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Apache Hadoop Big Data Training

Hadoop is indispensable when it comes to processing big data—as necessary to understanding your information as servers are to storing it. This 2 days crash course on Apache Hadoop Big Data training aims to give a good overview and familiarisation with Big Data tool sets such as Hadoop, MapReduce Pig, Hive,Impala, Sqoop, Oozie, Zookeeper Apache Sparks. It will explain Hadoop, its file system (HDFS), its processing engine (MapReduce) .

Topics include:

  • Understanding Hadoop core components: HDFS and MapReduce
  • Setting up your Hadoop development environment
  • Working with the Hadoop file system
  • Running and tracking Hadoop jobs
  • Tuning MapReduce
  • Understanding Hive and HBase
  • Exploring Pig tools
  • Building workflows
  • Using other libraries, such as Impala, Mahout, and Storm
  • Understanding Spark
  • Visualizing Hadoop output


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Course Code: CRS-N-0040689

Course Booking

$498.00

Course Date

Course Time

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Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.

Course Details

Day1

Module 1: Get Started on Apache Hadoop

  • Why Hadoop?
  • Differnece between HBase and Hadoop

Module 2: Hadoop Core Components

  • Java Virutal Machine (JVM)
  • HDFS
  • Hadoop Cluster Components
  • Exploring Hadoop Platforms

Module 3: Setup Hadoop Development Environment

  • Setup Cloudera Hadoop VM
  • Adding Hadoop LIbraries 
  • Programming Languages

Module 4: MapReduce  2.0/YARN

  • What is MapReduce?
  • MapReduce Components
  • MapReduce on HDFS

Module 5: Hive

  • What is Hive?
  • Hive Queries
  • Analyzing data with Hive

Day 2

Module 6: Pig

  • What is Pig
  • Pig Data types
  • Pig Commands

Module 7: Connectors and Workflows

  • Introducing Sqoop
  • Importing Data with Sqoop
  • Introuducing Flume
  • Importing Data with Sqoop
  • Introducing Zookeeper
  • Using Zookeeper to co-ordindate workflow
  • Introducing Oozie
  • Scheduling jobs using Oozie

Module 8: Exploring Other Hadoop Libraries

  • Introducing Impala
  • Introducing Mahout
  • Introduing Storm

Module 8: Apache Spark Basics

  • Why Apache Spark?
  • Apache Spark Components
  • Apache Spark Commmands

Who Should Attend

  • Data Scientists
  • Data Analyts
  • Hadoop Administrator
  • Big Data Analysts

Prerequisite

Nil

Trainers

Big Data TrainerMohan is certified cloud ear administrator and working as Big data architect in one of telecom Company. He has more than 12 years experience in the IT industry. His skill sets are Expertise in CDH,Hadoop, Spark, Scala, Hive/Hive-server2, Sqoop/Sqoop-Server2, Impala, Sentry, Kafka, solr, Hbase, Pig, Impala, Oozie, Fair scheduler,AWS,Map R. Provide the Big data consultancy services on Planning and sizing of Hadoop Cluster. Backup and recovery strategies, HA, Configure Hadoop security and authorization rules for Hive/Impala Jobs. Performance tunning of Map reduce Jobs, Spark jobs, Solr. Best Recommendations of Hardware and software for Solr,Hbase, Kafka,Zookeeper service ,Hadoop storage formats. Data Analysis using Impala, Impyla, spark. He graduated from S.V.University from India with a B.tech

Cyber Security TrainerDr. Sarita Singh received her Ph.D. degree for her work done in the area of Information Security. She is the recipient of the prestigious Infosys fellowship for pursuing her Ph.D. Programme. She has more than twenty-five years of teaching and research experience in Singapore, Malaysia and India in the field of Programming, Information Security, Web-application Development, Computer Networks and Engineering related modules.

She has presented papers at several National and International Conferences and has written articles for magazines. She has authored text-books for Engineering courses as well.

Big Data TrainerSunny Prakash is a Big Data Architect with Programming Background . He has around 7 years of IT experience. He has worked on Various Enterprise level solution. He is skilled in Cloud computing and Big Data Solution building in various Industrial sector and domain.

With an Strong background in Coding skills, he has a strong grips on Java,Python ,Scala ,HTML,JavaScript, Node Programming. Data Science is another specification where he has worked with larger Enterprises for finding their Data Insight and building Machine Learning mode

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