Apache spark example

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Apache Spark / PySpark Tutorial: Basics In 15 Mins

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25.03.2021

Looking to Become a Data Scientist FASTER?? SUBSCRIBE with NOTIFICATIONS ON 🔔! The Notebook: 🤍 Apache Spark / PySpark Tutorial in 15 minutes! Data Scientists, Data Engineers, and all Data Enthusiasts NEED to know Spark! This video gives an introduction to the Spark ecosystem and world of Big Data, using the Python Programming Language and its PySpark API. We also discuss the idea of parallel and distributed computing, and computing on a cluster of machines. Roadmap to Become a Data Scientist / Machine Learning Engineer in 2022: 🤍 Roadmap to Become a Data Analyst in 2022: 🤍 Roadmap to Become a Data Engineer in 2022: 🤍 Here's my favourite resources: Best Courses for Analytics: - + IBM Data Science (Python): 🤍 + Google Analytics (R): 🤍 + SQL Basics: 🤍 Best Courses for Programming: - + Data Science in R: 🤍 + Python for Everybody: 🤍 + Data Structures & Algorithms: 🤍 Best Courses for Machine Learning: - + Math Prerequisites: 🤍 + Machine Learning: 🤍 + Deep Learning: 🤍 + ML Ops: 🤍 Best Courses for Statistics: - + Introduction to Statistics: 🤍 + Statistics with Python: 🤍 + Statistics with R: 🤍 Best Courses for Big Data: - + Google Cloud Data Engineering: 🤍 + AWS Data Science: 🤍 + Big Data Specialization: 🤍 More Courses: - + Tableau: 🤍 + Excel: 🤍 + Computer Vision: 🤍 + Natural Language Processing: 🤍 + IBM Dev Ops: 🤍 + IBM Full Stack Cloud: 🤍 + Object Oriented Programming (Java): 🤍 + TensorFlow Advanced Techniques: 🤍 + TensorFlow Data and Deployment: 🤍 + Generative Adversarial Networks / GANs (PyTorch): 🤍 Become a Member of the Channel! 🤍 Follow me on LinkedIn! 🤍 Art: 🤍 🤍 Music: 🤍 Sound effects: 🤍 Full Disclosure: Please note that I may earn a commission for purchases made at the above sites! I strongly believe in the material provided; I only recommend what I truly think is great. If you do choose to make purchases through these links; thank you for supporting the channel, it helps me make more free content like this! #GregHogg #DataScience #MachineLearning

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

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25.09.2018

( Apache Spark Training - 🤍 ) 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: 🤍 Instagram: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 - #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: 🤍 Apache Spark with Hadoop, Why it matters: 🤍 For more information, Please write back to us at sales🤍edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Spark Tutorial For Beginners | Big Data Spark Tutorial | Apache Spark Tutorial | Simplilearn

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00:15:40
13.07.2017

🔥Free Big Data Hadoop and Spark Developer course: 🤍 This Spark Tutorial For Beginners will give an overview on the history of spark, what is spark, Batch vs real-time processing, Limitations of MapReduce in Hadoop, Introduction to Spark, Components of Spark Project and a comparison between Hadoop ecosystem and Spark. Let's get started with this Big Data Spark Tutorial! This Apache Spark Tutorial video will explain: 1. History of Spark - 00:00 2. Introduction to Spark - 04:02 3. Spark Components - 05:00 4. Spark Advantages - 12:31 Subscribe to Simplilearn channel for more Big Data and Hadoop Tutorials - 🤍 Check our Big Data Training Video Playlist: 🤍 Big Data and Analytics Articles - 🤍 To gain in-depth knowledge of Big Data and Hadoop, check our Big Data Hadoop and Spark Developer Certification Training Course: 🤍 #ApacheSparkTutorialforBeginners #SparkTutorial #Spark #WhatisSpark #ApacheSparkTutorial #SparkTutorialforBeginners #WhatisApacheSpark Apache Spark is an open-source cluster-computing framework. It is an analytics engine that was originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. It is used for processing and analyzing large amounts of data. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance. About Simplilearn's Big Data and Hadoop Certification Training Course: The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. You will also learn the various interactive algorithm in Spark and use Spark SQL. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. This Big Data course also prepares you for the Cloudera CCA175 certification. What are the course objectives of this Big Data and Hadoop Certification Training Course? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists Learn more at: 🤍 For more updates on courses and tips follow us on: - Facebook : 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the android app: 🤍 Get the iOS app: 🤍

Apache Spark Word Count example - Spark Shell

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00:11:23
18.01.2015

A live demonstration of using "spark-shell" and the Spark History server, The "Hello World" of the BigData world, the "Word Count". You can find the commands executed in the new link: 🤍 The input file can be found at: 🤍 For further questions you can leave comments. Enjoy.

