Bigdata Training in Bangalore

/Bigdata Training in Bangalore
Bigdata Training in Bangalore 2017-11-02T12:41:32+00:00

Bigdata Training in bangalore

The volume of data is growing exponentially year by year and the data sets are very large that the traditional Relational Database Management Systems or the existing data centers are not enough to handle such a huge volume of data. When the data falls under the following categories – Huge volume, different variety, high velocity(speed), the data is termed as Big Data. These characteristics are defined as 3V characteristics of Big Data.

Big Data is everywhere, from healthcare to transport to retail & e-commerce to even politics. Big Data processing and analytics played a crucial role in US President Trump’s successful election in 2017. All the organizations use their big data to provide customized services, improve customer satisfaction by providing recommendations, and many other various services which leads to find the new business opportunities.hadoop-training-in-bangalore

TIB Academy in Bangalore is recognized as the best Hadoop training institute in Bangalore as we provide the best Hadoop classroom training as well as the best online training which helps the candidate to learn big data Hadoop in a better and smart way.

Apache Hadoop allows the users to deal with the large set of data using a simple programming model. It provides, HDFS – Hadoop Distributed file system for large data set storage and Map Reduce – A programming model to process the data. Due to the faster data growth, Hadoop is considered as a key big data solution in the market. There are various Hadoop ecosystem components available like Apache Pig, Hive, Sqoop, Flume, Oozie which helps to harness the power of the big data better.

The resources with Hadoop Skill to be able to implement the data processing are in high demand with the rise of Big Data. Also, there has been a huge investment by various organizations in the Big Data field over last few years. Learning how to use Big Data technologies can make you highly desirable in various industries, since there has been a clear increase in the jobs on Big Data.

Among all the Hadoop training institutes in Bangalore, We, the TIB (Training In Bangalore) academy always ranked as the top Big Data Hadoop training institute since the course has an exceptional focus on real time Hadoop projects. You will become an expert in HDFS, Map Reduce, Apache Pig, Apache Hive, Flume, Oozie, HBase and guidance to learn Apache Spark with real time industrial use cases.

Syllabus

  • Importance of Data
  • ESG Report on Analytics
  • Big Data & It’s Hype
  • What is Big Data?
  • Structured vs Unstructured data
  • Definition of Big Data
  • Big Data Users & Scenarios
  • Challenges of Big Data
  • Why Distributed Processing?
  • History Of Hadoop
  • Hadoop Ecosystem
  • Hadoop Animal Planet
  • When to use & when not to use Hadoop
  • What is Hadoop?
  • Key Distinctions of Hadoop
  • Hadoop Components/Architecture
  • Understanding Storage Components
  • Understanding Processing Components
  • Anatomy Of a File Write Anatomy of a File Read
  • Handout discussion
  • Walkthrough of CDH setup
  • Hadoop Cluster Modes
  • Hadoop Configuration files
  • Understanding Hadoop Cluster configuration
  • Data Ingestion to HDFS
  • Meet MapReduce
  • Word Count Algorithm – Traditional approach
  • Traditional approach on a Distributed system
  • Traditional approach – Drawbacks
  • MapReduce approach
  • Input & Output Forms of a MR program
  • Map, Shuffle & Sort, Reduce Phases
  • Workflow & Transformation of Data
  • Word Count Code walkthrough
  • Input Split & HDFS Block
  • Relation between Split & Block
  • MR Flow with Single Reduce Task
  • MR flow with multiple Reducers
  • Data locality Optimization
  • Speculative Execution
  • Combiner
  • Partitioner
  • Counters
  • Hadoop Data Types
  • Custom Data Types
  • Input Format & Hierarchy
  • Output Format & Hierarchy
  • Side Data distribution – Distributed cache
  • Joins
  • Map side Join using Distributed cache
  • Reduce side Join
  • MR Unit – An Unit testing framework
  • What is Pig?
  • Why Pig?
  • Pig vs Sql
  • Execution Types or Modes
  • Running Pig
  • Pig Data types
  • Pig Latin relational Operators
  • Multi Query execution
  • Pig Latin Diagnostic Operators
  • Pig Latin Macro & UDF statements
  • Pig Latin Commands
  • Pig Latin Expressions
  • Schemas
  • Pig Functions
  • Pig Latin File Loaders
  • Pig UDF & executing a Pig UDF
  • Introduction to Hive
  • Pig Vs Hive
  • Hive Limitations & Possibilities
  • Hive Architecture
  • Metastore
  • Hive Data Organization
  • Hive QL
  • Sql vs Hive QL
  • Hive Data types
  • Data Storage
  • Managed & External Tables
  • Partitions & Buckets
  • Storage Formats
  • Built-in Serdes
  • Importing Data
  • Alter & Drop Commands
  • Data Querying
  • Using MR Scripts
  • Hive Joins
  • Sub Queries
  • Views
  • UDFs
  • Introduction to NoSql & HBase
  • Row & Column oriented storage
  • Characteristics of a huge DB
  • What is HBase?
  • HBase Data-Model
  • HBase vs RDBMS
  • HBase architecture
  • HBase in operation
  • Loading Data into HBase
  • HBase shell commands
  • HBase operations through Java
  • HBase operations through MR
  • Introduction to MongoDB
  • Basic Commands used in it
  • Introduction to Zookeeper
  • Distributed Coordination
  • Zookeeper Data Model
  • Zookeeper Service
  • Zookeeper in HBase
  • Introduction to Oozie
  • Oozie workflow
  • Introduction to Sqoop
  • Sqoop design
  • Sqoop Commands
  • Sqoop Import & Export Commands
  • Sqoop Incremental load Commands
  • Introduction to Flume
  • Architecture & its Components
  • Flume Configuration & Interceptors
  • Hadoop 1 Limitations
  • HDFS Federation
  • NameNode High Availability
  • Introduction to YARN
  • YARN Applications
  • YARN Architecture
  • Anatomy of an YARN application
  • Installing Hadoop 2.2 on the Ubuntu
  • Installing Eclipse and Maven
  • Setting up the configuration files
  • Installation of Pig,Hive,Sqoop,Flume,oozie and zookeper
  • Installation of NoSql database – HBase
  • Hadoop Commands
  • What is Big Data?
  • What is Spark?
  • Why Spark?
  • Spark Ecosystem
  • A note about Scala
  • Why Scala?
  • MapReduce vs Spark
  • Hello Spark!
  • Mockup Interview Session
  • Resume Preparation
  • Project Discussion
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