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

( ** Apache Spark Training - https://ift.tt/2zseFNB ** ) 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: https://goo.gl/ViRJ2K -------------------------------------------------------------------------------------------------------- Instagram: https://ift.tt/2OMisuk Facebook: https://ift.tt/2pxExzM Twitter: https://twitter.com/edurekain LinkedIn: https://ift.tt/2oDkDGg ------------------------------------------------------------------------------------------------------- #ApacheSparkTutorial #SparkArchitecture #Edureka 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 lightning fast big data analysis platforms. The following Edureka blogs will help you understand the significance of Spark training: 5 Reasons to Learn Spark: https://goo.gl/7nMcS0 Apache Spark with Hadoop, Why it matters: https://goo.gl/I2MCeP Please write back to us at sales@edureka.co or call us at +91 88808 62004 for more information.
via Youtube at https://youtu.be/jffQhcweGwY

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