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What Is Apache Spark?

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21.10.2022

Learn more about Apache Spark → 🤍 Check out IBM Analytics Engine → 🤍 Unboxing the IBM POWER E1080 Server → 🤍 Do you have a big data problem? Too much data to process or queries that are too costly to run in a reasonable amount of time? Spare your wallet and stress levels! David Adeyemi introduces Apache Spark. It may save you a hardware upgrade or testing your patience waiting for a SQL query to finish. Get started for free on IBM Cloud → 🤍 Subscribe to see more videos like this in the future → 🤍

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 🤍

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: 🤍

What exactly is Apache Spark? | Big Data Tools

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13.07.2021

What is Apache spark? And how does it fit into Big Data? How is it related to hadoop? We'll look at the architecture of spark, learn some of the key components, see how it related to other big data tools like hadoop. ⏯RELATED VIDEOS⏯ Building a Data Pipeline: 🤍 Data Podcast ►► 🤍 Website ►► 🤍 🎓Data courses (Not Produced by nullQueries)🎓 Azure Data Engineering: 🤍 DE Essentials, hands on: 🤍 📷VIDEO GEAR📷 Programming Mouse: 🤍 Lighting: 🤍 RGB light: 🤍 USB Microphone: 🤍 Mixer: 🤍 XLR Microphone: 🤍 💻VIDEO SOFTWARE💻 music/stock: 🤍 For business inquiries please contact nullQueries🤍gmail.com Some of the links in this description are affiliate links and support the channel. Thanks for the support! 00:00 Intro 00:25 History 00:44 Goals 00:58 Architecture 02:22 Libraries 02:57 Platforms 02:57 Comparisons

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

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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 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).

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 / PySpark Tutorial: Basics In 15 Mins

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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

What Is Apache Spark | Apache Spark Tutorial For Beginners | Simplilearn

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24.10.2017

Apache Spark is an open-source cluster-computing framework. 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. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance. 🔥Free Big Data Hadoop Spark Developer Course: 🤍 Big Data Hadoop and Spark Developer Certification Training: 🤍 #bigdata #bigdatatutorialforbeginners #bigdataanalytics #bigdatahadooptutorialforbeginners #bigdatatutorial #bigdatahadoop #bigdataanalyticstutorial 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 Hadoop and related tools: The course provides you with an in-depth understanding of the Hadoop framework including HDFS, YARN, and MapReduce. You will learn to use Pig, Hive, and Impala to process and analyze large datasets stored in the HDFS, and use Sqoop and Flume for data ingestion. 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 for creating, transforming, and querying data form. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-commerce. This Big Data course also prepares you for the Cloudera CCA175 certification. 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 16. Prepare for Cloudera Big Data CCA175 certification Who should take this 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 9. Graduates looking to build a career in Big Data Analytics For more updates on courses and tips follow us on: - Facebook : 🤍 - Twitter: 🤍 Get the android app: 🤍 Get the iOS app: 🤍

Spark Full Course | Spark Tutorial For Beginners | Learn Apache Spark | Simplilearn

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18.05.2021

This Apache Spark full course will help you learn the basics of Big Data, what Apache Spark is, and the architecture of Apache Spark. Then, you will understand how to install Apache Spark on Windows and Ubuntu. You will look at the important components of Spark, such as Spark Streaming, Spark MLlib, and Spark SQL. Finally, you will get an idea about implement Spark with Python in PySpark tutorial and look at some of the important Apache Spark interview questions. 🔥Free Big Data Hadoop & Spark Developer Course: 🤍 Below topics are explained in this Apache Spark Full Course: 00:00:00 What is Apache Spark 00:39:07 Spark Installation on windows 01:09:58 Spark Installation on ubuntu 01:26:46 Apache Spark Architecture 01:48:34 Spark case study 02:24:11 Spark Streaming 03:22:27 Spark SQL 04:12:15 Spark MLlib 05:27:02 Understanding PySpark 06:25:53 Apache Spark Interview Questions To learn more about Spark, subscribe to our YouTube channel: 🤍 Watch more videos on Spark Training: 🤍 #ApcheSparkFullCourse #ApcheSparkTutorial #SparkTutorialForBeginners #Learn ApacheSpark #LearnApacheSparkIn7Hours #SparkArchitecture #ApacheSpark #ApacheSparkTutorial #WhatIsApacheSpark #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 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 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 Learn more at: 🤍 🔥Free Big Data Hadoop & Spark Developer Course: 🤍 For more information about Simplilearn’s courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 - Instagram: 🤍 - Telegram Mobile: 🤍 - Telegram Desktop: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

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

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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 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

What is Apache Spark?

