Hadoop Demo 13Th Sep At 7 Am(Ist) With Real Time Data Set

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[color=#800080][font=helvetica, arial, sans-serif][size=6][b]Hadoop demo on 13th[/b][/size][/font][/color][b][color=#800080][size=6] Sep at 7 AM(IST) || 12th Sep at 9.30 PM(EST) [/size][/color][/b]
[color=#008000][b][size=6]by 9+ yrs exp.trainers [/size][/b][size=6]with Real time Data Set [/size][/color]

[color=#282828][font=helvetica, arial, sans-serif][size=4]Apache Hadoop Big Data Training Course[/size][/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Introduction to HADOOP[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Distributed computing , cloud computing[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Big data Basics and Need for Parallel Processing[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] How Hadoop works ?[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Introduction to HDFS and Map Reduce[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Hadoop Architecture Details[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Name Node[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Data Node[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Secondary Name Node[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Job Tracker[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Task Tracker[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]HDFS ( Hadoop - Distributed File System)[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hadoop Distributed file system , Background, GFS[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Data Replication[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Data Storage[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Data Retrieval[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Additional HDFS commands[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]MapReduce Programming[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] MapReduce, Background[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Writing MapReduce Programs[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Writable and WritableComparable[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Input Format, Output Format[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Input Split and Block size[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Combiner[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Partitioner[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Number of Mappers and Reducers[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Counters[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Map Reduce Algorithms and Exercises[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Line Count and Word Count[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Distributed Search[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Sorting Data – Key Value Data Type Mathematical Transformation example[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Working with Counters exercise[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Distributed Cache exercise[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Zero Reducer based exercises[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Hadoop Streaming[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Introduction to Hadoop Streaming[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Streaming API details and use cases[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Python Based Example for Streaming API[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Exercise for Hadoop Streaming ( XML Files ) Based.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Exercises on Ruby[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Exercise on C# using MS-Azure.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Apache Pig[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Installation[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Execution Types[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Grunt Shell[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Pig Latin[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Data Processing[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Loading and Storing[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Data Filtering[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Grouping & Joining Operations[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hands on Exercises[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Apache HBase Installation and Details[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] HBase and NOSQL Introduction[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] HBase Installation and Configuration.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] HBase and Java Based integration[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] HBase Hadoop Integration Details.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hbase basic exercises[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Apache Hive Instalaltion and Details[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hive Installation on Single cluster Hadoop Node.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hive Services[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hive Shell Description[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hive Server·[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Meta store Details[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hive QL Basics Working with Tables, Databases etc.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hive JDBC programming[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hands on Exercises and Assignments[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Introduction to Amazon Map Reduce (AWS-EMR)[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hadoop using Amaozon Web Service[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] AWS MapReduce and EC2[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] AWS - S3 Service Model.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] AWS-MR Architecture.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Streaming Exercise using EMR JobFlow.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Hadoop Infrastructure Planning[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Basic Hadoop hardware and software req[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Small , Medium and Large cluster[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Networking challenges in Hadoop Deployment[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Disaster Recovery ( DR ) in Hadoop .[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Performance Tuning a large cluster[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Hadoop Industry Solutions[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] EMC GreenPlum Introduction[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] IBM BigInsight Details[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Oracle , Microsoft etc Hadoop Offerings[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Cloudera and HortonWorks Hadoop Package[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Hadoop and Cloud Computing[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Using Cloud technologies for distributed processing[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hadoop on Amazon Web Service.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif] Hadoop in Oracle Cloud / RackSpace[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]============================================================[/font][/color]
[font=helvetica, arial, sans-serif][color=#282828]Recording[/color][/font]
[font=helvetica, arial, sans-serif][color=#282828]Faqs etc[/color][/font]

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