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Hadoop

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Hadoop is an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation.

Hadoop makes it possible to run applications on systems with thousands of commodity hardware nodes, and to handle thousands of terabytes of data

Hadoop is here to stay and lead the industry in helping the business with numerous ways to store, retrieve and analyze data.

HADOOP SYLLABUS:

INTRODUCTION

  • Big Data
  • 3Vs
  • Role of Hadoop in Big data
  • Hadoop and its ecosystem
  • Overview of other Big Data Systems
  • Requirements in Hadoop
  • UseCases of Hadoop

HDFS

  • Design
  • Architecture
  • Data Flow
  • CLI Commands
  • Java API
  • Data Flow Archives
  • Data Integrity
  • WebHDFS
  • Compression

MAPREDUCE

  • Theory
  • Data Flow (Map – Shuffle – Reduce)
  • Programming [Mapper, Reducer, Combiner, Partitioner]
  • Writables
  • InputFormat
  • Outputformat
  • Streaming API

ADVANCED MAPREDUCE PROGRAMMING

  • Counters
  • CustomInputFormat
  • Distributed Cache
  • Side Data Distribution
  • Joins
  • Sorting
  • ToolRunner
  • Debugging
  • Performance Fine tuning 

ADMINISTRATION – Information required at Developer level

  • Hardware Considerations – Tips and Tricks
  • Schedulers
  • Balancers
  • NameNode Failure and Recovery

HBase

  • NoSQL vs SQL
  • CAP Theorem
  • Architecture
  • Configuration
  • Role of Zookeeper
  • Java Based APIs
  • MapReduce Integration
  • Performance Tuning

HIVE

  • Architecture
  • Tables
  • DDL – DML – UDF – UDAF
  • Partitioning
  • Bucketing
  • Hive-Hbase Integration
  • Hive Web Interface
  • Hive Server

OTHER HADOOP ECOSYSTEMS

  • Pig (Pig Latin , Programming)
  • Sqoop (Need – Architecture ,Examples)
  • Introduction to Components (Flume, Oozie,ambari)

 

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