This Big Data Hadoop course is designed to help learners understand large-scale data processing using Hadoop’s powerful ecosystem. You will learn HDFS, MapReduce, Hive, Sqoop, Flume, Spark, and real-time project workflows. The course prepares students for Big Data Engineer, Hadoop Developer, Data Engineer, and ETL roles.
What is Big Data?
Challenges with traditional systems
Hadoop introduction & ecosystem overview
Use cases of Big Data in industries
HDFS (Hadoop Distributed File System)
Hadoop Cluster Setup (NameNode, DataNode)
Hadoop Commands
Replication, Blocks & Fault Tolerance
Map & Reduce functions
Writing MapReduce programs
InputSplit & RecordReader
Combiner & Partitioning
Hands-on MapReduce examples
Hive Architecture
Databases, Tables, Partitions
Internal & External Tables
Managed vs. External Storage
HiveQL Queries (CRUD, JOINS, GROUP BY, etc.)
ETL using Hive
Working with complex data types
Importing data from SQL to Hadoop
Exporting data from Hadoop to SQL
Incremental load
Sqoop jobs
Introduction to data ingestion
Flume architecture
Channels, Sources & Sinks
Log ingestion using Flume
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