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19.11.2018

See Matei Zaharia, one of the original creators of Apache Spark from Databricks discuss what is Apache Spark. 🤍 About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: 🤍 Connect with us: Website: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. 🤍

What is Apache Spark

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00:02:46
05.10.2020

Official Website: 🤍 Apache spark is an 1. Open source 2. Fast 3. In-memory data processing engine 4. University of California, Berkeley’s AMPLab; Apache software foundation 5. Development APIs 6. Less lines of code 7. Use cases 8. Data sources 9. File formats 10. Runs on cluster

Apache Spark Architecture | Apache Spark Architecture Explained | Apache Spark Tutorial |Simplilearn

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00:47:42
08.08.2019

This video on Spark Architecture will give an idea of what is Apache Spark, the essential features in Spark, and the different Spark components. You will learn about Spark Core, Spark SQL, Spark Streaming, Spark MLlib, and Graphx. You will understand how Spark processes an application. Finally, you will perform a demo on Apache Spark. 🔥Free Big Data Hadoop Spark Developer Course: 🤍 Below are the topics covered in this Apache Spark Architecture Video: 0:00​ Start 0:30 What is Apache Spark? 3:30 Spark Components 5:54 Spark Core 6:36 Spark RDD 10:18 Spark SQL 17:36 Spark Streaming 22:01 Spark MLlib 23:49 GraphX 25:38 Spark Architecture 30:40 Running a Spark Application 41:45 How a Spark application runs on a cluster? To learn more about Spark, subscribe to our YouTube channel: 🤍 To access the slides, click here: 🤍 Watch more videos on Spark Training: 🤍 #SparkArchitecture #SparkArchitectureExplained #ApacheSparkArchitecture #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: 🤍

Apache Spark Full Course | Apache Spark Tutorial For Beginners | Learn Spark In 7 Hours |Simplilearn

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🔥Free Big Data Hadoop & Spark Developer Course: 🤍 This Simplilearn video on Apache Spark Full Course will help you learn the basics of Big Data, what Apache Spark is, and the architecture of Apache Spark. Here you will learn Spark in 7 hours. You will look at Spark installation, Spark Streaming, Spark MLlib, Spark SQL, and PySpark. Finally, you will also go through the top Apache Spark interview questions. Now, let's get started with this Apache Spark tutorial for beginners! Below topics are explained in this Apache Spark Full Course: 1. Introduction 00:00 2. History of Spark 06:48 3. What is Spark 07:28 4. Hadoop vs spark 08:32 5. Components of Apache Spark 14:14 6. Spark Architecture 33:26 7. Applications of Spark 40:05 8. Spark Use Case 42:08 9. Running a Spark Application 44:08 10. Apache Spark installation on Windows 01:01:03 11. Apache Spark installation on Ubuntu 01:31:54 12. What is Spark Streaming 01:49:31 13. Spark Streaming data sources 01:50:39 14. Features of Spark Streaming 01:52:19 15. Working of Spark Streaming 01:52:53 16. Discretized Streams 01:54:03 17. caching/persistence 02:02:17 18. checkpointing in spark streaming 02:04:34 19. Demo on Spark Streaming 02:18:27 20. What is Spark MLlib 02:47:29 21. What is Machine Learning 02:49:14 22. Machine Learning Algorithms 02:51:38 23. Spark MLlib Tools 02:53:01 24. Spark MLlib Data Types 02:56:42 25. Machine Learning Pipelines 03:09:05 26. Spark MLlib Demo 03:18:38 27. What is Spark SQL 04:01:40 28. Spark SQL Features 04:03:52 29. Spark SQL Architecture 04:07:43 30. Spark SQL Data Frame 04:09:59 31. Spark SQL Data Source 04:11:55 32. Spark SQL Demo 04:23:00 33. What is PySpark 04:52:03 34. PySpark Features 04:58:02 35. PySpark with Python and Scala 04:58:54 36. PySpark Contents 05:00:35 37. PySpark Subpackages 05:40:10 38. Companies using PySpark 05:41:16 39. PySpark Demo 05:41:49 40. Spark Interview Questions 05:50:43 To learn more about Spark, subscribe to our YouTube channel: 🤍 Watch more videos on Spark Training: 🤍 #ApcheSparkFullCourse #ApcheSparkTutorial #SparkTutorialForBeginners #Learn ApacheSpark #LearnApacheSparkIn7Hours #SparkArchitecture #ApacheSpark #ApacheSparkTutorial #WhatIsApacheSpark #SimplilearnApacheSpark #Simplilearn 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. Simplilearn's 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. 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 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 Learn more at: 🤍 For more information about Simplilearn courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

