Apache Spark Tutorial | Spark Tutorial for Beginners | Apache Spark Training | Edureka

02:13 Big Data Introduction
13:02 Batch vs Real Time Analytics
1:00:02 What is Apache Spark?
1:01:16 Why Apache Spark?
1:03:27 Using Spark with Hadoop
1:06:37 Apache Spark Features
1:14:58 Apache Spark Ecosystem
1:18:01 Brief introduction to complete Spark Ecosystem Stack
1:40:24 Demo: Earthquake Detection Using Apache Spark

Subscribe to our channel to get video updates. Hit the subscribe button above.

#edureka #edurekaSpark #SparkTutorial #SparkOnlineTraining

How it Works?

1. This is a 4 Week Instructor led Online Course, 32 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to work on a project, based on which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course

This Spark training will enable learners to understand how Spark executes in-memory data processing and runs much faster than Hadoop MapReduce. Learners will master Scala programming and will get trained on different APIs which Spark offers such as Spark Streaming, Spark SQL, Spark RDD, Spark MLlib and Spark GraphX. This Edureka course is an integral part of Big Data developer's learning path.

After completing the Apache Spark and Scala training, you will be able to:

1) Understand Scala and its implementation
2) Master the concepts of Traits and OOPS in Scala programming
3) Install Spark and implement Spark operations on Spark Shell
4) Understand the role of Spark RDD
5) Implement Spark applications on YARN (Hadoop)
6) Learn Spark Streaming API
7) Implement machine learning algorithms in Spark MLlib API
8) Analyze Hive and Spark SQL architecture
9) Understand Spark GraphX API and implement graph algorithms
10) Implement Broadcast variable and Accumulators for performance tuning
11) Spark Real-time Projects

- - - - - - - - - - - - - -

Who should go for this Course?

This course is a must for anyone who aspires to embark into the field of big data and keep abreast of the latest developments around fast and efficient processing of ever-growing data using Spark and related projects. The course is ideal for:

1. Big Data enthusiasts
2. Software Architects, Engineers and Developers
3. Data Scientists and Analytics professionals

- - - - - - - - - - - - - -

Why learn Apache Spark?

In this era of ever growing data, the need for analyzing it for meaningful business insights is paramount. There are different big data processing alternatives like Hadoop, Spark, Storm and many more. Spark, however is unique in providing batch as well as streaming capabilities, thus making it a preferred choice for lightening fast big data analysis platforms.
The following Edureka blogs will help you understand the significance of Spark training:

Customer Review:

Michael Harkins, System Architect, Hortonworks says: “The courses are top rate. The best part is live instruction, with playback. But my favorite feature is viewing a previous class. Also, they are always there to answer questions, and prompt when you open an issue if you are having any trouble. Added bonus ~ you get lifetime access to the course you took!!! Edureka lets you go back later, when your boss says "I want this ASAP!" ~ This is the killer education app... I've taken two courses, and I'm taking two more.”

[arunasingh]

Well explained the concept of Lazy Evaluation!

[moview]

you are undoubtedly the king of all instructors...you rock man

[kag]

So far this is 4th course I am watching, Instructors from Edureka are amazing. Very well explained RDD in first half. Worth watching !!!

[daleoking]

This makes things more clear after my Data Science class lol. Thank you so much for a great tutorial, I think this will sharpen me up.

[nileshdhamanekar]

Awesome session! Hats off to the instructor, you are amazing! The RDD explanation was the best

[vinulovesutube]

Before starting this session I had no clue of Bigdata nor Spark . Now I have pretty decent insight . Thanks

[shamla]

Very detailed presentation and a very good instructor! Thank you!

[rmuru]

Excellent session...very informative..trainer is too good and explained all concepts in detail...thanks lot

[AdalarasanSachithanantham]

1st time really impressed in how the way you are teaching God bless you

[leojames]

One of the best video I ever watched.  MapReduce was not explained in this way wherever i checked.   Really thank you to post this.  Use Cases are really good.  Worth the time watching almost 2 hrs.  5 star to you the instructor.  Very impressed.

[draxutube]

SO GOOD TO WATCH I UNDERSTANDED SO MUCH

[arunasingh]

I have a question here, if we have almost 60M data then creating RDD while processing the data will helps in handling such huge data or some other processing steps required?

[gyanpattnaik]

Its an amazing video . Gives a complete concept of spark as well as its implementation in real world. Thanks

[taniakhan]

thank you so much for this wonderful tutorial.. I have a question.. while discussing about lazy evaluation, you mentioned that for B1 to B6 RDD memory is allocated, but they remain empty till collection is invoked. My qs is.. what is the size size of the memory that is allocated for each RDD? How does the framework predict the size before hand for each RDD without processing the data? eg, B4, B5, B6 might have different sizes and smaller or equal to B1, B2, B3 respectively... I didn't get this part. Could you please clarify?

[ramsp]

This one of the best and simplified Spark tutorial I have come across. 5 stars...!!!

[seenaiahpedipina]

Good explanation and useful tutorial. Conveyed a lot just in two hours. Thank you edureka !

[mix-fzln]

Awesome session! Hats off to the instructor,
I was searching hard to understand spark and nothing pop up to me and explained this session
amazing I love how the instructor clarify every concept and frames


you are amazing!

[yitayewsolomon]

thanks very much, I'm biggner for data science i got clear explanation for spark thanks alooot.

[puneethunplugged]

Thank you for the crisp session. Good content and flow. Appreciate it.

[moneymaker]

Excellent session no words to describe anything about it ...trainer is too good...worth watching