CS/IT TECHNOLOGIES:

The Big data Hadoop beginner training program

The main purpose of this program is to help you to recognize complicated Architectures of Hadoopand its features and show you in the right way to start with and quickly establish working with Hadoop and its features.

Getting Started:

It covers all what you call for as a Big Data learner. Study about Big Data market, diverse job roles, and technology culture, the past of Hadoop, HDFS, Hadoop bionetwork, Hive and Pig. In this course, we will see how as a learner one be supposed to start with Hadoop. This course comes with a lot of practical examples which will lend a hand to you to learn Hadoopquickly.
UnderstandHadoop and its complex architecture. Learn Hadoop Ecosystem with uncomplicated examples. Be familiar with unusual versions of Hadoop (Hadoop 1.x vsHadoop 2.x), special Hadoop Vendors in the market and Hadoop on Cloud. Identify with how Hadoop uses ELT plan. Find out installing Hadoop on your part of equipment. We will see consecutive HDFS guidelines from power line to direct HDFS.

After completion students will be able to:

  • necessities
  • depiction
  • perform with Big Data sets
  • recognize diverse technology trends, salary trends, Big Data market and different job roles in Big Data
  • Understand modern data architecture: Data Lake
  • develop you to be the owner of data pipeline using Pig and Hive
  • establish writing your own codes in Hive and Pig to process huge volumes of data
  • Understand what Hadoop is for, and how it works
  • Understand complex architectures of Hadoop and its component
  • Understand how MapReduce, Hive and Pig can be used to analyze big data sets
  • Hadoop installation on your machine
  • Sample data sets and scripts (HDFS commands, Hive sample queries, Pig sample queries, Data Pipeline sample queries)
  • High quality documents
  • Demos: Running HDFS commands, Hive queries, Pig queries

Topics covered:

  • Getting Started with Hive:
  • Use Cases:
  • Practice:
  • Big Data at a Glance:
  • Getting Started with Pig:

Course Syllabus

    Chapter-1: Introduction to BigData, Hadoop
  • Big Data Introduction
  • Hadoop Introduction
  • What is Hadoop? Why Hadoop?
  • Hadoop History?
  • Different types of Components in Hadoop?
  • HDFS, Map Reduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
  • What is the scope of Hadoop?
  • Chapter-2: Deep Drive in HDFS (for Storing the Data)
  • Introduction of HDFS
  • HDFS Design
  • HDFS role in Hadoop
  • Features of HDFS
  • Daemons of Hadoopand its functionality
    • Name Node
    • Secondary Name Node
    • Job Tracker
    • Data Node
    • Task Tracker
  • Anatomy of File Wright
  • Anatomy of File Read
  • Network Topology
    • Nodes
    • Racks
    • Data Center
  • Parallel Copying using DistCp
  • Basic Configuration for HDFS
  • Data Organization
    • Blocks
    • Replication
  • Rack Awareness
  • Heartbeat Signal
  • How to Store the Data into HDFS
  • How to Read the Data from HDFS
  • Accessing HDFS (Introduction of Basic UNIX commands)
  • CLI commands
  • Chapter-3: MapReduce using Java (Processing the Data)
  • Introduction of MapReduce.
  • MapReduce Architecture
  • Dataflow in MapReduce
    • Splits
    • Mapper
    • Portioning
    • Sort and shuffle Combiner
    • Reducer
  • Understand Difference Between Block and InputSplit
  • Role of RecordReader
  • Basic Configuration of MapReduce
  • MapReduce life cycle
    • Driver Code
    • Mapper
    • and Reducer
  • How MapReduce Works
  • Writing and Executing the Basic MapReduce Program using Java
  • Submission & Initialization of MapReduce Job.
  • File Input/output
  • Formatsin MapReduce Jobs
    • Text Input Format
    • Key Value Input Format
    • Sequence File Input Format
    • NLine Input FormatJoins
    • Mapside Joins
    • Reducer
    • Side Joins
  • Word Count Example
  • Partition MapReduce Program
  • Side Data Distribution
    • Distributed Cache (with Program)
  • Counters (with Program)
    • Types of Counters
    • Task Counters
    • Job Counters
    • User Defined Counters
    • Propagation of Counters
  • Job Scheduling
  • Chapter-4: PIG
  • Introduction to Apache PIG
  • Introduction to PIG Data Flow Engine
  • MapReduce vs PIG in detail
  • When should PIG used?
  • Data Types in PIG
  • Basic PIG programming
  • Modes of Execution in PIG
    • Local Modeand
    • MapReduce Mode
  • Execution Mechanisms
    • Grunt Shell
    • Script
    • Embedded
  • Operators/Transformations in PIG
  • PIG UDF’swith Program
  • Word Count Examplein PIG
  • The difference between the MapReduce and PIG
  • Chapter-5: SQOOP
  • Introduction to SQOOP
  • Use of SQOOP
  • Connect to mySql database
  • SQOOP commands
    • Import
    • Export
    • Eval
    • Codegen and etc…
  • Joins in SQOOP
  • Export to MySQL
  • Export to HBase
  • Chapter-6: HIVE
  • Introduction to HIVE
  • HIVE Meta Store
  • HIVE Architecture
  • Tables in HIVE
  • Managed Tables
    • External Tables
  • Hive Data Types
    • Primitive Types
    • Complex Types
  • Partition
  • Joins in HIVE
  • HIVE UDF’s and UADF’s with Programs
  • Word Count Example
  • Chapter-7: HBASE
  • Introduction to HBASE
  • Basic Configurations of HBASE
  • Fundamentals of HBase
  • What is NoSQL?
  • HBase DataModel
    • Table and Row
    • Column Family and Column Qualifier
    • Cell and its Versioning
  • Categories of NoSQL Data Bases
    • KeyValue Database
    • Document Database
  • Column Family Database
  • HBASE Architecture
    • HMaster
    • Region Servers
    • Regions
    • MemStore
    • Store SQL vs NOSQL
  • How HBASE is differ from RDBMS
  • HDFS vs HBase Client side buffering or bulk uploads
  • HBase Designing Tables
  • HBase Operations
    • Get
    • Scan
    • Put
    • Delete
    Chapter-8: OOZIE
  • Introduction to OOZIE
  • Use of OOZIE
  • Where to use?

Course Information

  • Class Start: Every Monday, Wednesday & Friday
  • Course Duration: 60 hours(40 hours for Software Training & 20 hours for Project Handling)
  • Student Capacity: 8-12 students per batch
  • Certification: For Software Training(1) & For Project Handling(1)
  • Course Benefits Include:
    • Industrial Visit
    • Tool Kit
    • Lifelong Support
    • Placement Guaranteed
    • Project Handling
    • Resume Writing
    • Moneyback Guaranteed

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