Making Apache Spark™ Better with Delta Lake

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15.09.2020

Join Michael Armbrust, head of Delta Lake engineering team, to learn about how his team built upon Apache Spark to bring ACID transactions and other data reliability technologies from the data warehouse world to cloud data lakes. Apache Spark is the dominant processing framework for big data. Delta Lake adds reliability to Spark so your analytics and machine learning initiatives have ready access to quality, reliable data. This webinar covers the use of Delta Lake to enhance data reliability for Spark environments. Topics areas include: - The role of Apache Spark in big data processing - Use of data lakes as an important part of the data architecture - Data lake reliability challenges - How Delta Lake helps provide reliable data for Spark processing - Specific improvements improvements that Delta Lake adds - The ease of adopting Delta Lake for powering your data lake See full Getting Started with Delta Lake tutorial series here: 🤍 Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. 🤍

Apache Spark in 60 Seconds

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Learn more about Apache Spark→ 🤍 Get started for free on IBM Cloud → 🤍 Subscribe to see more videos like this in the future → 🤍

Advanced Apache Spark Training - Sameer Farooqui (Databricks)

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Live Big Data Training from Spark Summit 2015 in New York City. "Today I'll cover Spark core in depth and get you prepared to use Spark in your own prototypes. We'll start by learning about the big data ecosystem, then jump into RDDs (Resilient Distributed Datasets). Then we'll talk about integrating Spark with resource managers like YARN and Standalone mode. After a peek into some Spark Internals, we touch base upon Accumulators and Broadcast Variables. Finally, we end with Spark Streaming and a technical explanation of how the 100 TB sort competition was won in 2014." - Sameer Slides: 🤍 Want to learn more about Spark? Check out my new class, "Exploring Wikipedia with Apache Spark", recorded June 2016: 🤍 // About the Presenter // Sameer Farooqui is a Technology Evangelist at Databricks where he helps promote the adoption of Apache Spark. As a founding member of the training team, he created and taught advanced Spark classes at private clients, meetups and conferences globally. Follow Sameer on - Twitter: 🤍 LinkedIn: 🤍

Apache Spark in 10 Minutes | What is Apache Spark? | Learn Apache Spark

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27.11.2020

Spark Programming and Azure Databricks ILT Master Class by Prashant Kumar Pandey - Fill out the google form for Course inquiry. 🤍 - Data Engineering using is one of the highest-paid jobs of today. It is going to remain in the top IT skills forever. Are you in database development, data warehousing, ETL tools, data analysis, SQL, PL/QL development? I have a well-crafted success path for you. I will help you get prepared for the data engineer and solution architect role depending on your profile and experience. We created a course that takes you deep into core data engineering technology and masters it. If you are a working professional: 1. Aspiring to become a data engineer. 2. Change your career to data engineering. 3. Grow your data engineering career. 4. Get Databricks Spark Certification. 5. Crack the Spark Data Engineering interviews. ScholarNest is offering a one-stop integrated Learning Path. The course is open for registration. The course delivers an example-driven approach and project-based learning. You will be practicing the skills using MCQ, Coding Exercises, and Capstone Projects. The course comes with the following integrated services. 1. Technical support and Doubt Clarification 2. Live Project Discussion 3. Resume Building 4. Interview Preparation 5. Mock Interviews Course Duration: 6 Months Course Prerequisite: Programming and SQL Knowledge Target Audience: Working Professionals Batch start: Registration Started Fill out the below form for more details and course inquiries. 🤍 Learn more at 🤍 Best place to learn Data engineering, Bigdata, Apache Spark, Databricks, Apache Kafka, Confluent Cloud, AWS Cloud Computing, Azure Cloud, Google Cloud - Self-paced, Instructor-led, Certification courses, and practice tests. SPARK COURSES - 🤍 🤍 🤍 🤍 🤍 KAFKA COURSES 🤍 🤍 🤍 AWS CLOUD 🤍 🤍 PYTHON 🤍 We are also available on the Udemy Platform Check out the below link for our Courses on Udemy 🤍 = You can also find us on Oreilly Learning 🤍 🤍 🤍 🤍 🤍 🤍 🤍 🤍 = Follow us on Social Media 🤍 🤍 🤍 🤍 🤍 🤍

