Hadoop Online Training Demo On 15Th Dec At 7.30Pm(Ist)

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[color=#282828][font=helvetica, arial, sans-serif][size=5][color=#FF0000]Email [/color][/size][/font][/color][color=#282828][font=helvetica, arial, sans-serif]: [/font][/color][color=#282828][font=helvetica, arial, sans-serif][size=5]saionlinetraining@gmail com [/size][/font][/color]
[color=#282828][font=helvetica, arial, sans-serif][size=5][color=#FF0000]Contact No[/color] : +91 9036 298 699 [/size][/font][/color]

[color=#FF0000][font=helvetica, arial, sans-serif][size=5]HADOOP Online Training Course Content (Duration:: 35 hours)[/size][/font][/color]

[color=#0000CD][font=helvetica, arial, sans-serif]Overview[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]• Move computation not data[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Hadoop performance and data scale facts[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Hadoop in the context of other data stores[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• The Apache Hadoop Project[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• The Hadoop Ecosystem[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]MapReduce Map and Reduce[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Java Map Reduce[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Running a Distributed Map[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Reduce Job Hadoop Streaming: Python[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]The Hadoop Distributed Filesystem[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• HDFS Design & Concepts[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Blocks, Namenodes and Datanodes[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• hadoop fs The Command-Line Interface[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Basic Filesystem Operations[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Reading Data from a Hadoop URL[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Reading Data Using the FileSystem API[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Data Flow Anatomy of a File Read[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Anatomy of a File Write Coherency Model[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]How MapReduce Works[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Anatomy of a MapReduce Job Run[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Job Submission Job Initialization, Task Assignment, Task Execution[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Progress and Status Updates[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Job Completion, Failures[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Job Scheduling[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Fair Scheduler[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Shuffle and Sort - Map Side, Reduce Side[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Configuration Tuning[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Task Execution, Speculative Execution, Task JVM Reuse, Skipping Bad Records[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• The Task Execution Environment[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Distributed Cache[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]Hadoop Administrator[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Setting Up a Hadoop Cluster[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Cluster Specification[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Network Topology[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Cluster Setup and Installation[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• SSH Configuration[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Hadoop Configuration[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Configuration Management[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]• Environment Settings[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]Hadoop Daemon Addresses and Ports[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Benchmarking a Hadoop Cluster: TeraByte Sort on Apache[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Monitoring, Logging Routine Administration Procedures[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]Installing and Running Pig[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Execution Types[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Running Pig Programs[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]User-Defined Functions[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]HiveQL.[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Serdes[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Metastore[/font][/color]

[color=#282828][font=helvetica, arial, sans-serif]HBase[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Concepts Data Model, Schema Design[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Test Drive[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]REST and Thrift[/font][/color]
[color=#282828][font=helvetica, arial, sans-serif]Metrics[/font][/color]

[training4u]

[color=#282828][font=helvetica, arial, sans-serif][size=5][color=#FF0000]Email [/color][/size][/font][/color][color=#282828][font=helvetica, arial, sans-serif]: [/font][/color][color=#282828][font=helvetica, arial, sans-serif][size=5]saionlinetraining@gmail com [/size][/font][/color]
[color=#282828][font=helvetica, arial, sans-serif][size=5][color=#FF0000]Contact No[/color] : +91 9036 298 699 [/size][/font][/color]

[color=#FF0000][font=helvetica, arial, sans-serif][size=5]HADOOP Online Training Course Content (Duration:: 35 hours)[/size][/font][/color]

[training4u]

By Hadoop certified trainer