Hadoop Training Syllabus

During the class you will go through the following hadoop contents.

  • Linux (Ubuntu/Centos) – Tips and Tricks
  • Basic Java Programming – Core Java Oops Concepts
  • Introduction to Big Data and Hadoop
  • Hadoop ecosystem concepts
  • Hadoop MapReduce concepts and features
  • Developing MapReduce applications
  • Pig concepts
  • Hive concepts
  • Oozie workflow concepts
  • Sqoop Data Ingestion
  • Flume Agents
  • Tableau Visualization
  • HBase concepts
  • Real Time tools like Hue, Putty, FileZilla, Cloudera Manager
  • Real Time Projects

Hadoop Cluster Understanding

  • Hadoop 2.x Architecture
  • Typical workflow
  • HDFS Commands
  • Writing files to HDFS
  • Reading files from HDFS
  • Rack awareness
  • Hadoop daemons

Mapreduce

  • MapReduce overview
  • Word count problem
  • Word count flow and solution
  • MapReduce flow

Hive

  • Hive Architecture
  • Types of Metastore
  • Hive Data Types
  • HiveQL
  • File Formats – Parquet, ORC, Sequence and Avro Files Comparison
  • Partitioning & Bucketing
  • Hive JDBC Client
  • Hive UDFs
  • Hive Serdes
  • Hands-on exercises
  • Integration with Tableau

PIG understanding

  • Pig Architecture
  • Pig Data Types
  • Load/Store Functions
  • PigLatin
  • Pig Udfs

Hbase

  • HBase architecture and concepts
  • Hbase Data Model
  • Hbase Shell Interface
  • Hbase Java API

SQOOP

  • Sqoop Architecture
  • Sqoop Import Command Arguments, Incremental Import
  • Sqoop Export
  • Sqoop Jobs

Flume

  • Flume Architecture
  • Flume Agent Setup
  • Types of sources, channels, sinks Multi Agent Flow
  • Hands-on exercises

Oozie

  • Oozie Fundamentals
  • Oozie workflow creations
  • Oozie Job submission, monitoring, debugging
  • Concepts on Coordinators and Bundles
  • Hands-on exercises

Hadoop Real time project implimentation

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