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 Introduction

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Apache Spark Introduction {தமிழ்} Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Video Playlist - Hadoop in Tamil - 🤍 Hadoop in English - 🤍 Spark in Tamil - 🤍 Spark in English - 🤍 Hive in Tamil - 🤍 Hive in English - 🤍 Data Engineering in Tamil - 🤍 Data Engineering in English - 🤍 Batch vs Stream processing Tamil - 🤍 Batch vs Stream processing English - 🤍 NOSQL in English - 🤍 NOSQL in Tamil - 🤍 Scala in Tamil: 🤍 Scala in English: 🤍 Email : atozknowledge.com🤍gmail.com LinkedIn : 🤍 Instagram : 🤍 YouTube channel link 🤍youtube.com/atozknowledgevideos Website 🤍 Technology in Tamil & English #spark #apachespark #bigdata

Introducing Amazon Athena for Apache Spark | Amazon Web Services

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Amazon Athena enables you to get started with interactive analytics on Apache Spark in under a second. Athena’s serverless, fully managed model eliminates any planning, configuring, or managing resources for your workloads. Interactive Spark applications start instantly under a second and run faster with our optimized Spark runtime, so you spend more time on insights, not waiting for results. Learn more at 🤍 Subscribe: More AWS videos - 🤍 More AWS events videos - 🤍 ABOUT AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster. #AWS #AmazonWebServices #CloudComputing

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

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18.02.2017

( Apache Spark Training - 🤍 ) This Edureka Spark Tutorial (Spark Blog Series: 🤍 will help you to understand all the basics of Apache Spark. This Spark tutorial is ideal for both beginners as well as professionals who want to learn or brush up Apache Spark concepts. Below are the topics covered in this tutorial: 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. PG in Big Data Engineering with NIT Rourkela : 🤍 (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) #edureka #edurekaSpark #SparkTutorial #SparkOnlineTraining 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: 🤍 Telegram: 🤍 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.”

15分钟入门Apache Spark

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简单介绍Apache Spark。 无需本地安装任何东西。介绍RDD和Data Frame的基本操作。 Example Link: 🤍

Hadoop vs Spark | Hadoop And Spark Difference | Hadoop And Spark Training | Simplilearn

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06.12.2019

🔥 Enroll for FREE Big Data Hadoop Spark Course & Get your Completion Certificate: 🤍 Hadoop and Spark are the two most popular big data technologies used for solving significant big data challenges. In this video, you will learn which of them is faster based on performance. You will know how expensive they are and which among them is fault-tolerant. You will get an idea about how Hadoop and Spark process data, and how easy they are for usage. You will look at the different languages they support and what's their scalability. Finally, you will understand their security features, which of them has the edge over machine learning. Now, let's get started with learning Hadoop vs. Spark. We will differentiate based on below categories 1. Performance 00:52 2. Cost 01:40 3. Fault Tolerance 02:31 4. Data Processing 03:06 5. Ease of Use 04:03 6. Language Support 04:52 7. Scalability 05:55 8. Security 06:38 9. Machine Learning 08:02 10. Scheduler 08:56 To learn more about Hadoop, subscribe to our YouTube channel: 🤍 To access the slides, click here: 🤍 Watch more videos on HadoopTraining: 🤍 #HadoopvsSpark #HadoopAndSpark #HadoopAndSparkDifference #DifferenceBetweenHadoopAndSpark #WhatIsHadoop #WhatIsSpark #LearnHadoop #HadoopTraining #SparkTraining #HadoopCertification #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 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: 🤍

Apache Spark - Capítulo 1. ¿Qué es Apache Spark?