PySpark Tutorial

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14.07.2021

Learn PySpark, an interface for Apache Spark in Python. PySpark is often used for large-scale data processing and machine learning. 💻 Code: 🤍 ✏️ Course from Krish Naik. Check out his channel: 🤍 ⌨️ (0:00:10) Pyspark Introduction ⌨️ (0:15:25) Pyspark Dataframe Part 1 ⌨️ (0:31:35) Pyspark Handling Missing Values ⌨️ (0:45:19) Pyspark Dataframe Part 2 ⌨️ (0:52:44) Pyspark Groupby And Aggregate Functions ⌨️ (1:02:58) Pyspark Mlib And Installation And Implementation ⌨️ (1:12:46) Introduction To Databricks ⌨️ (1:24:65) Implementing Linear Regression using Databricks in Single Clusters 🎉 Thanks to our Champion and Sponsor supporters: 👾 Wong Voon jinq 👾 hexploitation 👾 Katia Moran 👾 BlckPhantom 👾 Nick Raker 👾 Otis Morgan 👾 DeezMaster 👾 Treehouse Learn to code for free and get a developer job: 🤍 Read hundreds of articles on programming: 🤍

Apache Spark Tutorial | What Is Apache Spark? | Introduction To Apache Spark | Simplilearn

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01.08.2019

🔥 Enroll for FREE Big Data Hadoop Spark Course & Get your Completion Certificate: 🤍 This video on What Is Apache Spark? covers all the basics of Apache Spark that a beginner needs to know. In this introduction to Apache Spark video, we will discuss what is Apache Spark, the history of Spark, Hadoop vs Spark, Spark features, components of Apache Spark, Spark core, Spark SQL, Spark streaming, applications of Spark, etc. Below topics are explained in this Apache Spark Tutorial: 00.00 Introduction 00:41 History of Spark 01:22 What is Spark? 02:26 Hadoop vs Spark 05:29 Spark Features 08:27 Components of Apache Spark 10:24 Spark Core 11:28 Resilient Distributed Dataset 18:08 Spark SQL 21:28 Spark Streaming 24:57 Spark MLlib 25:54 GraphX 27:20 Spark architecture 32:16 Spark Cluster Managers 33:59 Applications of Spark 36:01 Spark use case 38:02 Conclusion To learn more about Spark, subscribe to our YouTube channel: 🤍 To access the slides, click here: 🤍 Watch more videos on Spark Training: 🤍 #WhatIsApacheSpark #ApacheSpark #ApacheSparkTutorial #SparkTutorialForBeginners #SimplilearnApacheSpark #SparkTutorial #Simplilearn Introduction to Apache Spark: Apache Spark Is an open-source cluster computing framework that was initially developed at UC Berkeley in the AMPLab. As compared to the disk-based, two-stage MapReduce of Hadoop, Spark provides up to 100 times faster performance for a few applications with in-memory primitives. This makes it suitable for machine learning algorithms, as it allows programs to load data into the memory of a cluster and query the data constantly. A Spark project contains various components such as Spark Core and Resilient Distributed Datasets or RDDs, Spark SQL, Spark Streaming, Machine Learning Library or Mllib, and GraphX. About Simplilearn Apache Spark Certification training: This Apache Spark and Scala certification training is designed to advance your expertise working with the Big Data Hadoop Ecosystem. You will master essential skills of the Apache Spark open source framework and the Scala programming language, including Spark Streaming, Spark SQL, machine learning programming, GraphX programming, and Shell Scripting Spark. This Scala Certification course will give you vital skillsets and a competitive advantage for an exciting career as a Hadoop Developer. What are the course objectives? Simplilearn’s Apache Spark and Scala certification training are designed to: 1. Advance your expertise in the Big Data Hadoop Ecosystem 2. Help you master essential Apache and Spark skills, such as Spark Streaming, Spark SQL, machine learning programming, GraphX programming and Shell Scripting Spark 3. Help you land a Hadoop developer job requiring Apache Spark expertise by giving you a real-life industry project coupled with 30 demos What skills will you learn? By completing this Apache Spark and Scala course you will be able to: 1. Understand the limitations of MapReduce and the role of Spark in overcoming these limitations 2. Understand the fundamentals of the Scala programming language and its features 3. Explain and master the process of installing Spark as a standalone cluster 4. Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark 5. Master Structured Query Language (SQL) using SparkSQL 6. Gain a thorough understanding of Spark streaming features 7. Master and describe the features of Spark ML programming and GraphX programming Who should take this Scala course? 1. Professionals aspiring for a career in the field of real-time big data analytics 2. Analytics professionals 3. Research professionals 4. IT developers and testers 5. Data scientists 6. BI and reporting professionals Learn more about Apache Spark at 🤍 For more information about Simplilearn courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

Spark Streaming Example with PySpark ❌ BEST Apache SPARK Structured STREAMING TUTORIAL with PySpark

