Big Data Hadoop

Big Data Hadoop course is offered by NSPL (Neurosharp Software Pvt. Ltd.). The sole aim of this institute is to empower students with practical knowledge and quality education especially when technological advances have revolutionized life on all fronts.

Our mission is to provide high value-added premier IT Education for our aspiring Students and train them to competently and confidently face the economic, and social challenges arising out of the rapid advancement of technology, shifting economic base in various global markets by providing simultaneous enhancement of research and development capabilities as a synthesis of modern education system, we provide avenues to all sections of the society to grow and prosper.

It is our mission to become the Center of true professional IT Education and create visionary leaders who can face challenges and translate dream into reality for carving a better tomorrow. We always desired to be a centre of professional learning with idea, spirit, and excellence. Always these values remain our code of control to drive us for taking transparent decisions.

Syllabus:

• Overview of Big Data
• Big Data analytics project lifecycle – brief
• Hadoop Overview
• Environment setup
• Setting up Single node cluster
• Setting up Multi node cluster
• Hadoop Distributed File System – HDFS
• HDFS Overview
• HDFS Architecture, Operations
• Data Storage in Hadoop – Replication and Block storage• Hadoop Daemons and its functionality
• Java based approach (Access HDFS through Java)
• Map Reduce
• History of Map Reduce
• Map Reduce architecture – Programming paradigm• How Map Reduce model works?
• Mapper and Reducer concepts
• Data types in Map Reduce
• Input and output formats of Map Reduce
• Course – Curriculum
• Different phases of Map Reduce
• Partitioner and Combiner
• Data Localization in Map Reduce
• Examples of Map Reduce program – Log Analysis• MR Job Configurations
• YARN Framework
• Yarn Architecture
• Advantages of YARN over MR engine V1
• MR Job submission and execution procedure
• Sqoop
• Overview of Sqoop
• Sqoop Installation and configuration
• Importing data from RDBMS to HDFS
• Incremental import of data
• Conditional based import
• Sqoop – to hive import
• Sqoop – Export to RDBMS
• Sqoop – Meta store
• Sqoop – Jobs configure and execution
• Course – Curriculum
• Hive
• Introduction to Hive
• Hive Architecture
• RDBMS vs Hive
• Map Reduce Vs Apache Pig Vs Hive
• Hive shell and HiveQL(HQL)
• Hive server & Beeline client
• Tables Management (External Vs Managed tables)
• Schemas and data types
• Partitions (Static & Dynamic partitioning)
• Bucketing
• Different file formats – rc, orc, parquet, Json, text formats• Hive – Built in functions
• Hive – User defined functions (UDF)
• HQL – Query execution plan & performance tuningIntroduction to NoSQL
• What is NoSQL Databases?
• Fixed schema(RDBMS) Vs Flexible Schema(NoSQL)
• Json (JavaScript Object Notation) format
• Ideas Behind MongoDB / Cassandra
• Course – Curriculum
• HBase
• HBase Introduction
• HBase architecture
• HBase vs RDBMS (fixed Vs flexible schema)
• Master and Region servers
• HBase commands
• Introduction to Apache Spark
• Introduction to Spark
• Apache Hadoop Vs Apache Spark
• Need for Spark
• Sample Programs to understand the advantages of Spark