June 23, 2021
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This video will teach you all about Hadoop MapReduce. The programming technique where huge data is processed in a parallel and distributed fashion is known as Hadoop MapReduce. This video talks about the distributed processing in MapReduce, the various Map execution phases, MapReduce jobs, Hadoop MapReduce job work interaction, and the data types in Hadoop. It also talks about setting up the environment for MapReduce development, helps us understand how to create a new project using MapReduce, speaks of advanced MapReduce, the various output formats in MapReduce, and the joins in MapReduce. 🔥Free Big Data Hadoop Spark Developer Course: https://www.simplilearn.com/learn-had... To learn more about Hadoop, subscribe to our YouTube channel: https://www.youtube.com/user/Simplile... Watch more videos on HadoopTraining: https://www.youtube.com/watch?v=CKLzD... #HadoopTutorialForBeginners #HadoopYARN #WhatIshadoop #HDFSTutorial #Hadoop #HadoopMapReduce #LearnHadoop #HadoopTraining #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 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
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