World. It's nothing special. Why is it used by so many professionals? Read this article to the end and you will understand. Let's explore it with us now.
Looking for a career in Big Data? Need help for your next interview? Here’s a compilation of the 15 commonly asked Hadoop interview questions. If only I knew these things before.
In this tutorial, we'll learn 4 Common Reasons for FetchFailed Exception in Apache Spark. Let's explore it with us now.
What's the difference between Hadoop and Spark? Hadoop and Spark, both developed by the Apache Software Foundation. The respective architectures of Hadoop and Spark, how these big data frameworks compare in multiple contexts and scenarios that fit best with each solution.
Know about potential stragglers in your Spark application and how they affect the overall application performance. In this tutorial, we'll learn Identify and Resolve Stragglers in Your Spark Application.
In this tutorial, we'll learn Big Data Analysis is now commonly used by many companies to predict market trends, personalise customers experiences, speed up companies workflow.
In this tutorial, we'll learn update 12 of the Big Data Tools plugin for IntelliJ IDEA Ultimate, PyCharm Professional, and DataGrip has been released. You can install it from the JetBrains Plugin Repository or from inside your IDE. Let's explore it with us now.
This Edureka video on "Apache Hadoop & Spark Tutorial For Beginners" will help you understand the basics of Hadoop and Spark with examples.
In this tutorial we will explore some big data tools such as Hadoop, hive, etc .We will learn how to setup a workspace and also how to load files into HDFS and Hive
Cloud-based and big data-based projects require a lot of guidelines to keep all factors in check and accounted for — review the most important ones. Data Storage, Data Processing, Data Locality, Various
🔵 Intellipaat Hadoop Training: https://intellipaat.com/big-data-hadoop-training/In this Big Data Tutorial for Beginners, Introduction to Big Data & Why choo...
A Hybrid Container Cloud With Kubernetes and Hadoop YARN - Hadoop YARN is a resource management platform to run big data applications such as MapReduce, Spark and it is architecturally different from Kubernetes which well suits long running services. In this talk we will present a framework developed by Alibaba, that can seamlessly run both Kubernetes and Hadoop in a single cluster with the ability of elastic resource sharing. In addition, we will also share lessons we learned in managing both workloads in production to support Alibaba massive commercial platform.
This Edureka video on Apache Pig Tutorial will help you understand the concepts of Apache Pig in depth.
This Edureka video on How to Setup Hadoop Cluster? will provide you with detailed knowledge about Hadoop and its concepts along with it. This video will help you to set up a Hadoop cluster on your own.
This Edureka Big Data Hadoop Tutorial For Beginners video will help you understand and learn Hadoop concepts in detail. This Big Data Hadoop Tutorial is ideal for both beginners as well as professionals who want to get started with the Hadoop Ecosystem.
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Here are the steps to migrate from Hadoop On-Premise to Google Cloud.
Learn how to use Apache Spark with SQL Server to process data efficiently from several different types of datafiles. Learn how you can process data with Apache Spark and what better way to establish the capabilities of Spark than to put it through its paces and use the Hadoop-DS benchmark to compare performance, throughput, and SQL compatibility against SQL Server.