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15.10.2020

In this video we'll understand Spark Streaming with PySpark through an applied example of how we might use Structured Streaming in a real world scenario. Stream processing is the act of continuously incorporating new data to compute a result. In stream processing, the input data has no predetermined beginning or end as it simply forms a series of events that arrive as a stream (ex. credit card transactions). Here we're focusing on Structured Streaming in Spark using Python, more specifically PySpark, and in the simplest terms, Structured Streaming is a dataFrame, but streaming. The main idea behind Spark Structured Streaming is to treat a stream of data as a table, a dataset to which data is continuously appended. The job then periodically checks for new input data, processes it and updates the result. You can access the Jupyter notebook here (login required): 🤍 🎁 1 MONTH FREE TRIAL! Financial and Alternative Datasets for today's Data Analysts & Scientists: 🤍 📚 RECOMMENDED DATA SCIENCE BOOKS: 🤍 ✅ Subscribe and support us: 🤍 💻 Data Science resources I strongly recommend: 🤍 🌐 Let's connect: 🤍 - At DecisionForest we serve both retail and institutional investors by providing them with the data necessary to make better decisions: 🤍 #DecisionForest

Apache Spark - Computerphile

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12.12.2018

Analysing big data stored on a cluster is not easy. Spark allows you to do so much more than just MapReduce. Rebecca Tickle takes us through some code. 🤍 🤍 This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: 🤍 Computerphile is a sister project to Brady Haran's Numberphile. More at 🤍

Big Data Spark Tutorial | Apache Spark Example | Spark Training | Edureka | Apache Spark Live - 1

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00:36:36
08.04.2020

🔥Apache Spark Training - 🤍 This Edureka video on "Apache Spark Tutorial for beginners" will provide you with the detailed and comprehensive knowledge about apache Spark, You will learn about the various Spark facts, features, and applications of Apache Spark. This video will cover the following topics: Why we need Apache Spark? Apache Spark Features Spark Eco-System Hands-on Examples Use Case Check our complete Apache Spark and Scala playlist here: 🤍 Spark Blog Series: 🤍 Subscribe to our channel to get video updates. Hit the subscribe button above. PG in Big Data Engineering with NIT Rourkela : 🤍 (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) Instagram: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Telegram: 🤍 #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: 5 Reasons to Learn Spark: 🤍 Apache Spark with Hadoop, Why it matters: 🤍 For more information, Please write back to us at sales🤍edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Apache Spark - MapReduce example and difference between hadoop and spark engine

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00:14:38
24.10.2015

Connect with me or follow me at 🤍 🤍 🤍 🤍 🤍

Apache Spark Full Course - Learn Apache Spark in 8 Hours | Apache Spark Tutorial | Edureka

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07:48:37
27.10.2019

Edureka Apache Spark Training (Use Code: YOUTUBE20) - 🤍 ) This Edureka Spark Full Course video will help you understand and learn Apache Spark in detail. This Spark tutorial is ideal for both beginners as well as professionals who want to master Apache Spark concepts. Below are the topics covered in this Spark tutorial for beginners: 00:00 Agenda 2:44 Introduction to Apache Spark 3:49 What is Spark? 5:34 Spark Eco-System 7:44 Why RDD? 16:44 RDD Operations 18:59 Yahoo Use-Case 21:09 Apache Spark Architecture 24:24 RDD 26:59 Spark Architecture 31:09 Demo 39:54 Spark RDD 41:09 Spark Applications 41:59 Need For RDDs 43:34 What are RDDs? 44:24 Sources of RDDs 45:04 Features of RDDs 46:39 Creation of RDDs 50:19 Operations Performed On RDDs 50:49 Narrow Transformations 51:04 Wide Transformations 51:29 Actions 51:44 RDDs Using Spark Pokemon Use-Case 1:05:19 Spark DataFrame 1:06:54 What is a DataFrame? 1:08:24 Why Do We Need Dataframes? 1:09:54 Features of DataFrames 1:11:09 Sources Of DataFrames 1:11:34 Creation Of DataFrame 1:24:44 Spark SQL 1:25:14 Why Spark SQL? 1:27:09 Spark SQL Advantages Over Hive 1:31:54 Spark SQL Success Story 1:33:24 Spark SQL Features 1:37:15 Spark SQL Architecture 1:39:40 Spark SQL Libraries 1:42:15 Querying Using Spark SQL 1:45:50 Adding Schema To RDDs 1:55:05 Hive Tables 1:57:50 Use Case: Stock Market Analysis with Spark SQL 2:16:50 Spark Streaming 2:18:10 What is Streaming? 2:25:46 Spark Streaming Overview 2:27:56 Spark Streaming workflow 2:31:21 Streaming Fundamentals 2:33:36 DStream 2:38:56 Input DStreams 2:40:11 Transformations on DStreams 2:43:06 DStreams Window 2:47:11 Caching/Persistence 2:48:11 Accumulators 2:49:06 Broadcast Variables 2:49:56 Checkpoints 2:51:11 Use-Case Twitter Sentiment Analysis 3:00:26 Spark MLlib 3:00:31 MLlib Techniques 3:01:46 Demo 3:11:51 Use Case: Earthquake Detection Using Spark 3:24:01 Visualizing Result 3:25:11 Spark GraphX 3:26:01 Basics of Graph 3:27:56 Types of Graph 3:38:56 GraphX 3:40:42 Property Graph 3:48:37 Creating & Transforming Property Graph 3:56:17 Graph Builder 4:02:22 Vertex RDD 4:07:07 Edge RDD 4:11:37 Graph Operators 4:24:37 GraphX Demo 4:34:24 Graph Algorithms 4:34:40 PageRank 4:38:29 Connected Components 4:40:39 Triangle Counting 4:44:09 Spark GraphX Demo 4;57:54 MapReduce vs Spark 5:13:03 Kafka with Spark Streaming 5:23:38 Messaging System 5:21:15 Kafka Components 2:23:45 Kafka Cluster 5:24:15 Demo 5:48:56 Kafka Spark Streaming Demo 6:17:16 PySpark Tutorial 6:21:26 PySpark Installation 6:47:06 Spark Interview Questions PG in Big Data Engineering with NIT Rourkela : 🤍 (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) Instagram: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, please write back to us at sales🤍edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Spark Streaming | Twitter Sentiment Analysis Example | Apache Spark Training | Edureka

