Overview

The Big Data Hadoop designer course have been intended to grant a top to bottom information on Big Data handling utilizing Hadoop and Spark and Data Science.

LEARNING OUTCOMES

• Comprehend the various parts of Hadoop environment, for example, Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
• Addition information on Hadoop Distributed File System (HDFS) and YARN just as their engineering, and figure out how to work with them for capacity and asset the board
• Comprehend MapReduce and its qualities, and acclimatize some progressed MapReduce ideas
• Get a review of Sqoop and Flume and depict how to ingest information utilizing them
• Comprehend various sorts of record groups, Avro Schema, utilizing Arvo with Hive, and Sqoop and Schema advancement
• Become more acquainted with about HBase, its engineering, information stockpiling, and working with HBase. You will likewise comprehend the contrast among HBase and RDBMS
• Increase a working information on Pig and its parts
• Do practical programming in Spark
• Comprehend flexible dispersion datasets (RDD) in detail
• Execute and construct Spark applications
• Comprehend the basic use-instances of Spark and the different intelligent calculations
• Learn Spark SQL, making, changing, and questioning Data outlines

DURATION: 4DAYS 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 - Classroom training from Certified Trainer.
• Course materials and practice exercises for exam.
• Course Completion certificate