Apache Spark Architecture | Spark Cluster Architecture Explained | Spark Training | Edureka

( ** Apache Spark Training - www.edureka.co/apache-spark-s... ** )
This Edureka Spark Architecture Tutorial video will help you to understand the Architecture of Spark in depth. It includes an example where we will create an application in Spark Shell using Scala. It will also take you through the Spark Web UI, DAG and Event Timeline of the executed tasks.
The following topics are covered in this video:
1. Apache Spark & Its features
2. Spark Eco-system
3. Resilient Distributed Dataset(RDD)
4. Spark Architecture
5. Word count example Demo using Scala.
Check our complete Apache Spark and Scala playlist here: goo.gl/ViRJ2K
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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!
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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
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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
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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 lightning fast big data analysis platforms.
The following Edureka blogs will help you understand the significance of Spark training:
5 Reasons to Learn Spark: goo.gl/7nMcS0
Apache Spark with Hadoop, Why it matters: goo.gl/I2MCeP
For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Пікірлер: 28

  • @edurekaIN
    @edurekaIN5 жыл бұрын

    Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Apache Spark Certification Training Curriculum, Visit the website: bit.ly/2KHSmII

  • @sibikrishnap5739
    @sibikrishnap57394 жыл бұрын

    Being a Spark Developer. I would say this is the best content I have ever come across which explains Spark Architecture in detail within 21 minutes. Kudos to your work.

  • @edurekaIN

    @edurekaIN

    4 жыл бұрын

    Thanks for the wonderful feedback! Do subscribe to our channel and stay connected with us. Cheers!

  • @balakk5009
    @balakk50092 жыл бұрын

    Thank you team of edureka! ,you did a such grate job entire subject into 10 minutes video. Can you explain DAG in detail like how filter work internally , group by ,sork ,insert statement ,update,delete how internally works Scan /seek Joining Filter Groupby Distinct Top Orderby Union ,unionall,intersect

  • @rohangurubhaiye2487
    @rohangurubhaiye24873 жыл бұрын

    Amazing Video ,Got to learn a whole lot about spark in a short duration ,Thank you Edureka.

  • @aggrawalnikhil02
    @aggrawalnikhil025 жыл бұрын

    In 21 minutes, I learnt lot of things....

  • @ptbejoy
    @ptbejoy5 жыл бұрын

    This video is very informative and very well explained. This is the best Edureka video that i watched so far . Thanks for the trainer.

  • @edurekaIN

    @edurekaIN

    5 жыл бұрын

    Hey Bejoy, thank you for appreciating our efforts. We are glad you loved the video. Do subscribe to the channel and hit the bell icon to never miss an update from us in the future. Cheers!

  • @rsamurti
    @rsamurti2 жыл бұрын

    In Spark is there any facility to capture the DAGs and the status of task scheduler before a job is executed? Is it possible to manually change the job scheduling policies?

  • @VivekYadav-gk9gy
    @VivekYadav-gk9gy5 жыл бұрын

    Web API was something new I learnt through this video.

  • @edurekaIN

    @edurekaIN

    5 жыл бұрын

    Hey Vivek, we are glad you loved the video. Do subscribe and hit the bell icon to never miss an update from edureka in the future. Cheers!

  • @babarhassan7726
    @babarhassan7726 Жыл бұрын

    Brilliant job👏 not only about spark architecture but also mini end to end project 👍

  • @edurekaIN

    @edurekaIN

    Жыл бұрын

    Thank you so much : ) We are glad to be a part of your learning journey. Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

  • @anshumanster
    @anshumanster5 жыл бұрын

    Very nicely explained ... crisp and very professional

  • @edurekaIN

    @edurekaIN

    5 жыл бұрын

    Hey Anshuman, thanks for the compliment. We are glad you loved the video. Do subscribe and hit the bell icon to never miss an update from us in the future. Cheers!

  • @arunprakash3103
    @arunprakash31034 жыл бұрын

    Thank You Edureka for such Informative videos.

  • @edurekaIN

    @edurekaIN

    4 жыл бұрын

    You are most welcome Arun, don't forget to Subscribe our channel.

  • @LearnAndShare9222
    @LearnAndShare92224 жыл бұрын

    Thank edurka. It would be great if you guys help us to understand Spark vs YARN architecture ( in terms of similarities & differences)

  • @edurekaIN

    @edurekaIN

    4 жыл бұрын

    Thanks for watching the video. We will process your request as soon as possible. Do subscribe to our channel and stay connected with us. Cheers :)

  • @ashinkajay
    @ashinkajay2 жыл бұрын

    Thank you !

  • @geethasudhakar6759
    @geethasudhakar67594 жыл бұрын

    Excellent Explanation.

  • @edurekaIN

    @edurekaIN

    4 жыл бұрын

    Thank you. You can also check out our complete training here: Apache Spark and Scala Certification Training - bit.ly/3bWTxQh Use code "KZread20" to get Flat 20% off on this training.

  • @skateforlife3679
    @skateforlife36792 жыл бұрын

    Nice spark is

  • @edurekaIN

    @edurekaIN

    2 жыл бұрын

    Thank you so much for your review on our channel  Great to hear that Edureka is helping you learn better . We’ll strive to make even better learning contents/courses in the future ! Do subscribe the channel for more updates : )

  • @vikramj22
    @vikramj225 жыл бұрын

    Why the output in spite of being so small in size got split in two parts ?

  • @edurekaIN

    @edurekaIN

    5 жыл бұрын

    Hi Vikram, it's because one partition could have hit the performance rate.

  • @balajicherukuri
    @balajicherukuri4 жыл бұрын

    Why there are multiple part files, rather than single part file?

  • @edurekaIN

    @edurekaIN

    4 жыл бұрын

    The file gets divided into multiple part files as default. You can also keep one single part file as well. no issues regarding that.