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00:45:15
26.02.2017

( Apache Spark Training - 🤍 ) This Edureka Spark Streaming Tutorial (Spark Streaming blog: 🤍 will help you understand how to use Spark Streaming to stream data from twitter in real-time and then process it for Sentiment Analysis. This Spark Streaming tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Apache Spark concepts. Below are the topics covered in this tutorial: 1:08 What is Streaming? 4:26 Spark Ecosystem 7:04 Why Spark Streaming? 8:52 Spark Streaming Overview 16:36 DStreams 23:12 DStream Transformations 30:14 Caching/ Persistence 31:12 Accumulators, Broadcast Variables and Checkpoints 34:18 Use Case - Twitter Sentiment Analysis Subscribe to our channel to get video updates. Hit the subscribe button above. PG in Big Data Engineering with NIT Rourkela : 🤍 (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) Check our complete Apache Spark and Scala playlist here: 🤍 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: 5 Reasons to Learn Spark: 🤍 Apache Spark with Hadoop, Why it matters: 🤍 For more information, Please write back to us at sales🤍edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 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.”

Apache Spark Machine Learning Example code review

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23.05.2016

Spark Machine Learning code review from our Apache Spark with Scala training course available at 🤍 Thumbnail image credit 🤍

Spark Tutorial | Spark Tutorial for Beginners | Apache Spark Full Course - Learn Apache Spark 2020

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24.04.2020

🔥1000+ Free Courses With Free Certificates: 🤍 🔥Accelerate your Software Development career with E&ICT IIT Roorkee: 🤍 In this 'Spark Tutorial' you will comprehensively learn all the major concepts of Spark such as Spark RDD, Dataframes, Spark SQL and Spark Streaming. With the increasing size of data that generates every second, it is important to analyze this data to get important business insights in lesser time. This is where Apache Spark comes in to process real-time big data. So, keeping the importance of Spark in mind, we have come up with this full course. 🏁 Topics Covered: This 'Apache Spark Full Course' will comprise of the following topics: 00:00:00- Introduction 00:01:23 - Spark Fundamentals 00:24:00 - Spark and it's Ecosystem 00:51:22 - Spark vs Hadoop 01:08:56 - RDD Fundamentals 01:29:22 - Spark Transformations, Actions and Operations 02:36:54 - Job, Stages and Task 03:10:17 - RDD Creation 03:49:15 - Spark SQL 04:12:38 - Spark Dataframe basics 05:05:30 - Reading files of different formats 05:46:01 - Spark SQL Hive Integration 06:04:58 - Sqoop on Spark 07:08:07 - Twitter Streaming through Flume 🔥Check Our Free Courses with free certificate: 📌 Spark Basics course: 🤍 📌Spark Twitter Streaming: 🤍 📌Data Analysis using PySpark: 🤍 ⚡ About Great Learning Academy: Visit Great Learning Academy to get access to 1000+ free courses with free certificate on Data Science, Data Analytics, Digital Marketing, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity, Software Development, and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. ⚡ About Great Learning: With more than 5.4 Million+ learners in 170+ countries, Great Learning, a part of the BYJU'S group, is a leading global edtech company for professional and higher education offering industry-relevant programs in the blended, classroom, and purely online modes across technology, data and business domains. These programs are developed in collaboration with the top institutions like Stanford Executive Education, MIT Professional Education, The University of Texas at Austin, NUS, IIT Madras, IIT Bombay & more. SOCIAL MEDIA LINKS: 🔹 For more interesting tutorials, don't forget to subscribe to our channel: 🤍 🔹 For more updates on courses and tips follow us on: ✅ Telegram: 🤍 ✅ Facebook: 🤍 ✅ LinkedIn: 🤍 ✅ Follow our Blog: 🤍 #apachespark #hadooptutorial