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04.11.2021

Ponente: Daniel Portugal Revilla LinkedIn: 🤍 Capítulo 1. ¿Qué es Apache Spark? Apache Spark es un motor informático unificado y un conjunto de librerías para el procesamiento de datos en paralelo en clústeres de computadoras. En el momento de escribir este artículo, Spark es el motor de código abierto más desarrollado para esta tarea, lo que lo convierte en una herramienta estándar para cualquier desarrollador o científico de datos interesado en big data. Spark admite múltiples lenguajes de programación ampliamente utilizados (Python, Java, Scala y R), incluye bibliotecas para diversas tareas que van desde SQL hasta streaming y machine learningo, y se ejecuta en cualquier lugar, desde una computadora portátil hasta un clúster de miles de servidores. # Acerca del libro Título: Spark: The Definitive Guide Apache Spark es actualmente uno de los sistemas más populares para el procesamiento de datos a gran escala, con API en múltiples lenguajes de programación y una gran cantidad de bibliotecas integradas y de terceros. Aunque el proyecto ha existido durante varios años, primero como un proyecto de investigación que comenzó en UC Berkeley en 2009, luego en la Apache Software Foundation desde 2013, la comunidad de código abierto continúa creando API más potentes y bibliotecas de alto nivel sobre Spark, por lo que todavía hay mucho que escribir sobre el proyecto. - ¿Te gustaría compartir y aprender sobre SQL, Bases de datos, Big Data, Cloud, R, Oracle, SQL Server, Hadoop, Hive, Spark, Databricks, Delta Lake, git, Airflow, Apache Hudi, Apache Beam, DVC, lakeFS, Flink, AWS, GCP, Azure, Presto/Trino, Snowflake, Ingeniería de Datos, Machine Learning, MLOps, Data Management, etc con más entusiastas por los datos así como tú? 📣Únete a la comunidad Data Engineering LATAM en las distintas redes que tenemos 🤍 📺 YouTube: 🤍 📈 Linkedin: 🤍 📸 Instagram: 🤍 👍 Facebook: 🤍 🐦 Twitter: 🤍 ✉ Telegram: 🤍 📚 Slack: 🤍 Grupos de Estudios: 🎤 English Speaking and stuff 🎤 DAMA's Study Group (Data Management) 🎤 Databricks Certified Associate 🎤 Apache Airflow Study Club 🎤 Power BI como debe ser 🎤 Club de Lectura / Designing data-intensive Applications 🐗 🎤¿Quieres dar charla en la comunidad? 🤍 💌Suscríbete a este canal con el botón rojo que está debajo de los videos y pulsa la campana para que te notifique de las novedades. 📢 ¡Pasa la voz y ayúdanos a ser la comunidad más grande y chévere de todas!

Apache Spark Interview Questions And Answers | Apache Spark Interview Questions 2020 | Simplilearn

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16.01.2020

This Simplilearn video on Apache Spark interview questions and answers will acquaint you with all the important Spark questions that will help you crack an interview. We will cover questions on various topics like Spark Streaming, Spark MLlib, Spark SQL, and GraphX to name a few. So, let's get started! 🔥Free Big Data Hadoop Spark Developer Course: 🤍 The topics covered in this video on Spark Interview Questions are: 1. Introduction to Spark Interview Questions: 00:00 2. Generic Spark Questions 00:21 3. Spark Core Questions 19:40 4. Spark Streaming Questions 26:01 5. Spark MLlib Questions 36:42 6. Spark SQL Questions 42:43 7. Spark GraphX Questions 46:51 To learn more about Spark, subscribe to our YouTube channel: 🤍 To access the slides, click here: 🤍 Watch more videos on Spark Training: 🤍 #SparkInterviewQuestions #SparkInterviewQuestionsAndAnswers #ApacheSparkInterviewQuestions #ApacheSpark #ApacheSparkTutorial #WhatIsApacheSpark #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: 🤍

