What will you in the Hadoop Platform and Application Framework Course
Understand the architecture and components of the Hadoop ecosystem
Gain hands-on experience with Hadoop and Spark frameworks
Learn to use the Hadoop Distributed File System (HDFS) for data storage
Implement data processing tasks using the MapReduce programming model
Explore tools like Apache Pig, Hive, and HBase for big data analysis
Program Overview
1. Hadoop Basics
Duration: 2 hours
Introduction to big data concepts and the Hadoop ecosystem
Overview of Hadoop stack and associated tools
Hands-on exploration of the Cloudera virtual machine
2. Introduction to the Hadoop Stack
Duration: 3 hours
Detailed examination of HDFS components and application execution frameworks
Introduction to YARN, Tez, and Spark
Exploration of Hadoop-based applications and services
3. Introduction to Hadoop Distributed File System (HDFS)
Duration: 3 hours
Understanding the design goals and architecture of HDFS
Learning about read/write processes and performance tuning
Accessing HDFS data through various APIs
4. Introduction to MapReduce
Duration: 7 hours
Learning the MapReduce programming model
Designing and executing MapReduce tasks
Exploring trade-offs and performance considerations in MapReduce
5. Introduction to Spark
Duration: 9 hours
Understanding the Spark framework and its integration with Hadoop
Exploring Spark’s core components and functionalities
Hands-on experience with Spark for big data processing
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Job Outlook
Data Engineers: Enhance skills in big data processing using Hadoop and Spark
Data Analysts: Gain proficiency in handling large datasets and performing complex analyses
Software Developers: Learn to build scalable applications using Hadoop ecosystem tools
IT Professionals: Understand the infrastructure and management of big data platforms
Aspiring Data Scientists: Build a strong foundation in big data technologies
Specification: Hadoop Platform and Application Framework
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