Spark Streaming Tutorial | Spark Streaming Example | Spark Tutorial For Beginners | Simplilearn

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00:58:14
19.09.2019

This Spark streaming tutorial will help you to understand one of the major components of Apache Spark, i.e., Spark Streaming. You will learn the basics of Spark Streaming, the various data sources used in streaming, and the features of Spark Streaming. You will get an idea about discretized streams, transformations on DStreams, and how windowed stream processing works. You will also come across concepts like caching, checkpointing, and accumulators. Finally, you will see a real-time example of Spark Streaming and do a demo to count the occurrence of words in a file. Now, let's get started and learn Spark Streaming in detail. 🔥Free Big Data Hadoop Spark Developer Course: 🤍 To learn more about Spark, subscribe to our YouTube channel: 🤍 To access the slides, click here: 🤍 Watch more videos on Spark Training: 🤍 #SparkStreaming #SparkStreamingExample #SparkStreamingTutorial #ApacheSpark #ApacheSparkTutorial #SparkTutorialForBeginners #SimplilearnApacheSpark #Simplilearn This Apache Spark and Scala certification training is designed to advance your expertise working with the Big Data Hadoop Ecosystem. You will master essential skills of the Apache Spark open source framework and the Scala programming language, including Spark Streaming, Spark SQL, machine learning programming, GraphX programming, and Shell Scripting Spark. This Scala Certification course will give you vital skillsets and a competitive advantage for an exciting career as a Hadoop Developer. What is this Big Data Hadoop training course about? The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. What are the course objectives? Simplilearn’s Apache Spark and Scala certification training are designed to: 1. Advance your expertise in the Big Data Hadoop Ecosystem 2. Help you master essential Apache and Spark skills, such as Spark Streaming, Spark SQL, machine learning programming, GraphX programming and Shell Scripting Spark 3. Help you land a Hadoop developer job requiring Apache Spark expertise by giving you a real-life industry project coupled with 30 demos What skills will you learn? By completing this Apache Spark and Scala course you will be able to: 1. Understand the limitations of MapReduce and the role of Spark in overcoming these limitations 2. Understand the fundamentals of the Scala programming language and its features 3. Explain and master the process of installing Spark as a standalone cluster 4. Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark 5. Master Structured Query Language (SQL) using SparkSQL 6. Gain a thorough understanding of Spark streaming features 7. Master and describe the features of Spark ML programming and GraphX programming Who should take this Scala course? 1. Professionals aspiring for a career in the field of real-time big data analytics 2. Analytics professionals 3. Research professionals 4. IT developers and testers 5. Data scientists 6. BI and reporting professionals 7. Students who wish to gain a thorough understanding of Apache Spark Learn more at: 🤍 For more information about Simplilearn courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

Spark Word Count Example

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Spark Word Count Example Watch more Videos at 🤍 Lecture By: Mr. Arnab Chakraborty, Tutorials Point India Private Limited

Big Data Analytics using Spark with Python | PySpark Tutorial | Intellipaat

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🔥Intellipaat PySpark training: 🤍 #bigadataanalyticsusingsparkwithpython #pysparktutorial #bigdatanalayticsusingspark #python #apachespark Intellipaat is a global online professional training provider. We are offering some of the most updated, industry-designed certification training programs which includes courses in Big Data, Data Science, Artificial Intelligence and 150 other top trending technologies. We help professionals make the right career decisions, choose the trainers with over a decade of industry experience, provide extensive hands-on projects, rigorously evaluate learner progress and offer industry-recognized certifications. We also assist corporate clients to upskill their workforce and keep them in sync with the changing technology and digital landscape. 📌 Do subscribe to Intellipaat channel & get regular updates on videos: 🤍 Intellipaat Edge 1. 24*7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs 5. Industry Oriented Course ware 6. Life time free Course Upgrade For more information: Please write us to sales🤍intellipaat.com or call us at: +91-7847955955 Website: 🤍 Facebook: 🤍 Telegram: 🤍 Instagram: 🤍 LinkedIn: 🤍 Twitter: 🤍 Meetup : 🤍

Apache Kafka with Spark Streaming | Kafka Spark Streaming Examples | Kafka Training | Edureka