A Tale of Three Apache Spark APIs: RDDs, DataFrames, and Datasets - Jules Damji

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30.10.2017

"Of all the developers' delight, none is more attractive than a set of APIs that make developers productive, that are easy to use, and that are intuitive and expressive. Apache Spark offers these APIs across components such as Spark SQL, Streaming, Machine Learning, and Graph Processing to operate on large data sets in languages such as Scala, Java, Python, and R for doing distributed big data processing at scale. In this talk, I will explore the evolution of three sets of APIs-RDDs, DataFrames, and Datasets-available in Apache Spark 2.x. In particular, I will emphasize three takeaways: 1) why and when you should use each set as best practices 2) outline its performance and optimization benefits; and 3) underscore scenarios when to use DataFrames and Datasets instead of RDDs for your big data distributed processing. Through simple notebook demonstrations with API code examples, you'll learn how to process big data using RDDs, DataFrames, and Datasets and interoperate among them. (this will be vocalization of the blog, along with the latest developments in Apache Spark 2.x Dataframe/Datasets and Spark SQL APIs: 🤍 🤍 Session hashtag: #EUdev12" About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: 🤍 Connect with us: Website: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. 🤍

Vidéo présentation d’Apache Spark - Vidéo Tuto

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00:04:17
10.08.2020

Une Vidéo présentation d’Apache Spark ✅ Suivez la formation complète du Big Data avec Apache Spark : ▶ 🤍 ➖➖➖➖➖➖➖ C’est quoi le Big Data ? Le big Data signifie mégadonnées, grosses données ou encore données massives. Il désigne un ensemble très volumineux de données qu’aucun outil classique de gestion de base de données ou de gestion de l’information ne peut vraiment travailler. En effet, nous procréons environ 2,5 trillions d’octets de données tous les jours. Ce sont les informations provenant de partout : messages que nous nous envoyons, vidéos que nous publions, informations climatiques, signaux GPS, enregistrements transactionnels d’achats en ligne et bien d’autres encore. Ces données sont baptisées Big Data ou volumes massifs de données. Les géants du Web, au premier rang desquels Yahoo (mais aussi Facebook et Google), ont été les tous premiers à déployer ce type de technologie. C'est quoi Apache Spark ? Spark est actuellement le projet open source le plus actif sous la plate-forme Apache Software Foundation (ASF). Il est aussi l'un des projets open source de big data le plus actif. Spark permet aux développeurs de créer un traitement de données complexe en plusieurs étapes routines, fournissant une API de haut niveau et un cadre tolérant aux pannes qui permet aux programmeurs à se concentrer sur la logique plutôt que sur les problèmes d'infrastructure ou d'environnement comme une défaillance matérielle par exemple. Dans cette formation vous allez vous familiariser avec les principes fondamentaux de Spark en utilisant le langage Scala. Spark est écrit en Scala. Il fonctionne en Java virtuel machines (JVM). Vous allez maitriser l’utilisation MapReduce avec Spark qui est une alternative à l'utilisation traditionnelle MapReduce sur Hadoop. L’utilisation de MapReduce avec Hadoop a été jugé inadaptée aux requêtes interactives ou temps réel, avec une faible latence applications. Un inconvénient majeur de l'implémentation MapReduce de Hadoop était sa persistance des données intermédiaires sur le disque entre le Map et le Reduce en phases de traitement. Dans cette formation vous allez apprendre à implémenter une structure distribuée, tolérante aux pannes et in-memory appelée Resilient Distributed Dataset (RDD). Vous allez également apprendre à traiter les données non structurées. Dans le chapitre de Spark SQL les notions des DataFrame et DataSet ne seront plus un secret pour vous. Vous avez surement entendu parler du traitement des données qui arrivent en temps réel, ce qu’on appelle le Streaming. Un chapitre bien détaillé vous attend afin que vous puissiez monter en compétence rapidement avec Spark Streaming. ➖➖➖➖➖➖➖ Abonnez-vous à la chaîne : ▶ 🤍 ➖➖➖➖➖➖➖ ✳️ Le plan de la formation Big Data avec Apache Spark : 1. Introduction de la formation 2. Le Big Data 3. Apache Hadoop 4. Apache Spark 5. Scala avec Apache Spark 6. RDD - Resilient Distributed Dataset 7. Spark SQL 8. Spark Streaming 9. Conclusion La formation complète du Big Data avec Apache Spark : ▶ 🤍 ➖➖➖➖➖➖➖ Playlist des vidéos du Big Data avec Apache Spark: ▶ 🤍 ➖➖➖➖➖➖➖ 🔵 Restez connecté-e : Alphorm Formations ▶ 🤍 YouTube ▶ 🤍 LinkedIn ▶ 🤍 Twitter ▶ 🤍 Facebook ▶ 🤍 Quora ▶ 🤍 #BigData #ApacheSpark #FormationBigData #apachehadoop #sparksql

