Hadoop Demo On 18Th Apr At 8 Am(Ist)

[training4u]

[color=#282828][size=4]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]EMAIL : [email protected][/size][/font][/color]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]contact No : +91 9036298699[/size][/font][/color]

[size=6][b][color=#0000FF]Hadoop Demo On 18th Apr at 8 AM(IST)[font=helvetica, arial, sans-serif] || [/font][/color]
[color=#0000FF][font=helvetica, arial, sans-serif]17th Apr at 10.30 PM(EST).[/font][/color] [/b][/size][/size][/color]<p>

[b]Hadoop and Amazon Web Service-Map Reduce Complete Training course details: [/b]


[b]Exercises:[/b]


[b]1. Introduction to HADOOP[/b]


[b]2. Hadoop Architecture Details[/b]

[b]3. HDFS ( Hadoop - Distributed File System)[/b]

[b]4) MapReduce Programming[/b]


[b]5) Hadoop Streaming[/b]

[b]6) Introduction to Amazon Map Reduce (AMR)[/b]

[b]7) Hadoop Ecosystem and Other Related Projects[/b]
[b]8) Hadoop Data Center Deployment[/b]



[b]9) Hadoop Cluster Administration[/b]



[b]9) Hadoop Business Case[/b]

[b]10) Hadoop and Cloud Computing[/b]


[b]Certification Help:[/b][url="http://www.andhrafriends.com/index.php?app=forums&module=post&section=post&do=reply_post&f=15&t=402204&qpid=1303595871"]Quote[/url][list]
[*]Hadoop Virtual Machine Setup
[*]Configuring Hadoop in Single Cluster.
[*]Loading/UnLoading Data in Distributed HDFS System.
[*]Amazon Map Reduce based Hadoop setup - Multi Cluster Mode.
[*]Process and Metrics Analysis for Hadoop Output.
[*]Apache Pig Installation and script execution.
[*]NOSQL Data setup and Integration with Hadoop.
[*]HiveQL commands and scripts .
[*]HBASE Map Reduce examples.
[*]Many more examples and exercises /assignments
[*]Distributed computing , cloud computing
[*]Big data Basics and Need for Parallel Processing
[*]How Hadoop works ?
[*]Introduction to HDFS and Map Reduce
[*]Name Node
[*]Data Node
[*]Secondary Name Node
[*]Job Tracker
[*]Task Tracker
[*]Hadoop Distributed file system , Background, GFS
[*]Data Replication
[*]Data Storage
[*]Data Retrieval
[*]Additional HDFS commands
[*]MapReduce, Background
[*]Writing MapReduce Programs
[*]Writable and WritableComparable
[*]Input Format, Output Format
[*]Input Split and Block size
[*]Combiner
[*]Partitioner
[*]Number of Mappers and Reducers
[*]Counters
[*]How Streaming Works ?
[*]Writing MapReduce programs in other languages
[*]MapReduce using Cloud
[*]AWS MapReduce and EC2
[*]AWS-MR Architecture.
[*]Multipl Cluster Deployment using AWS-S3
[*]Hive
[*]Pig
[*]HBase
[*]Sqoop
[*]Flume
[*]Oozie
[*]Basic Hadoop data center deployment techniques
[*]Networking challenges in Hadoop Deployment
[*]Disaster Recovery ( DR ) in Hadoop .
[*]Master / Salve Configuration
[*]Important Directroires
[*]Small, Medium and Large Cluster considerations
[*]Hadoop Monitoring - GANGLIA ,NAGIOS
[*]Why Hadoop is NOT a Silver Bullet for all your problems.
[*]When to use Hadoop- Business Cases
[*]When NOT to use Hadoop - Business Case
[*]Using Cloud technologies for distributed processing
[*]Hadoop on Amazon Web Service.
[*]Hadoop in Oracle Cloud / RackSpace
[*]Exam Papers for Cloudera Certified Hadoop Developer/Administrator.
[*]Preparation help and Guidance.


[b]Hadoop and Amazon Web Service-Map Reduce Complete Training course details: [/b]


[b]Exercises:[/b]


[b]1. Introduction to HADOOP[/b]


[b]2. Hadoop Architecture Details[/b]

[b]3. HDFS ( Hadoop - Distributed File System)[/b]

[b]4) MapReduce Programming[/b]


[b]5) Hadoop Streaming[/b]

[b]6) Introduction to Amazon Map Reduce (AMR)[/b]

[b]7) Hadoop Ecosystem and Other Related Projects[/b]
[b]8) Hadoop Data Center Deployment[/b]



[b]9) Hadoop Cluster Administration[/b]



[b]9) Hadoop Business Case[/b]

[b]10) Hadoop and Cloud Computing[/b]


