Asked by: Omnia Akil
technology and computing data storage and warehousing

Which is better to learn spark or Hadoop?

Last Updated: 14th April, 2020

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No, it is not mandatory to learn Hadoop first tolearn Spark but basic knowledge of Hadoop and HDFSwill add an advantage to your learning of Spark.Spark is an emerging technology and is a market buzz.Learning Spark will be beneficial for your career asSpark professionals are more preferred in theindustry.

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Furthermore, which is better Hadoop or spark?

Hadoop is designed to handle batch processingefficiently whereas Spark is designed to handle real-timedata efficiently. Hadoop is a high latency computingframework, which does not have an interactive mode whereasSpark is a low latency computing and can process datainteractively.

Furthermore, is spark better than MapReduce? Key Difference Between MapReduce vs ApacheSpark MapReduce is strictly disk-based while ApacheSpark uses memory and can use a disk for processing.Spark is able to execute batch-processing jobs between 10 to100 times faster than the MapReduce Although both thetools are used for processing Big Data.

Also to know, is it necessary to learn Hadoop for spark?

No, you don't need to learn Hadoop to learnSpark. Spark was an independent project . But after YARNand Hadoop 2.0, Spark became popular becauseSpark can run on top of HDFS along with other Hadoopcomponents. Hadoop is a framework in which you writeMapReduce job by inheriting Java classes.

Is Apache spark worth learning?

1) Learn Apache Spark to have Increased Access toBig Data Data scientists are exhibiting interest in working withSpark because of its ability to store data resident inmemory that helps speed up machine learning workloads unlikeHadoop MapReduce.

Related Question Answers

Ortansa Zurheide

Professional

Does spark replace Hadoop?

Besides, Spark does not have its own filemanagement system, so you need to integrate with Hadoop, orother cloud based data platforms. For many of the input and outputformats, Spark still uses Hadoop's IO classes. So,Spark needs to come a long way in order to replaceHadoop.

Gianna Wernke

Professional

Is Hadoop outdated?

No, Hadoop is not outdated. There is stillno replacement for Hadoop ecosystem. HDFS is still the mostreliable storage system in world and more than 50% of the world'sData has been moved to Hadoop. Inshort, you shoulddefinitely learn Hadoop what ever new technologies come,Hadoop will be the base.

Fiordaliza Moran

Professional

Does Databricks use Hadoop?

Databricks cloud helps analysts by organizing thedata into "notebooks" and making it easy to visualize data throughthe use of dashboards. It also makes it easy to analyze datausing machine learning (MLib), GraphX and SparkSQL.

Huaying Fouces

Explainer

What are the alternatives to Hadoop?

What are Hadoop alternatives and should you look forone?
  • Apache Spark. Hailed as the de-facto successor to the alreadypopular Hadoop, Apache Spark is used as a computational engine forHadoop data.
  • Apache Storm. Apache Storm is another excellent, open-sourcetool used for processing large quantities of analytics data.
  • Google BigQuery.
  • DataTorrent RTS.
  • Hydra.

Mariana Pelarda

Explainer

Is Hadoop a memory?

Hadoop and in-memory databases aredifferent technologies, but they overlap. They're not the same butthey are compatible. Hadoop does not do the analytics byitself. Hadoop is a framework which supports theHadoop Distributed File System (HDFS) andMapReduce.

Lingzhi Brink

Explainer

Is Hadoop a database?

What is Hadoop? Hadoop is not a type ofdatabase, but rather a software ecosystem that allows formassively parallel computing. It is an enabler of certain typesNoSQL distributed databases (such as HBase), which can allowfor data to be spread across thousands of servers with littlereduction in performance.

Timotea Alto

Pundit

Why spark is faster than Hadoop?

The biggest claim from Spark regarding speed isthat it is able to "run programs up to 100x faster thanHadoop MapReduce in memory, or 10x faster on disk."Spark could make this claim because it does the processingin the main memory of the worker nodes and prevents the unnecessaryI/O operations with the disks.

Aitziber Bronne

Pundit

What database does spark use?

Spark SQL -- One of the most commonly usedlibraries, Spark SQL enables users to query data stored indisparate applications using the common SQL language.Spark Streaming -- This library enables users to buildapplications that analyze and present data in realtime.

Nekal Ienco

Pundit

Is Hadoop difficult to learn?

Hadoop programming is easier for people with SQLskills too - thanks to Pig and Hive. Students or professionalswithout any programming background, with just basic SQL knowledge,can master Hadoop through comprehensive hands-onHadoop training if they have the zeal and willingness tolearn.

Kostadin Kisie

Pundit

Is python required for Hadoop?

Hadoop framework is written in Java language, butit is entirely possible for Hadoop programs to be coded inPython or C++ language. Which implies that data architectsdon't have to learn Java, if they are familiar withPython.

Przemyslaw Worgan

Pundit

What is difference between Hadoop and Spark?

In fact, the key difference between HadoopMapReduce and Spark lies in the approach toprocessing: Spark can do it in-memory, while HadoopMapReduce has to read from and write to a disk. As a result, thespeed of processing differs significantly – Spark maybe up to 100 times faster.

Rabii Casanellas

Teacher

Where can I learn big data for free?

The 9 Best Free Online Big Data And Data ScienceCourses
  • Who could benefit from a free online data science course?
  • Coursera – Data Science Specialization.
  • Coursera – Data-Driven Decision Making.
  • EdX – Data Science Essentials.
  • Udacity – Intro to Machine Learning.
  • IBM – Data Science Fundamentals.
  • California Institute of Technology – Learning fromData.

Laurynas Krumlinde

Teacher

Do data scientist need to know Hadoop?

Data scientists have several technical skillslike Hadoop, NoSQL, Python, Spark, R, Java and more. Forsome, a data scientist should have the ability to managedata using Hadoop along with a good ability to runstatistics against the data set.

Ula Bohmler

Teacher

Where can I practice Big Data?

I would suggest heading over to any of the below mentionedwebsites to learn and practice Big Data.
  • Big Data University | Data Science Courses.
  • Udacity - Free Online Classes & Nanodegrees.
  • Udemy: Online Courses Anytime, Anywhere.
  • Coursera.
  • Harvard.
  • Stanford.
  • CalTech.

Franc Jluktov

Teacher

Why Scala is used in spark?

1) Apache Spark is written in Scala andbecause of its scalability on JVM - Scala programming ismost prominently used programming language, by big datadevelopers for working on Spark projects. Also, theperformance achieved using Scala is better than many othertraditional data analysis tools like R or Python.

Andriy Sucino

Reviewer

How long does it take to learn Hadoop?

approximately 3-4 months

Hortensio Weigand

Reviewer

What is difference between Spark and Scala?

The difference between Spark and Scala is that thApache Spark is a cluster computing framework, designed forfast Hadoop computation while the Scala is a general-purposeprogramming language that supports functional and object-orientedprogramming. Scala is one language that is used to writeSpark.

Sifeddine Piterskih

Reviewer

Why do we need spark?

Spark uses Micro-batching for real-timestreaming. Apache Spark is open source, general-purposedistributed computing engine used for processing and analyzing alarge amount of data. Just like Hadoop MapReduce, it also workswith the system to distribute data across the cluster and processthe data in parallel.

Navia Fortunez

Reviewer

Does spark run MapReduce?

Spark vs. Hadoop MapReduce. The secret isthat it runs in-memory on the cluster, and that it isn'ttied to Hadoop's MapReduce two-stage paradigm. This makesrepeated access to the same data much faster. Spark can runas a standalone or on top of Hadoop YARN, where it can readdata directly from HDFS.