Обработка больших данных при помощи Apache Spark ч1 | Технострим

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15.06.2017

Мероприятие: Moscow Data Science Junior Meetup, 10.06.2017 Выступающий: Виталий Худобахшов, Одноклассники Apache Spark сегодня является одной из самых популярных технологий обработки больших данных в первую очередь за счет очень удобного API, который близок к обычному функциональному стилю программирования на Scala. Спикер расскажет, что такое Spark и как с ним работать. Рассмотрит некоторые паттерны использования Spark. И, конечно, расскажет, что такое большие данные с практической точки зрения. В качестве основных примеров разберет, как определить пол и возраст пользователя в социальной сети, если он указан с ошибкой. На этих примерах станет понятно, что можно узнать просто с помощью правильной обработки данных, даже не используя машинное обучение. Календарь событий: 🤍 О КАНАЛЕ: Официальный канал образовательных проектов Mail.Ru Group ► Нажмите здесь для подписки ‣ 🤍 Актуальные лекции и мастер-классы о программировании от лучших IT-специалистов. Если вы увлечены мобильной и веб-разработкой, присоединяйтесь! Наши проекты: Технопарк при МГТУ им. Баумана ‣ 🤍 Техносфера при МГУ им. Ломоносова ‣ 🤍 Технотрек при МФТИ ‣ 🤍 Техноатом при МИФИ - 🤍 Технополис при СПбПУ - 🤍 МЫ В СЕТИ: Технопарк в ВК | 🤍 Техносфера в ВК | 🤍 Технотрек в ВК | 🤍 Техноатом в ВК | 🤍 Технополис в ОК: 🤍 Технополис в ВК: 🤍 Блог на Хабре | 🤍

DATALEARN | DE - 101 | МОДУЛЬ 7-2 ЧТО ТАКОЕ APACHE SPARK

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13.06.2022

Apache Spark является самый популярным инструментом среди инженеров данных, аналитиков и инженеров машинного обучения. Его главная задача это обработка данных. С помощью Spark можно подключаться к любому источнику данных, читать большие данные и обрабатывать их в оперативной памяти с использованием распределенного вычисления (distributed computing). В этом видео: 📌 Узнаем история Apache Spark 📌 Посмотрим примеры архитектур с использованием Spark 📌 Разберемся когда его можно использовать 📌 Узнаем про основные компоненты 📌 Узнаем, обозначает термин Unified Analytics В 7м модуле мы познакомимся с open source решением для аналитики и инжиниринга данных - Apache Spark и его коммерческой версией Databricks. Вы узнаете примеры использования в индустрии и популярные use cases. Я расскажу о своем опыте с Apache Spark в Амазоне и Майкрософт и научу вас работать с данными с помощью PySpark и Spark SQL, покажу вам лучшие книги и материалы по Spark. В этом видео еще узнаете про Whistler, BC;) 🔔 Подписывайтесь на канал "Datalearn" чтобы не пропустить остальные части и ставьте лайки! 📕 Записывайтесь и проходите курс Инженера Данных. ⚠️ КУРС БЕСПЛАТНЫЙ! 🔗 Записаться вы можете на нашем портале 🤍 👍🏻 Запись на курс даст вам возможность не только просматривать видео, но и получить доступ к закрытым материалам, а также возможность выполнять домашние задания и получить сертификат прохождения курса. 🔥Самые актуальные новости про аналитику в Telegram канале: 🤍

Spark Architecture in 3 minutes| Spark components | How spark works

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12.04.2021

Spark is one of the most prominent and widely used processing framework in Bigdata world. This videos explains the core components and architecture of spark with a real world example in just 3 minutes.

