Hadoop Big Data Demo On 12Th June At 7 Am(Ist)

[training4u]

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[color=#000000][font=helvetica, arial, sans-serif][size=6][b]Contact No: [/b][/size][/font][/color][color=#FF0000][font=helvetica, arial, sans-serif][size=6][b]+91 9036 298 699[/b][/size][/font][/color]


[font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]Hadoop Bigdata demo [/color][/b][/size][/font][b][size=6][color=#0000FF]on 12[/color][/size][/b][b][color=#0000FF][size=6]th June At 7 AM(IST)[/size][/color][size=6][color=#0000FF] [/color][/size][/b][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]|| 11th[/color][/b][/size][/font][b][color=#0000FF][size=6] June [/size][/color][/b][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]at 9.30 PM(EST).[/color][/b][/size][/font]

[color=#800080][size=6][b]Hadoop Training Course Contents[/b][/size][/color]
· Introduction and Motivation of Hadoop

[indent=1]o What is Big Data[/indent]
[indent=1]o Challenges in Big Data[/indent]
[indent=1]o Challenges in Traditional Application[/indent]
[indent=1]o New Requirements[/indent]
[indent=1]o What is Hadoop[/indent]
[indent=1]o Brief history of Hadoop[/indent]
[indent=1]o Features of Hadoop[/indent]
[indent=1]o Hadoop v/s RDBMS[/indent]
[indent=1]o Hadoop Ecosystem’s overview[/indent]
[indent=1]o Overview of HDFS and MapReduce[/indent]· Understanding Hadoop Distributed File System

[indent=1]o Understanding Configuration[/indent]
[indent=1]o HDFS Concepts[/indent]
[indent=1]§ Blocks[/indent]
[indent=1]§ Replication[/indent]
[indent=1]§ Version File[/indent]
[indent=1]§ Safe mode[/indent]
[indent=1]§ Namespace IDs[/indent]
[indent=1]o Reading and Writing in HDFS[/indent]
[indent=1]o Understanding Name Node[/indent]
[indent=1]o Understanding Data Node[/indent]
[indent=1]o Understanding Secondary Name Node[/indent]
[indent=1]o Understanding Job Tracker[/indent]
[indent=1]o Understanding Task Tracker[/indent]· HDFS Shell Commands

[indent=1]o Hands On Exercise[/indent]· Accessing HDFS using API

[indent=1]o Understanding HDFS Java classes and methods[/indent]
[indent=1]o Hands On Exercise[/indent]· Map Reduce Programming

[indent=1]o Understanding block and input splits[/indent]
[indent=1]o Common Input and Output Formats[/indent]
[indent=1]o MapReduce Data types[/indent]
[indent=1]o Understanding Writable and WritableComparable (Introduction)[/indent]
[indent=1]o Data Flow in MapReduce Application[/indent]
[indent=1]o Understanding WordCount problem[/indent]
[indent=1]o Writing MapReduce Application[/indent]
[indent=1]§ Understanding Mapper function[/indent]
[indent=1]§ Understanding Reducer Function[/indent]
[indent=1]§ Understanding Driver[/indent]
[indent=1]§ Understanding Tool Runner[/indent]
[indent=1]§ Hands on Exercise[/indent]· MapReduce Continued

[indent=1]o Using Combiner[/indent]
[indent=1]o Using Distributed Cache[/indent]
[indent=1]o Passing the parameters to mapper and reducer[/indent]
[indent=1]o Hands On Exercise[/indent]
[indent=1]o Writing Custom key values[/indent]
[indent=1]o Writing Custom Partitioner[/indent]
[indent=1]o Hands On Exercise[/indent]· Introduction to PIG

[indent=1]o Terminology[/indent]
[indent=1]o Understanding Pig Program, structure and Execution[/indent]
[indent=1]o Pig Data types[/indent]
[indent=1]o Loading and Dumping Data[/indent]
[indent=1]o Filtering[/indent]
[indent=1]o Group and Co-Group[/indent]
[indent=1]o Joins[/indent]
[indent=1]§ Inner Join[/indent]
[indent=1]§ Left Outer Join[/indent]
[indent=1]§ Right Outer Join[/indent]
[indent=1]§ Full Outer Join[/indent]
[indent=1]o Hands on[/indent]· Introduction to Hive

[indent=1]o Motivation and Understanding Hive[/indent]
[indent=1]o Using Hive Command line Interface[/indent]
[indent=1]o Data types and File Formats[/indent]
[indent=1]o Basic DDL operations[/indent]
[indent=1]o Schema Design[/indent][b]Hadoop Ecosystem and Other Related Projects[/b]
· [b]HBase[/b]
· [b]Sqoop[/b]
· [b]Flume[/b]
· [b]Oozie[/b][/color][list]
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[training4u]

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[training4u]

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[color=#000000][font=helvetica, arial, sans-serif][size=6][b]Contact No: [/b][/size][/font][/color][color=#FF0000][font=helvetica, arial, sans-serif][size=6][b]+91 9036 298 699[/b][/size][/font][/color]

[training4u]

[color=#282828][font=helvetica, arial, sans-serif][size=6][color=#000000][b]Email:[/b][/color][color=#FF0000][b] [email protected] [/b][/color][/size][/font][/color]

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[training4u]

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