Overview

The Big Data Hadoop developer course has been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark and Data Science.

Learning Outcomes

• Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
• Gain knowledge of Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
• Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
• Get an overview of Sqoop and Flume and describe how to ingest data using them
• Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution

• Get to know about HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
• Gain a working knowledge of Pig and its components
• Do functional programming in Spark
• Understand resilient distribution datasets (RDD) in detail
• Implement and build Spark applications
• Understand the common use-cases of Spark and the various interactive algorithms
• Learn Spark SQL, creating, transforming, and querying Data frames

Duration: 4 days Workshop + Post Workshop Support

Modules

• Introduction
• Introduction to Big data and Hadoop Ecosystem
• HDFS and YARN
• MapReduce and Scoop
• Basics of Hive and Impala
• Types of Data Formats
• Advanced Hive Concept and Data File Partitioning

• Apache Flume and HBase
• Pig/Tableau & QlikView
• Basics of Apache Spark
• RDDs in Spark
• Implementation of Spark Applications
• Spark Parallel Processing
• Spark RDD Optimization Techniques
• Spark Algorithm

Deliverables

• 2 days Instructor-Led Classroom training from Certified Trainer of Senior Profile.
• Course materials(soft copy) and practice exercises
• Big data Course Completion Certification

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