Are you looking for Apache Spark Assignment Help, Hadoop assignment help, Hadoop homework help?.
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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