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Hadoop Big Data Admin & Developer Online Training


saiit9

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[b]Hi All,[/b]

[b]We are providing online training on [color=#0000ff]HADOOP BIG DATA (Admin & Developer)[/color]. If anyone interested, please contact us[/b]

[b]Email: [email="[email protected]"][email protected][/email] [/b]
[b] [/b]
[b]Contact No: +91-8123414771[/b]


[color=#0000ff][b]HADOOP Admin Content.[/b][/color]
[b]Introduction[/b]
[b]The Case for Apache Hadoop[/b][list]
[*]A brief history of Hadoop
[*]Core Hadoop components
[*]Fundamental concepts
[/list]
[b]The Hadoop Distributed File System[/b][list]
[*]HDFS features
[*]HDFS design assumptions
[*]Overview of HDFS architecture
[*]Writing and reading files
[*]NameNode considerations
[*]An overview of HDFS security
[*]Hands-On Exercise
[/list]
[b]MapReduce[/b][list]
[*]What is MapReduce?
[*]Features of MapReduce
[*]Basic MapReduce concepts
[*]Architectural overview
[*]Failure recovery
[*]Hands-On Exercise
[/list]
[b]An Overview of the Hadoop Ecosystem[/b][list]
[*]What is the Hadoop ecosystem?
[*]Integration tools
[*]Analysis tools
[*]Data storage and retrieval tools
[/list]
[b]Planning your Hadoop Cluster[/b][list]
[*]General planning considerations
[*]Choosing the right hardware
[*]Network considerations
[*]Configuring nodes
[/list]
[b]Hadoop Installation[/b][list]
[*]Installing Hadoop
[*]Using Cloudera Manager for easy installation
[*]Basic configuration parameters
[*]Hands-On Exercise
[/list]
[b]Advanced Configuration[/b][list]
[*]Advanced parameters
[*]Configuring rack awareness
[*]Configuring Federation
[*]Configuring High Availability
[/list]
[b]Managing and Scheduling Jobs[/b][list]
[*]Managing running jobs
[*]Hands-On Exercise
[*]The FIFO Scheduler
[*]The FairScheduler
[*]Configuring the FairScheduler
[*]Hands-On Exercise
[/list]
[b]Cluster Maintenance[/b][list]
[*]Checking HDFS status
[*]Hands-On Exercise
[*]Copying data between clusters
[*]Adding and removing cluster nodes
[*]Rebalancing the cluster
[*]Hands-On Exercise
[*]NameNode Metadata backup
[*]Cluster upgrading
[/list]
[b]Cluster Monitoring and Troubleshooting[/b][list]
[*]General system monitoring
[*]Managing Hadoop’s log files
[*]Using the NameNode and JobTracker Web UIs
[*]Hands-On Exercise
[*]Cluster monitoring with Ganglia
[*]Common troubleshooting issues
[*]Benchmarking your cluster
[/list]
[b]Populating HDFS from External Sources[/b][list]
[*]An overview of Flume
[*]Hands-On Exercise
[*]An overview of Sqoop
[*]Best practices for importing data
[/list]
[b]Installing and Managing Other Hadoop Projects[/b][list]
[*]Hive
[*]Pig
[*]HBase
[/list]

[color=#0000ff][b]HADOOP Developer Content:[/b][/color]
[b]Introduction[/b]
[b]The Motivation for Hadoop[/b][list]
[*]Problems with traditional large-scale systems
[*]Requirements for a new approach
[/list]
[b]Hadoop: Basic Concepts[/b][list]
[*]An Overview of Hadoop
[*]The Hadoop Distributed File System
[*]Hands-On Exercise
[*]How MapReduce Works
[*]Hands-On Exercise
[*]Anatomy of a Hadoop Cluster
[*]Other Hadoop Ecosystem Components
[/list]
[b]Writing a MapReduce Program[/b][list]
[*]The MapReduce Flow
[*]Examining a Sample MapReduce Program
[*]Basic MapReduce API Concepts
[*]The Driver Code
[*]The Mapper
[*]The Reducer
[*]Hadoop’s Streaming API
[*]Using Eclipse for Rapid Development
[*]Hands-on exercise
[*]The New MapReduce API
[/list]
[b]Integrating Hadoop into the Workflow[/b][list]
[*]Relational Database Management Systems
[*]Storage Systems
[*]Importing Data from RDBMSs With Sqoop
[*]Hands-on exercise
[*]Importing Real-Time Data with Flume
[*]Accessing HDFS Using FuseDFS and Hoop
[/list]
[b]Delving Deeper Into The Hadoop API[/b][list]
[*]More about ToolRunner
[*]Testing with MRUnit
[*]Reducing Intermediate Data With Combiners
[*]The configure and close methods for Map/Reduce Setup and Teardown
[*]Writing Partitioners for Better Load Balancing
[*]Hands-On Exercise
[*]Directly Accessing HDFS
[*]Using the Distributed Cache
[*]Hands-On Exercise
[/list]
[b]Common MapReduce Algorithms[/b][list]
[*]Sorting and Searching
[*]Indexing
[*]Machine Learning With Mahout
[*]Term Frequency – Inverse Document Frequency
[*]Word Co-Occurrence
[*]Hands-On Exercise
[/list]
[b]Using Hive and Pig[/b][list]
[*]Hive Basics
[*]Pig Basics
[*]Hands-on exercise
[/list]
[b]Practical Development Tips and Techniques[/b][list]
[*]Debugging MapReduce Code
[*]Using LocalJobRunner Mode For Easier Debugging
[*]Retrieving Job Information with Counters
[*]Logging
[*]Splittable File Formats
[*]Determining the Optimal Number of Reducers
[*]Map-Only MapReduce Jobs
[*]Hands-On Exercise
[/list]
[b]Joining Data Sets in MapReduce[/b][list]
[*]Map-Side Joins
[*]The Secondary Sort
[*]Reduce-Side Joins
[/list]
[b]Graph Manipulation in Hadoop[/b][list]
[*]Introduction to graph techniques
[*]Representing graphs in Hadoop
[*]Implementing a sample algorithm: Single Source Shortest Path
[/list]
[b]Creating Workflows With Oozie[/b][list]
[*]The Motivation for Oozie
[*]Oozie’s Workflow Definition Format
[*]Hands-On Exercise
[/list]

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