Big data hadoop course syllabus - NetTech India

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NetTech India is the best big data Hadoop training course provider in Mumbai. We provide big data Hadoop classroom training for students and also for working professionals.


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BIGDATA HADOOP – ANALYTIC Module 1: Introduction Big data and Hadoop  What is Big Data  Characteristics of big data  Big Data challenges  Popular tools used with big data For storing processing analysing visualization  Where Hadoop fits in  Traditional data analytics architecture versus Hadoop  What is Hadoop  History of Hadoop  Hadoop’s key characteristics  Hadoop usage Module 2: Hadoop Eco-system Architecture  Hadoop eco-system core components  HDFS architecture overview of MRv1  HDFS daemons  Files and blocks  Anatomy of a file write read  Replication rack awareness Module 3: Introduction to YARN  What is YARN  MR1 v MR2  YARN architecture  HDFS Federation  YARN Deamons  YARN Job execution workflow  Authentication and high availability in Hadoop Module 4: Hadoop Cluster Configuration  Hortonworks sandbox installation configuration  Hadoop Configuration files  Working with Hadoop services using Ambari  Hadoop deamons  Browsing Hadoop UI consoles  Basic Hadoop Shell commands  Eclipse winscp installation configurations on VM Module 5: Basics of MapReduce on YARN  Running a MapReduce application in MR2  MapReduce Framework on YARN  Fault tolerance in YARN  Map Reduce Shuffle phases  Understanding Mapper Reducer Driver classes Module 6: MapReduce Programming  Writing Map Reduce WordCount program  Executing monitoring a Map Reduce job  Use case - Sales calculation using M/R

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Module 7: Analysis using Pig  Background of Pig  Pig architecture  Pig Latin basics  Pig execution modes  Pig processing – loading and transforming data  Pig built-in functions  Filtering grouping sorting data  Relational join operators  Pig Scripting  Pig UDFs Module 8: Analysis using Hive Data Warehousing Infrastructure  Background of Hive  Hive architecture  Hive Query Language  Derby to MySQL database  Managed external tables  Data processing – loading data into tables  Hive Query Language  Using Hive built-in functions  Partitioning data using Hive  Bucketing data  Hive Scripting  Using Hive UDFs Module 9: Working with HBase  HBase overview  Data model  HBase architecture  HBase shell  Zookeeper its role in HBase environment  HBase Shell environment  Creating table  Creating column families  CLI commands – get put delete scan  Scan Filter operations Module 10: Importing Exporting Data using Sqoop  Importing data from RDBMS to HDFS  Exporting data from HDFS to RDBMS  Importing exporting data between RDBMS Hive tables Module 11: Oozie Workflow Management  Overview of Oozie  Oozie Workflow Architecture  Creating workflows with Oozie Module 12: Using Flume for Analysing Streaming Data  Introduction to Flume  Flume Architecture  Flume Demo

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