[b]Certification Help:[/b]
[list]
[*]Hadoop Virtual Machine Setup
[*]Configuring Hadoop in Single Cluster.
[*]Loading/UnLoading Data in Distributed HDFS System.
[*]Amazon Map Reduce based Hadoop setup - Multi Cluster Mode.
[*]Process and Metrics Analysis for Hadoop Output.
[*]Apache Pig Installation and script execution.
[*]NOSQL Data setup and Integration with Hadoop.
[*]HiveQL commands and scripts .
[*]HBASE Map Reduce examples.
[*]Many more examples and exercises /assignments
[*]Distributed computing , cloud computing
[*]Big data Basics and Need for Parallel Processing
[*]How Hadoop works ?
[*]Introduction to HDFS and Map Reduce
[*]Name Node
[*]Data Node
[*]Secondary Name Node
[*]Job Tracker
[*]Task Tracker
[*]Hadoop Distributed file system , Background, GFS
[*]Data Replication
[*]Data Storage
[*]Data Retrieval
[*]Additional HDFS commands
[*]MapReduce, Background
[*]Writing MapReduce Programs
[*]Writable and WritableComparable
[*]Input Format, Output Format
[*]Input Split and Block size
[*]Combiner
[*]Partitioner
[*]Number of Mappers and Reducers
[*]Counters
[*]How Streaming Works ?
[*]Writing MapReduce programs in other languages
[*]MapReduce using Cloud
[*]AWS MapReduce and EC2
[*]AWS-MR Architecture.
[*]Multipl Cluster Deployment using AWS-S3
[*]Hive
[*]Pig
[*]HBase
[*]Sqoop
[*]Flume
[*]Oozie
[*]Basic Hadoop data center deployment techniques
[*]Networking challenges in Hadoop Deployment
[*]Disaster Recovery ( DR ) in Hadoop .
[*]Master / Salve Configuration
[*]Important Directroires
[*]Small, Medium and Large Cluster considerations
[*]Hadoop Monitoring - GANGLIA ,NAGIOS
[*]Why Hadoop is NOT a Silver Bullet for all your problems.
[*]When to use Hadoop- Business Cases
[*]When NOT to use Hadoop - Business Case
[*]Using Cloud technologies for distributed processing
[*]Hadoop on Amazon Web Service.
[*]Hadoop in Oracle Cloud / RackSpace
[*]Exam Papers for Cloudera Certified Hadoop Developer/Administrator.
[*]Preparation help and Guidance.
[/list]
[/list][list]
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[/list]

[training4u]

[color=#282828][font=helvetica, arial, sans-serif][color=#FF0000][size=6]EMAIL : [email protected][/size][/color]
[color=#FF0000][size=6]contact No : +91 9036298699[/size][/color]

[size=6][b][color=#0000FF]Hadoop Demo On 18th Apr at 8 AM(IST) || [/color]
[color=#0000FF]17th Apr at 10.30 PM(EST).[/color] [/b][/size][/font][/color][color=#282828][font=helvetica, arial, sans-serif]<p>[/font][/color]

[training4u]

[color=#282828][font=helvetica, arial, sans-serif][color=#FF0000][size=6]EMAIL : [email protected][/size][/color]
[color=#FF0000][size=6]contact No : +91 9036298699[/size][/color]

[size=6][b][color=#0000FF]Hadoop Demo On 18th Apr at 8 AM(IST) || [/color]
[color=#0000FF]17th Apr at 10.30 PM(EST).[/color] [/b][/size][/font][/color][color=#282828][font=helvetica, arial, sans-serif]<p>[/font][/color]

[training4u]

[color=#FF0000][font=helvetica, arial, sans-serif][size=6]EMAIL : [email protected][/size][/font][/color]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]contact No : +91 9036298699[/size][/font][/color]

[color=#282828][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]Hadoop Demo On 18th Apr at 8 AM(IST) || [/color]
[color=#0000FF]17th Apr at 10.30 PM(EST)[/color][/b][/size][/font][/color]

[training4u]

[color=#FF0000][font=helvetica, arial, sans-serif][size=6]EMAIL : [email protected][/size][/font][/color]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]contact No : +91 9036298699[/size][/font][/color]

[training4u]

[color=#FF0000][font=helvetica, arial, sans-serif][size=6]EMAIL : [email protected][/size][/font][/color]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]contact No : +91 9036298699[/size][/font][/color]

[training4u]

[color=#FF0000][font=helvetica, arial, sans-serif][size=6]EMAIL : [email protected][/size][/font][/color]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]contact No : +91 9036298699[/size][/font][/color]

[training4u]

[color=#282828][font=helvetica, arial, sans-serif][color=#FF0000][size=6]EMAIL : [email protected][/size][/color]
[color=#FF0000][size=6]contact No : +91 9036298699[/size][/color]

[size=6][b][color=#0000FF]Hadoop Demo On 18th Apr at 8 AM(IST) || [/color]
[color=#0000FF]17th Apr at 10.30 PM(EST).[/color] [/b][/size][/font][/color][color=#282828][font=helvetica, arial, sans-serif]<p>[/font][/color]

[training4u]

[color=#FF0000][font=helvetica, arial, sans-serif][size=6]EMAIL : [email protected][/size][/font][/color]
[color=#FF0000][font=helvetica, arial, sans-serif][size=6]contact No : +91 9036298699[/size][/font][/color]

[color=#282828][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]Hadoop Demo On 18th Apr at 8 AM(IST) || [/color]
[color=#0000FF]17th Apr at 10.30 PM(EST)[/color][/b][/size][/font][/color]