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21.05.2018

Kafka Online Training : 🤍 In this Kafka Spark Streaming video, we are demonstrating how Apache Kafka works with Spark Streaming. In this video, we have discussed Apache Kafka & Apache Spark briefly. Finally, we have explained the integration of Kafka & Spark Streaming. Topics covered in this Kafka Spark Streaming Tutorial video are: 1. What is Kafka? 2. Kafka Components 3. Kafka architecture 4. What is Spark? 5. Spark Component 6. Kafka Spark Integration 7. Kafka Spark Streaming Project As mentioned in the video, you can go through these Kafka & Spark videos: Kafka Tutorial: 🤍 Spark Tutorial: 🤍 Spark Streaming: 🤍 Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Kafka playlist here: 🤍 - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 40 hours of assignment and 30 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 undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka’s Apache Kafka certification training is designed to help you become a Kafka developer. During this course, our expert Kafka instructors will help you: 1. Learn Kafka and its components 2. Set up an end to end Kafka cluster along with Hadoop and YARN cluster 3. Integrate Kafka with real time streaming systems like Spark & Storm 4. Describe the basic and advanced features involved in designing and developing a high throughput messaging system 5. Use Kafka to produce and consume messages from various sources including real time streaming sources like Twitter 6. Get insights of Kafka Producer & Consumer APIs 7. Understand Kafka Stream APIs 8. Work on a real-life project, ‘Implementing Twitter Streaming with Kafka, Flume, Hadoop & Storm - - - - - - - - - - - - - - Who should go for this course? This course is designed for professionals who want to learn Kafka techniques and wish to apply it on Big Data. It is highly recommended for: Developers, who want to gain acceleration in their career as a "Kafka Big Data Developer" Testing Professionals, who are currently involved in Queuing and Messaging Systems Big Data Architects, who like to include Kafka in their ecosystem Project Managers, who are working on projects related to Messaging Systems Admins, who want to gain acceleration in their careers as a "Apache Kafka Administrator - - - - - - - - - - - - - - Why Learn Kafka? Kafka is used heavily in the Big Data space as a reliable way to ingest and move large amounts of data very quickly. ​LinkedIn, Yahoo, Twitter, Netflix, Uber, Goldman Sachs,PayPal, Airbnb​ ​​& other fortune 500 companies use Kafka. The average salary of a Software Engineer with Apache Kafka skill is $87,500 per year. (Payscale.com salary data). - - - - - - - - - - - - - For more information, Please write back to us at sales🤍edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free). Instagram: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Customer Review: Michael Harkins, System Architect, Hortonworks says: “The courses are top rate. The best part is live instruction, with playback. But my favourite 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!!! ~ This is the killer education app... I've take two courses, and I'm taking two more.”

Apache Spark - Data Partitioning Example

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14.09.2017

In this video, we will understand the data partitioning with an example.

Hadoop In 5 Minutes | What Is Hadoop? | Introduction To Hadoop | Hadoop Explained |Simplilearn

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21.01.2021

🔥Free Big Data Hadoop and Spark Developer course: 🤍 Hadoop is a famous Big Data framework; this video on Hadoop will acquaint you with the term Big Data and help you understand the importance of Hadoop. Here, you will also learn about the three main components of Hadoop, namely, HDFS, MapReduce, and YARN. In the end, we will have a quiz on Hadoop. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let's get started and learn all about Hadoop. Don't forget to take the quiz at 05:11! To learn more about Hadoop, subscribe to our YouTube channel: 🤍 Watch more videos on HadoopTraining: 🤍 #WhatIsHadoop #Hadoop #HadoopExplained #IntroductionToHadoop #HadoopTutorial #Simplilearn Big Data #SimplilearnHadoop #Simplilearn Simplilearn’s Big Data Hadoop training course lets you master the concepts of the Hadoop framework and prepares you for Cloudera’s CCA175 Big data certification. With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab. What is this Big Data Hadoop training course about? The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. What are the course objectives? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists Learn more at: 🤍 For more information about Simplilearn courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

Spark SQL Tutorial | Spark SQL Using Scala | Apache Spark Tutorial For Beginners | Simplilearn

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00:50:53
10.10.2019

This Spark SQL tutorial will help you understand what is Spark SQL, Spark SQL features, architecture, dataframe API, data source API, catalyst optimizer, running SQL queries and a demo on Spark SQL. Spark SQL is a Apache Spark's module for working with structures and semi-strcutures data. It is originated to overcome the limitations of Apache Hive. Now, let us get started and understand Spark SQL in detail. 🔥Free Big Data Hadoop Spark Developer Course: 🤍 Below topics are explained in this Spark SQL tutorial: 1. What is Spark SQL? 00:31 2. Spark SQL features 02:43 3. Spark SQL architecture 06:34 4. Spark SQL - Dataframe API 08:50 5. Spark SQL - Data source API 10:46 6. Spark SQL - Catalyst optimizer 12:02 7. Running SQL queries 29:00 8. Spark SQL demo 35:44 To learn more about Spark, subscribe to our YouTube channel: 🤍 To access the slides, click here: 🤍 Watch more videos on Spark Training: 🤍 #ApacheSparkSQL #SparkSQLUsingScala #ApacheSpark #ApacheSparkTutorial #SparkTutorialForBeginners #SimplilearnApacheSpark #Simplilearn This Apache Spark and Scala certification training is designed to advance your expertise working with the Big Data Hadoop Ecosystem. You will master essential skills of the Apache Spark open source framework and the Scala programming language, including Spark Streaming, Spark SQL, machine learning programming, GraphX programming, and Shell Scripting Spark. This Scala Certification course will give you vital skillsets and a competitive advantage for an exciting career as a Hadoop Developer. What is this Big Data Hadoop training course about? The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. What are the course objectives? Simplilearn’s Apache Spark and Scala certification training are designed to: 1. Advance your expertise in the Big Data Hadoop Ecosystem 2. Help you master essential Apache and Spark skills, such as Spark Streaming, Spark SQL, machine learning programming, GraphX programming and Shell Scripting Spark 3. Help you land a Hadoop developer job requiring Apache Spark expertise by giving you a real-life industry project coupled with 30 demos What skills will you learn? By completing this Apache Spark and Scala course you will be able to: 1. Understand the limitations of MapReduce and the role of Spark in overcoming these limitations 2. Understand the fundamentals of the Scala programming language and its features 3. Explain and master the process of installing Spark as a standalone cluster 4. Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark 5. Master Structured Query Language (SQL) using SparkSQL 6. Gain a thorough understanding of Spark streaming features 7. Master and describe the features of Spark ML programming and GraphX programming Who should take this Scala course? 1. Professionals aspiring for a career in the field of real-time big data analytics 2. Analytics professionals 3. Research professionals 4. IT developers and testers 5. Data scientists 6. BI and reporting professionals 7. Students who wish to gain a thorough understanding of Apache Spark Learn more at: 🤍 For more information about Simplilearn courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

