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Hadoop Big Data Demo On 7Th June At 7.30 Am(Ist)


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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]


[color=#282828][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]Hadoop Bigdata demo [/color][/b][/size][/font][/color][b][size=6][color=#0000FF]on 7[/color][/size][/b][b][color=#0000FF][size=6]th June At 7.30 AM(IST)[/size][/color][size=6][color=#0000FF] [/color][/size][/b][color=#282828][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF]|| 6th[/color][/b][/size][/font][/color][b][color=#0000FF][size=6] June[/size][/color][/b][color=#282828][font=helvetica, arial, sans-serif][size=6][b][color=#0000FF] at 10 PM(EST).[/color][/b][/size][/font][/color]

[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]

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[font=Arial, sans-serif][size=2][/size][/font][b][color=red][font=Arial, sans-serif][size=2]Hadoop[/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2] [/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]online Demo on 1s[/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]t June at 8.30 PM (IST) || [/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]1s[/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]t June at[/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2] 11 AM (EST) || [/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]1s[/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]t June at 10 AM(CST) || [/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]1s[/size][/font][/color][/b][b][color=red][font=Arial, sans-serif][size=2]t June at 8 AM(PST)[/size][/font][/color][/b]

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