Hadoop Assignment: Apache Spark Assignment Help


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Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.

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Are Big Data and Hadoop same?

Big Data is nothing but a concept which facilitates handling large amount of datasets. Hadoop is just a single framework out of dozens of tools. Hadoop is primarily used for batch processing. The difference between big data and the open source software Hadoop is a distinct and fundamental one.



Apache Spark is a unified analytics engine for large-scale data processing.



Feature of Apache Spark


Speed

Apache Spark achieves high performance for both batch and streaming data


Ease of Use

Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells.


Generality

Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming.


Runs Everywhere

Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources.



Apache Hadoop Architecture

The Apache Hadoop framework comprises:

  • Hadoop Common – Contains libraries and utilities needed by other Hadoop modules

  • Hadoop Distributed File System (HDFS) – A distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster

  • Hadoop YARN – A resource-management platform responsible for managing compute resources in clusters and using them for scheduling of users' applications

  • Hadoop MapReduce– A programming model for large-scale data processing.


Most popular framework for Big Data, Hadoop

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