Spark Streaming Example with PySpark | Apache SPARK Structured STREAMING TUTORIAL with PySpark

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25.07.2021

In this video we'll understand Spark Streaming with PySpark through an applied example of how we might use Structured Streaming in a real world scenario. #pyspark #streaming #databricks

Apache Spark Tutorial - 05 Data Preprocessing

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Versi bahasa Indo, beli bukunya di sini aja ya 😀 🤍 Github link: 🤍

Machine learning with Apache Spark | Machine Learning Essentials

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26.01.2021

Join Seth Juarez, Principal Cloud Developer Advocate at Microsoft, to learn how to use Azure Databricks for machine learning. Learn more: 🤍 #Microsoft #Azure

Java in Spark | Spark-Submit Job with Spark UI Example | Tech Primers

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15.05.2018

This video covers on how to create a Spark Java program and run it using spark-submit. Example code in Github: 🤍 Website: 🤍 Slack Community: 🤍 To get invite, drop a mail to info🤍techprimers.com Twitter: 🤍 Facebook: 🤍 GitHub: 🤍 or 🤍 Video Editing: iMovie Background Music: Joakim Karud Dyalla

Apache Spark SQL - running a sample program

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05.10.2015

Connect with me or follow me at 🤍 🤍 🤍 🤍 🤍

ETL With Apache Spark

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15.12.2017

Problem Statement: ETL jobs generally require heavy vendor tooling that is expensive and slow; with little improvement or support for Big Data applications. This video provides a demonstration for using Apache Spark to build robust ETL pipelines while taking advantage of open source, general purpose cluster computing. GitHub: 🤍

Apache Spark Tutorial - 09 Clustering

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27.12.2018

Versi bahasa Indo, beli bukunya di sini aja ya 😀 🤍 Github link: 🤍

Data Engineering Interview | Apache Spark Interview | Live Big Data Interview

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29.09.2020

This video is part of the Spark Interview Questions Series. A lot of subscribers has requested me to give some experience on how an actual Big Dta Interview look like. In This Video we have covered what usually happens in Big data or data engineering interview happens. There will be more videos covering different aspects of Data Engineering Interviews. Here are a few Links useful for you Git Repo: 🤍 Spark Interview Questions: 🤍 If you are interested to join our community. Please join the following groups Telegram: 🤍 Whatsapp: 🤍 You can drop me an email for any queries at aforalgo🤍gmail.com #apachespark #sparktutorial #bigdata #spark #hadoop #spark3 #bigdata #dataengineer

Apache Spark - Loading data from relational databases

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29.09.2015

Connect with me or follow me at 🤍 🤍 🤍 🤍 🤍

Master Databricks and Apache Spark Step by Step: Lesson 1 - Introduction

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In this first lesson, you learn about scale-up vs. scale-out, Databricks, and Apache Spark. This video lays the foundation of the series by explaining what Apache Spark and Databricks are. The series will take you from Padawan to Jedi Knight! Join me! Join my Patreon Community 🤍 Twitter: 🤍BryanCafferky Slides and Other Content when Applicable available at: 🤍

Apache Spark RDD Operations - Transformations (With Demonstration)

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09.11.2018

Spark Transformation is a function that produces new RDD from the existing RDDs. It takes RDD as input and produces one or more RDD as output.

