This Apache Hadoop course that we are presenting, and very much looking forward to, will give participants an in-depth look at fundamental concepts and processes that are integral to getting Apache Hadoop working efficiently and solidly for businesses of all sizes.

Understanding Bigdata & Hadoop

• Introduction to Big Data & Big Data Challenges
• Limitations & Solutions of Big Data Architecture
• Hadoop & its Features
• Hadoop Ecosystem
• Hadoop 2.x Core Components
• Hadoop Storage: HDFS (Hadoop Distributed File System)
• Hadoop Processing: MapReduce Framework
• Different Hadoop Distributions

Hadoop Architecture & HDFS

• Hadoop 2.x Cluster Architecture
• Federation and High Availability Architecture
• Typical Production Hadoop Cluster
• Hadoop Cluster Modes
• Common Hadoop Shell Commands
• Hadoop 2.x Configuration Files
• Single Node Cluster & Multi-Node Cluster set up
• Basic Hadoop Administration

Hadoop MapReduce Framework

• Traditional way vs. MapReduce way
• Why MapReduce
• YARN Components
• YARN Architecture
• YARN MapReduce Application Execution Flow
• YARN Workflow
• Anatomy of MapReduce Program
• Input Splits, Relation between Input Splits and HDFS Blocks
• MapReduce: Combiner & Partitioner
• Demo of Health Care Dataset
• Demo of Weather Dataset

Advanced Hadoop MapReduce

• Counters
• Distributed Cache
• MRunit
• Reduce Join
• Custom Input Format
• Sequence Input Format
• XML file Parsing using MapReduce

Apache Pig

• Introduction to Apache Pig
• MapReduce vs. Pig
• Pig Components & Pig Execution
• Pig Data Types & Data Models in Pig
• Pig Latin Programs
• Shell and Utility Commands
• Pig UDF & Pig Streaming
• Testing Pig scripts with Punit
• Aviation use-case in PIG
• Pig Demo of Healthcare Dataset

Apache Hive

• Introduction to Apache Hive
• Hive vs Pig
• Hive Architecture and Components
• Hive Metastore
• Limitations of Hive
• Comparison with Traditional Database
• Hive Data Types and Data Models
• Hive Partition
• Hive Bucketing
• Hive Tables (Managed Tables and External Tables)
• Importing Data
• Querying Data & Managing Outputs
• Hive Script & Hive UDF
• Retail use case in Hive
• Hive Demo on Healthcare Dataset

Advanced Apache Hive & HBase

• Hive QL: Joining Tables, Dynamic Partitioning
• Custom MapReduce Scripts
• Hive Indexes and views
• Hive Query Optimizers
• Hive Thrift Server
• Hive UDF
• Apache HBase: Introduction to NoSQL Databases and HBase
• HBase v/s RDBMS
• HBase Components
• HBase Architecture
• HBase Run Modes
• HBase Configuration
• HBase Cluster Deployment

Advanced Apache Hbase

• HBase Data Model
• HBase Shell
• HBase Client API
• Hive Data Loading Techniques
• Apache Zookeeper Introduction
• ZooKeeper Data Model
• Zookeeper Service
• HBase Bulk Loading
• Getting and Inserting Data
• HBase Filters

Processing Distributed Data with Apache Spark

• What is Spark
• Spark Ecosystem
• Spark Components
• What is Scala
• Why Scala
• SparkContext
• Spark RDD

Oozie & Hadoop Project

• Oozie
• Oozie Components
• Oozie Workflow
• Scheduling Jobs with Oozie Scheduler
• Demo of Oozie Workflow
• Oozie Coordinator
• Oozie Commands
• Oozie Web Console
• Oozie for MapReduce
• Combining flow of MapReduce Jobs
• Hive in Oozie
• Hadoop Project Demo
• Hadoop Talend Integration