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: 🤍

How Apache Spark Works

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15.11.2013

🤍 Erich Nachbar talks to Stefan Groschupf about what Apache Spark is and how it works. Nachbar also discusses why he uses MapR. Watch the whole discussion at 🤍

Что такое Apache Spark

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21.06.2020

В данном видео мы знакомимся с фреймворком для параллельной обработки данных Apache Spark. На конкретном примере разбираем возможности Apache Spark по работе с источниками данных (файлами и RDBMS), трансформации данных (как с помощью Structured API, так на Spark SQL). Курс проводится только в специализированном учебном центре «Школа Больших Данных» По вопросам обучения на курсах машинного обучения приглашаем в нашу «Школа Больших Данных» Обращаться по телефону: +7 (495) 41-41-121 +7 (995) 100-45-63 Чтобы не пропустить информацию о новых курсах, акциях и других событиях Школы Больших Данных, рекомендуем подписаться на нас в социальных сетях: Телеграм-канал: 🤍 Facebook: 🤍 Вконтакте: 🤍 LinkedIn: 🤍 Twitter: 🤍 Подписывайтесь и будьте в курсе всех интересных новинок мира Big Data вместе со Школой больших данных - 🤍

МИТАП "Apache Spark за 2 часа - для нетерпеливых"_20 апреля 2022г

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02:36:23
20.04.2022

По вопросам обучения на курсах по технологиям больших данных приглашаем в нашу "Школу Больших Данных" Обращаться по телефону: +7 (495) 41-41-121 +7 (995) 100-45-63 Чтобы не пропустить информацию о новых курсах, акциях и других событиях Школы Больших Данных, рекомендуем подписаться на нас в социальных сетях: Телеграм-канал: 🤍 Вконтакте: 🤍 LinkedIn: 🤍 Twitter: 🤍 Подписывайтесь и будьте в курсе всех интересных новинок мира Big Data вместе со Школой больших данных - 🤍

ВВЕДЕНИЕ В PYSPARK И SPARKSQL / ОЛЕГ АГАПОВ

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02:52:51
10.08.2021

На вебинаре хочу рассказать про появление Apache Spark, его применение в современном стеке дата-инструментов, а также на практике показать как запустить Spark на своём компьютере и написать первый ETL пайплайн! 🔔 План: 📌 Как и почему появился Apache Spark 📌 Какие задачи решает 📌 Основные концепции 📌 Практика 1 – установка и запуск PySpark локально 📌 SparkSQL API 📌 Практика 2 – делаем ETL в PySpark 📌 Q&A 🔔 Подписывайтесь на канал "Datalearn" чтобы не пропустить новые видео и ставьте лайки! 📕 Записывайтесь и проходите курс Инженера Данных. ⚠️ КУРС БЕСПЛАТНЫЙ! 🔗 Записаться вы можете на нашем портале 🤍 👍🏻 Запись на курс даст вам возможность не только просматривать видео, но и получить доступ к закрытым материалам, а также возможность выполнять домашние задания, отдавать их на проверку и получить сертификат прохождения курса.

Apache Spark™ ML and Distributed Learning (1/5)

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00:06:55
11.01.2019

Unlock the full self-paced class from Databricks Academy! Introduction to Data Science and Machine Learning (AWS Databricks) 🤍 Introduction to Data Science and Machine Learning (Azure Databricks) 🤍 In this video, Conor Murphy introduces the core concepts of Machine Learning and Distributed Learning, and how Distributed Machine Learning is done with Apache Spark. He also sets up the goal of the entire video series: building an end-to-end machine learning pipeline using Databricks. Download the code here: 🤍 Don't have a Databricks Account? Sign up for Community Edition: 🤍 This is Part 1 of our Introduction to Machine Learning Video Series: 🤍 About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: 🤍 Connect with us: Website: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Instagram: 🤍 Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. 🤍

DataScience con PySpark I: Apache Spark, Python, DataFrames y RDDs

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22.03.2021

Empezamos con Apache Spark, herramienta líder para analítica de datos con BigData, Ingeniería de datos, etc. Todo el código y explicación en mi blog albert coronado punto com.

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