Analytics Vidhya

JUNE 14, 2022

Introduction Hadoop is an open-source, Java-based framework used to store and process large amounts of data. The post Introduction to Hadoop Architecture and Its Components appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Developed by Doug Cutting and Michael […].

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Analytics Vidhya

OCTOBER 23, 2020

Overview Hadoop is among the most popular tools in the data engineering and Big Data space Here’s an introduction to everything you need to. The post Introduction to the Hadoop Ecosystem for Big Data and Data Engineering appeared first on Analytics Vidhya.

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Analytics Vidhya

SEPTEMBER 14, 2022

The post Frequent Itemset Mining Using MapReduce on Hadoop appeared first on Analytics Vidhya. Introduction Every Data Science enthusiast’s journey goes through one of the most classical data problems – Frequent Itemset Mining, also sometimes referred to as Association Rule Mining or Market Basket Analysis.

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Analytics Vidhya

JUNE 14, 2022

Earlier to it, Hadoop MapReduce was the main focus for processing large data with no competitors. The post Apache Spark Vs. Hadoop MapReduce – Top 7 Differences appeared first on Analytics Vidhya. Introduction Apache Spark was released in 2014. Let’s take a […].

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Analytics Vidhya

MAY 31, 2022

The post The Tale of Apache Hadoop YARN! Initially, it was described as “Redesigned Resource Manager” as it separates the processing engine and the management function of MapReduce. Apart from resource management, […]. appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 5, 2023

Big data […] The post A Beginner’s Guide to the Basics of Big Data and Hadoop appeared first on Analytics Vidhya. Big data is nothing but the vast volume of datasets measured in terabytes or petabytes or even more.

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Analytics Vidhya

OCTOBER 28, 2020

Overview Get familiar with Hadoop Distributed File System (HDFS) Understand the Components of HDFS Introduction In contemporary times, it is commonplace to deal. The post Hadoop Distributed File System (HDFS) Architecture – A Guide to HDFS for Every Data Engineer appeared first on Analytics Vidhya.

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Analytics Vidhya

MAY 5, 2022

Introduction This article will discuss the Hadoop Distributed File System, its features, components, functions, and benefits. Hadoop is a powerful platform for supporting an enormous variety of data applications. The post Workings of Hadoop Distributed File System (HDFS) appeared first on Analytics Vidhya.

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Analytics Vidhya

JULY 5, 2022

Introduction MapReduce is part of the Apache Hadoop ecosystem, a framework that develops large-scale data processing. Other components of Apache Hadoop include Hadoop Distributed File System (HDFS), Yarn, and Apache Pig. This article was published as a part of the Data Science Blogathon.

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Analytics Vidhya

MARCH 16, 2023

Apache Oozie is a workflow scheduler system for managing Hadoop jobs. It enables users to plan and carry out complex data processing workflows while handling several tasks and operations throughout the Hadoop ecosystem. Introduction This article will be a deep guide for Beginners in Apache Oozie.

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Analytics Vidhya

JANUARY 7, 2022

In today’s world, data is being generated at an ever-growing pace, leading to a boom in demand for Big Data tools such as Hadoop, Pig, Spark, Hive, and many more. The tool that stands out the most is Apache Hadoop, and one of its core components is YARN. Apache Hadoop YARN, or as it is […].

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Dataconomy

OCTOBER 9, 2017

Image: SAP Cloud Platform Hadoop is a Java-based, open source framework that supports companies in the storage and processing of massive data sets. Currently, many firms still struggle with interpreting Hadoop’s software and are doubtful about whether or not they can depend on it for delivering projects. Even so, it’s.

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Analytics Vidhya

JANUARY 11, 2023

Introduction Amazon Elastic MapReduce (EMR) is a fully managed service that makes it easy to process large amounts of data using the popular open-source framework Apache Hadoop. EMR enables you to run petabyte-scale data warehouses and analytics workloads using the Apache Spark, Presto, and Hadoop ecosystems.

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Analytics Vidhya

JANUARY 31, 2023

It is designed to be more flexible and generic than the original Hadoop MapReduce system, making it an attractive choice for companies looking to implement Hadoop. It is a powerful resource management system for a horizontal server environment.

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Analytics Vidhya

MAY 12, 2022

Introduction Apache Flume, a part of the Hadoop ecosystem, was developed by Cloudera. This article was published as a part of the Data Science Blogathon. Initially, it was designed to handle log data solely, but later, it was developed to process event data. The Apache Flume tool is designed mainly for ingesting a high volume […].

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Analytics Vidhya

FEBRUARY 1, 2023

Introduction In this constantly growing technical era, big data is at its peak, with the need for a tool to import and export the data between RDBMS and Hadoop. Apache Sqoop stands for “SQL to Hadoop,” and is one such tool that transfers data between Hadoop(HIVE, HBASE, HDFS, etc.)

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Analytics Vidhya

JULY 25, 2022

Introduction Apache Sqoop is a big data engine for transferring data between Hadoop and relational database servers. Sqoop transfers data from RDBMS (Relational Database Management System) such as MySQL and Oracle to HDFS (Hadoop Distributed File System). This article was published as a part of the Data Science Blogathon.

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Dataconomy

MAY 14, 2018

The post Hadoop Evolved: How Industries Are Being Transformed By Big Data appeared first on Dataconomy. The message tells him to get off immediately because his pulse is abnormally high, which puts him at risk of a heart attack. Such a scenario is not far off thanks to Pontem, a platform.