Apache Spark Tutorial | Spark tutorial | Python Spark

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05.06.2018

Access this full Apache Spark course on Level Up Academy: 🤍 This Apache Spark Tutorial covers all the fundamentals about Apache Spark with Python and teaches you everything you need to know about developing Spark applications using PySpark, the Python API for Spark. Apache Spark Tutorial | Spark tutorial | Apache tutorial Access this full Apache Spark course on Level Up Academy: 🤍 At the end of this Apache Spark Tutorial, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipeline and data analytics applications. Apache Spark Tutorial | Spark tutorial | Apache tutorial This Apache Spark Tutorial covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom. And much much more. Access this full Apache Spark course on Level Up Academy: 🤍 Apache Spark Tutorial | Spark tutorial | Apache tutorial What will you learn from this Apache Spark Tutorial: In particularly, you will learn: An overview of the architecture of Apache Spark. Develop Apache Spark 2.0 applications with PySpark using RDD transformations and actions and Spark SQL. Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets. Deep dive into advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs. Scale up Spark applications on a Hadoop YARN cluster through Amazon's Elastic MapReduce service. Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Spark SQL. Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators. Best practices of working with Apache Spark in the field. Big data ecosystem overview. Apache Spark Tutorial | Spark tutorial | Apache tutorial

Apache Spark Struct Type Field Transformation - Spark Real Time Use Case | Using PySpark

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15.10.2022

#bigdata #apachespark #databricks Apache Spark Struct Type Field Transformation - Spark Real Time Use Case | Using PySpark In this video, we will understand how to add, Remove or Cast a column in Spark Dataframe of Struct Type. We will use PySpark for this demo. Code Snippet and Sample Dataset: 🤍 Blog link to learn more on Spark: 🤍learntospark.com Linkedin profile: 🤍 FB page: 🤍

Introduction to Apache Spark GraphX

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23.11.2018

Learn the basics of Spark GraphX

Apache Spark Job On yarn cluster using docker container with an example

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20.02.2021

This video explains how to submit Apache Spark Job On yarn cluster using docker container with an example If you like this video from my channel please subscribe to the link: 🤍 Docker config - docker network create -d bridge hadoopspark docker run name namenode network=hadoopspark -v "D:/PROJECTS/hadoopspark:/opt/hadoopspark" -e "CORE_CONF_fs_defaultFS=hdfs://namenode:9000" -e "CLUSTER_NAME=hadooptest" -p 9870:9870 -p 9000:9000 -d bde2020/hadoop-namenode docker run name datanode network=hadoopspark -e "CORE_CONF_fs_defaultFS=hdfs://namenode:9000" -d bde2020/hadoop-datanode docker run name resourcemanager hostname resourcemanager -e "CORE_CONF_fs_defaultFS=hdfs://namenode:9000" network=hadoopspark -v "D:/PROJECTS/hadoopspark:/opt/hadoopspark" -p 8088:8088 -d bde2020/hadoop-resourcemanager docker run name nodemanager network=hadoopspark -e "CORE_CONF_fs_defaultFS=hdfs://namenode:9000" -e "YARN_CONF_yarn_resourcemanager_hostname=resourcemanager" -v "D:/PROJECTS/hadoopspark:/opt/hadoopspark" -d bde2020/hadoop-nodemanager export HADOOP_CONF_DIR=/opt/hadoop-3.2.1/etc/hadoop ./spark-submit class test.spark.ArrivalDelay master yarn deploy-mode cluster driver-memory 2g executor-memory 2g executor-cores 2 /opt/hadoopspark/airlinecarriersjoin.jar

Getting Started with Apache Spark | Spark Project in Intellij | Spark Scala Program For Beginner

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00:21:44
19.09.2021

This video shows how to create a Spark Scala program in Intellij IDEA . Project name : Average number of Friends by Age 00:16 Step 1 : Project Description Download fakefriends.csv from this link: 🤍 02:12 Step 2 : Create New Spark Scala Project in Intelli 04:40 Step 3 : Configure bulit.sbt built.sbt configuaration : name := "SparkFriendsAge" version := "0.1" scalaVersion := "2.12.10" libraryDependencies = Seq( "org.apache.spark" %% "spark-core" % "3.1.2", "org.apache.spark" %% "spark-sql" % "3.1.2" ) 06:25 Step 4 : Create Scala Object Class and Write Spark Scala Codes You can also download FriendsByAge.scala from this link : 🤍 20:08 Step 5 : Run the Project

Apache Spark RDD operations : Transformations and Actions

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14.04.2017

Official Website: 🤍 RDD operations There are 2 operations that can be applied on RDD. One is transformation. 1) Transformation = Transformation is what you do to an RDD to get another resultant RDD. The example would be to apply functions like filter, union , that would then create another resultant RDD. FILTER is a transformation that when applied on an RDD, will isolate certain elements and create a new RDD. This combining of elements from 2 RDD be done using UNION transformation. UNION is a multi-RDD transformation, which means it acts on more than one RDD. 2) Actions = Actions are second type of operations in RDD. Actions return a result to the driver program , or write it in a storage and kick off a computation. some examples are count , first, collect, take count action can be used to get the number of elements in an RDD. first action can be used to retrieve the first element in the RDD. - take action can be used to retrieve n elements out of the RDD. collect action can be used to retrieve the complete list of elements - from the RDD.

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