big data training institute in chennai

Big data and hadoop Training in Chennai

Big data and hadoop Training Institute in chennai With Live Projects

big data training institute in chennai

bigdata training in chennai. Big data means really a big data, it is a collection of large datasets that cannot be processed using traditional computing techniques. Big data is not merely a data, rather it has become a complete subject, which involves various tools, technqiues and frameworks.Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware.Hadoop training in chennai It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.

Best Institute for Learning Big dada and Hadoop

Zerobug Academy Provides best Big dada and Hadoop Training in Chennai at reasonable cost and best placement support. The Big dada and Hadoop training sessions are handled by top notch IT experts in Chennai who are capable of teaching concepts with real time examples. The Big dada and Hadoop Training in Chennai Zerobug Academy Syllabus are designed according current requirement of IT companies moreover Zerobug Academy provides more practical class which help you clear the interviews and certification easily. After completion of course Zerobug Academy will arrange you interviews in leading software companies in Chennai so it right time to join Big dada and Hadoop training at Zerobug Academy.

It is free of cost and that makes it easily approachable for all the first-timers and beginners. The documentation support via Big data and hadoop Doc is of great use to all those who are not aware of the technicalities that come with programming.

Hadoop Training Course syllabus :

Module 1 : Fundamental of Core Java

Module 2 : Fundamental of Basic SQL

Module 3: Introduction to BigData, Hadoop (HDFS and MapReduce) :