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Analytics Vidhya

FEBRUARY 14, 2023

Introduction Today we have an abundance of Hadoop jobs that are running in a constant plane, but we can’t schedule these jobs manually, we need some kind of scheduler to handle this flow. Apache Oozie is one such job scheduler that allows users to run, schedule, and manage Hadoop jobs in a distributed environment.

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Analytics Vidhya

OCTOBER 21, 2021

This article was published as a part of the Data Science Blogathon Overview Hadoop is widely used in the industry to examine large data volumes. The reason for this is that the Hadoop framework is based on a basic programming model (MapReduce), which allows for a scalable, flexible, fault-tolerant, and cost-effective computing solution.

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Analytics Vidhya

MAY 18, 2022

Introduction Hadoop facilitates the processing of large datasets in a distributed manner and provides the foundation on which other services and applications can be built. MapReduce and HDFS are the two main components of Hadoop. This article was published as a part of the Data Science Blogathon.

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Analytics Vidhya

OCTOBER 12, 2022

With the advent of big data, several organizations realized the benefits of big data processing and started choosing solutions like Hadoop to […]. Introduction Since the 1970s, relational database management systems have solved the problems of storing and maintaining large volumes of structured data.

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Analytics Vidhya

JULY 11, 2022

Introduction YARN is an open-source project for Apache representing “Yet Another Resource Negotiator” Hadoop Collection Manager is responsible for sharing resources (such as CPU, memory, disk, and network), and organizing and monitoring tasks throughout the Hadoop collection.

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Analytics Vidhya

MARCH 5, 2023

Introduction Microsoft Azure HDInsight(or Microsoft HDFS) is a cloud-based Hadoop Distributed File System version. HDInsight works seamlessly with the Hadoop ecosystem, which includes technologies like MapReduce, Hive, […] The post Top 6 Microsoft HDFS Interview Questions appeared first on Analytics Vidhya.

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Dataconomy

APRIL 21, 2016

Recent technology advances within the Apache Hadoop ecosystem have provided a big boost to Hadoop’s viability as an analytics environment—above and beyond just being a good place to store data. Leveraging these advances, new technologies now support SQL on Hadoop, making in-cluster analytics of data in Hadoop a reality.

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Analytics Vidhya

FEBRUARY 20, 2022

Introduction Apache Hive is a data warehouse system built on top of Hadoop which gives the user the flexibility to write complex MapReduce programs in form of SQL- like queries. This article was published as a part of the Data Science Blogathon. Performance Tuning is an essential part of running Hive Queries as it helps […].

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Dataconomy

MARCH 7, 2016

If you listen in on what people are talking about at Big Data conferences, chances are you’ll hear a lot of buzz around Hadoop and Spark. People often think of Hadoop and Apache Spark as key tools for tackling a wide range of big data challenges, but they assume that.

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Analytics Vidhya

FEBRUARY 6, 2023

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It is a core component of the Apache Hadoop ecosystem and allows for storing and processing large datasets across multiple commodity servers.

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Analytics Vidhya

AUGUST 1, 2022

Introduction HBase is a column-oriented non-relational database management system that operates on Hadoop Distributed File System (HDFS). This article was published as a part of the Data Science Blogathon. HBase provides a fault-tolerant manner of storing sparse data sets, which are prevalent in several big data use cases.

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Analytics Vidhya

APRIL 29, 2022

Introduction Apache Hadoop is the most used open-source framework in the industry to store and process large data efficiently. Hive is built on the top of Hadoop for providing data storage, query and processing capabilities. This article was published as a part of the Data Science Blogathon.

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Analytics Vidhya

FEBRUARY 2, 2023

Hadoop, the Open-Source Software Framework for scalable and scattered computation of massive data sets, makes it easy. Introduction Big data processing is crucial today. Big data analytics and learning help corporations foresee client demands, provide useful recommendations, and more.

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Analytics Vidhya

OCTOBER 28, 2021

The official description of Hive is- ‘Apache Hive data warehouse software project built on top of Apache Hadoop for providing data query and analysis. This article was published as a part of the Data Science Blogathon What is the need for Hive? Hive gives an SQL-like interface to query data stored in various databases and […].

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Analytics Vidhya

OCTOBER 10, 2022

You would have already worked on systems that used traditional warehouses or Hadoop-based data lakes. Introduction Most of you would know the different approaches for building a data and analytics platform. Some of you might have also read about Lakehouses. Selecting one among […].

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Analytics Vidhya

AUGUST 30, 2021

It is built on top of Hadoop and can process batch as well as streaming data. Hadoop is a framework for distributed computing that […]. This article was published as a part of the Data Science Blogathon Introduction Spark is an analytics engine that is used by data scientists all over the world for Big Data Processing.

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Analytics Vidhya

AUGUST 2, 2022

Introduction Apache Oozie is a distributed workflow scheduler for performing and controlling Hadoop tasks. This article was published as a part of the Data Science Blogathon. MapReduce, Sqoop, Pig, and Hive jobs can be easily scheduled with this tool. It allows for the sequential enforcement of several difficult tasks to finish a bigger task.

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Analytics Vidhya

AUGUST 17, 2022

Introduction Impala is an open-source and native analytics database for Hadoop. This article was published as a part of the Data Science Blogathon. Vendors such as Cloudera, Oracle, MapReduce, and Amazon have shipped Impala. If you want to learn all things Impala, you’ve come to the right place.

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Analytics Vidhya

SEPTEMBER 20, 2022

Introduction Apache Oozie is a Hadoop workflow scheduler. Users can design Directed Acyclic Graphs of workflows that can be run in parallel and sequentially in Hadoop. This article was published as a part of the Data Science Blogathon. It is a system that manages the workflow of dependent tasks.

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