Excellent Real Time Big Data Hadoop Training By Experts

[intuites]

HADOOP ADMINISTRATION AND DEVELOPER COURSE

 

HADOOP INTRODUCTION

 

·         Introduction to Hadoop:   Introduction to Data and System, Data Lifecycle Management,   Data Properties,  Types of Data,  Introduction of system,   Problems with traditional large-scale systems,  Types of  Systems  &  scaling,  What is Big Data ?,Challenges in Big Data,  Challenges in Traditional Application, New Requirements,What is Hadoop, Brief history of Hadoop,  Features of Hadoop,  Hadoop v/s RDBMS,Hadoop Ecosystem’s overview.

 

ADMINISTRATION OF HADOOP DISTRIBUTED FILE SYSTEM (HDFS)

·         Administration Concepts :  Blocks,  Replication,  Version File, Safe mode,     Namespace IDs,  Reading and Writing in HDFS,  Understanding Name Node,    Understanding Data Node, Understanding Secondary Name Node,  Understanding Job  Tracker,  Understanding Task Tracker, HDFS Shell Commands, Hadoop Admin Commands, Accessing HDFS using API,  Understanding HDFS Java classes and methods, HDFS Nextgeneration Concepts, Hands On Exercise,

 

·         Setting up Hadoop Cluster for Apache Hadoop:     Installation in detail, creating Ubuntu image in VMware, Downloading  Hadoop, Installing  SSH, configuring Hadoop, Download,  Installation & Configuration of Pig, Hive and Sqoop, Installing MySql in Hadoop cluster, Download and work with Cloudera Image.

 

·         Configuring Hadoop in Different Modes;  Local Mode,Running without HDFS, Pseudo-distributed Mode, Running all daemons in a single node, Fully distributed mode,Running daemons on dedicated nodes Managing Hadoop Processes,  Starting and Stopping Processes with Init Scripts, Starting and Stopping Processes Manually, HDFS Maintenance Tasks, Adding a Datanode, Decommissioning a Datanode, Checking Filesystem Integrity with fsck, Balancing HDFS Block Data,    Dealing with a Failed Disk,MapReduce Maintenance Tasks,   Adding a Tasktracker,Decommissioning a Tasktracker,   Killing a MapReduce Job,  Killing a MapReduceTask,Dealing with a Blacklisted Tasktracker

 

MAP REDUCE

(DEVELOPMENT)

 

·         Map Reduce Programming :Understanding block and input splits,,Common Input and Output Formats, MapReduce Data types, Understanding Writable and WritableComparable (Introduction), Data Flow in MapReduce Application, Understanding MapReduce  problem on real datasets(stocks), MapReduce Skeleton in Details, Writing MapReduce Application, Understanding Mapper function, Understanding Reducer Function, Understanding Driver,     Understanding Tool Runner, Hands on Exercise, MapReduce Continued, Using Combiner Using Distributed Cache, Passing the parameters to mapper and reducer, Hands On exercise,Writing Custom key values, Hands On Exercise,Designed Use Cases for common problems.

 

·         Advanced Map Reduce Programming :   MapReduce Chaining, Customized Input Formats and Output Formats

 

·         JobMonitoring and debugging on a Production Cluster :  Counters,  Skipping Bad Records,

Running in local mode

 

·         Tuning for Performance in MapReduce :  Reducing network traffic with combiner,     Partitioners, Reducing the amount of input data, Using Compression, Reusing the JVM,     Running with speculative execution

 

HIVE

(DEVELOPMENT)

 

·         Hive Concepts:  Hive architecture, Install and configure hive on cluster,Different type of tables in hive, Hive library functions, Buckets, Partitions, Joins in hive (inner joins, Outer Joins), Hive UDF

PIG

(DEVELOPMENT)

 

·         Pig Concepts:  Install and configure PIG on a cluster, PIG Library functions, Pig Vs Hive,   Write sample Pig Latin scripts, Modes of running PIG, Running in Grunt shell, Running as Java program, PIG UDFs

SQOOP

(DEVELOPMENT)

 

·         Sqoop Concepts:   Install and configure Sqoop on cluster, Connecting to RDBMS, Installing Mysql, Import data from Oracle/Mysql to hive, Export data to Oracle/Mysql, Internal mechanism of import/export

 

HBASE

(DEVELOPMENT)

 

·         Hbase Concepts:  HBase architecture, Region server architecture, File storage architecture,    HBase basics, Column access, Scans, HBase use cases, Install and configure HBase on a multi node cluster, Create database, Develop and run sample applications, Access data stored in HBase using clients like Java, Python and Perl, Map Reduce client to access the HBase data

 

 

Highlights of the Training :

 

1)      The instructor is a Hadoop Architect  with 9+ years of Experience.

2)      The training is 80% practical and 20% theoretical

3)      Training with Realtime examples

4)      Assignments for every 2 classes

5)      Classes on all weekdays except occasionally on weekends.

6)      Online training using Webex : Easy to install and record your own sessions

7)      Trainer Certified by Intuites

8)      Batches starting every 2 weeks.

9)      Duration of the Training :   1 Month

 

       If Interested in Placement after training, we provide the following   :

 

§  Complete Mockup Sessions  for Vendor and Client  Interviews

§  Resume Review and Preparation by Hadoop Expert

§  Dedicated recruiters to place you and excellent people to help with interviews.

§  Strong relationships with many Prime Vendors and our direct clients for placements.

§  Competitive Pay as per market, on-time payment with our transparent payment system.

§  Our E-Verification may help you to get the extra 17 months extension on OPT

§  Assurance of timely visa status upgrades from OPT/CPT/L1 to H1B and then Green card  with one of the nation’s best ranked immigration attorney

 

      For further details, please contact Pavan at (234)-542-3945 or by email at [email protected].

      If we missed your call, please leave us a message or send us an email.

 

       To know more about Intuites, please visit our website :www.intuites.com

 

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