  • 1. BigData Inroduction
  • 2. Hadoop Introduction
  • 3. HDFS Introduction
  • 4. MapReduce Introduction
  • Module 4 : Deep Dive in HDFS
  • 1. HDFS Design
  • 2. Fundamental of HDFS (Blocks, NameNode, DataNode, Secondary Name Node)
  • 3. Read/Write from HDFS
  • 4. HDFS Federation and High Availability
  • 5. Parallel Copying using DistCp
  • 6. HDFS Command Line Interface
  • Module 4A : HDFS File Operation Lifecycle (Supplementary)
  • 1. File Read Cycel from HDFS
  • DistributedFileSystem
  • FSDataInputStream
  • 2. Failure or Error Handling When File Reading Fails
  • 3. File Write Cycle from HDFS
  • FSDataOutputStream
  • 4. Failure or Error Handling while File write fails
  • Module 5 : Understanding MapReduce :
  • 1. JobTracker and TaskTracker
  • 2. Topology Hadoop cluster
  • 3. Example of MapReduce
  • Map Function
  • Reduce Function
  • 4. Java Implementation of MapReduce
  • 5. DataFlow of MapReduce
  • 6. Use of Combiner
  • Module 6 : MapReduce Internals -1 (In Detail)
  • 1. How MapReduce Works
  • 2. Anatomy of MapReduce Job (MR-1)
  • 3. Submission & Initialization of MapReduce Job (What Happen ?)
  • 4. Assigning & Execution of Tasks
  • 5. Monitoring & Progress of MapReduce Job
  • 6. Completion of Job
  • Module 7 : Advanced MapReduce Algorithm
  • File Based Data Structure
  • Sequence File
  • MapFile
  • Default Sorting In MapReduce
  • Data Filtering (Map-only jobs)
  • Partial Sorting
  • Data Lookup Stratgies
  • In MapFiles
  • Sorting Algorithm
  • Total Sort (Globally Sorted Data)
  • InputSampler
  • Secondary Sort
  • Module 8 : Advanced MapReduce Algorithm -2
  • 1. MapReduce Joining
  • Reduce Side Join
  • MapSide Join
  • Semi Join
  • 2. MapReduce Job Chaining
  • MapReduce Sequence Chaining
  • MapReduce Complex Chaining
  • Module 9 : Apache Pig
  • 1. What is Pig ?
  • 2. Introduction to Pig Data Flow Engine
  • 3. Pig and MapReduce in Detail
  • 4. When should Pig Used ?
  • 5. Pig and Hadoop Cluster
  • 6. Pig Interpreter and MapReduce
  • 7. Pig Relations and Data Types
  • 8. PigLatin Example in Detail
  • 9. Debugging and Generating Example in Apache Pig
  • Module 9A : Apache Pig Coding
  • 1. Working with Grunt shell
  • 2. Create word count application
  • 3. Execute word count application
  • 4. Accessing HDFS from grunt shell
  • Module 9B : Apache Pig Complex Datatypes
  • 1. Underst7and Map, Tuple and Bag
  • 2. Create Outer Bag and Inner Bag
  • 3. Defining Pig Schema
  • Module 9C : Apache Pig Data loading
  • 1. Understand Load statement
  • 2. Loading csv file
  • 3. Loading csv file with schema
  • 4. Loading Tab separated file
  • 5. Storing back data to HDFS.
  • Module 9D :Apache Pig Statements
  • 1. ForEach statement
  • 2. Example 1 : Data projecting and foreach statement
  • 3. Example 2 : Projection using schema
  • 4. Example 3 : Another way of selecting columns using two dots ..
  • Module 9E : Apache Pig Complex Datatype practice
  • 1. Example 1 : Loading Complex Datatypes
  • 2. Example 2 : Loading compressed files
  • 3. Example 3 : Store relation as compressed files
  • 4. Example 4 : Nested FOREACH statements to solved same problem.
  • Module 10 : Fundamental of Apache Hive Part-1
  • 1. What is Hive ?
  • 2. Architecture of Hive
  • 3. Hive Services
  • 4. Hive Clients
  • 5. how Hive Differs from Traditional RDBMS
  • 6. Introduction to HiveQL
  • 7. Data Types and File Formats in Hive
  • 8. File Encoding
  • 9. Common problems while working with Hive
  • Module 10A : Apache Hive
  • 1. HiveQL
  • 2. Managed and External Tables
  • 3. Understand Storage Formats
  • 4. Querying Data
  • Sorting and Aggregation
  • MapReduce In Query
  • Joins, SubQueries and Views
  • 5. Writing User Defined Functions (UDFs)
  • 6. Data types and schemas
  • 7. Querying Data
  • 8. HiveODBC
  • 9. User-Defined Functions
  • Module 11 :Step by Step Process creating and Configuring eclipse for writing MapReduce
    Code
  • Module 12 : NOSQL Introduction and Implementation
  • 1. What is NoSQL ?
  • 2. NoSQL Characerstics or Common Traits
  • 3. Catgories of NoSQL DataBases
  • Key-Value Database
  • Document DataBase
  • Column Family DataBase
  • Graph DataBase
  • 4. Aggregate Orientation : Perfect fit for NoSQl
  • 5. NOSQL Implementation
  • 6. Key-Value Database Example and Use
  • 7. Document DataBase Example and Use
  • 8. Column Family DataBase Example and Use
  • 9. What is Polyglot persistence ?
  • Module 12A : HBase Introduction
  • 1. Fundamentals of HBase
  • 2. Usage Scenerio of HBase
  • 3. Use of HBase in Search Engine
  • 4. HBase DataModel
  • Table and Row
  • Column Family and Column Qualifier
  • Cell and its Versioning
  • Regions and Region Server
  • 5. HBase Designing Tables
  • 6. HBase Data Coordinates
  • 7. Versions and HBase Operation
  • Get/Scan
  • Put
  • Delete
  • Module 13 : Apache Sqoop (SQL To Hadoop)
  • 1. Sqoop Tutorial
  • 2. How does Sqoop Work
  • 3. Sqoop JDBCDriver and Connectors
  • 4. Sqoop Importing Data
  • 5. Various Options to Import Data
  • Table Import
  • Binary Data Import
  • SpeedUp the Import
  • Filtering Import
  • Full DataBase Import Introduction to Sqoop
  • Module 14 : Apache Flume
  • 1. Data Acquisition : Apache Flume Introduction
  • 2. Apache Flume Components
  • 3. POSIX and HDFS File Write
  • 4. Flume Events
  • 5. Interceptors, Channel Selectors, Sink Processor
  • 1. Sample Twiteer Feed Configuration
  • 2. Flume Channel
  • Memory Channel
  • File Channel
  • 3. Sinks and Sink Processors
  • 4. Sources
  • 5. Channel Selectors
  • 6. Interceptors
  • Module 15 : Apache Spark : Introduction to Apache Spark
  • 1. Introduction to Apache Spark
  • 2. Features of Apache Spark
  • 3. Apache Spark Stack
  • 4. Introduction to RDD’s
  • 5. RDD’s Transformation
  • 6. What is Good and Bad In MapReduce
  • 7. Why to use Apache Spark
  • Module 16 : Load data in HDFS using the HDFS commands
  • Module 17 : Importing Data from RDBMS to HDFS
  • 1. Without Specifying Directory
  • 2. With target Directory
  • 3. With warehouse directory
  • Module 18 : Sqoop Import & Export Module
  • 1. Importing Subset of data from RDBMS
  • 2. Chnaging the delimiter during Import
  • 3. Encoding Null values
  • 4. Importing Entire schema or all tables
  • BIG DATA Course Syllabus
  • --------------------------
  • Big Data overview
  • What is a data scientist?
  • What are the roles of a data scientist?
  • Big Data Analytics in industry
  • Data analytics lifecycle
  • Data Discovery
  • Data Preparation
  • Data Model Planning
  • Data Model Building
  • Data Insights
  • Data Analytic Methods Using R
  • Introduction to R
  • Analyzing and Exploring the Data
  • Model Building and Evaluation

Get Touch With Us

  • Zerobug Academy
  • No.19/13A, 7th Cross Street,
  • Rajalakshmi Nagar,
  • (100ft Road Near Erikkarai Bus Stop),
  • (Before Excellent Care Hospital),
  • Velachery, Chennai-600 042
  • PH: +91-9750061584 / 9791040581 / 9524222501

Zerobug Academy is the fast growing software training institute in Chennai offering training in various technologies like Java, Dotnet, Php, AWS, Selenium, Digital Marketing, Hadoop and much more with live examples for the students who are looking for employment opportunities and for the professional who are looking for a job change.