Hadoop training in hyderabad –
what is Hadoop ?
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what is Hadoop Development .
Big Data (Hadoop) Developer Course outline.
Introduction to Big Data and Hadoop.
Understanding Big Data
Challenges in processing Big Data
3V Characteristics (Volume, Variety and Velocity)
Brief history of Hadoop
How Hadoop addresses Big Data?
HDFS and MR
what is HDFS (Hadoop Distributed File System).
HDFS Overview and Architecture
HDFS Keywords like Namenode, Datanode, Heartbeat etc
Data Flows (Read and Write)
HDFS Permissions and Security
How many types in Daemons processes Mapreduce ?
5 Daemons processes Mapreduce.
Mapreduce Data Flow
Word Count Example solving
Algorithms for simple and complex problems
what is Developing a Mapreduce Application.
Setting up working environment
Custom Data Types (Writable and Custom Key Types)
Input and Output file formats
Driver, Mapper and Reducer Code Wal thru
Configuring IDE Eclipse
Writing Unit test and running locally
Map Reduce Web UI
How Mapreduce works?
Classic Mapreduce (Mapreduce I)
YARN (Mapreduce II)
Shuffle and Sort
How Mapreduce works?
Input formats – Input splits & records, text input, binary input, multiple inputs and database input.
Output formats – text output, binary output, multiple outputs, Lazy output and database output.
what is Hadoop EcoSystems.
what is PIG.
Overview of PIG
Installation and running PIG
Loading and storing data
what is HIVE.
Overview of HIVE
Installation and running HIVE
Overview of HBASE
CLinets (avro, REST, Thrift)
what is SQOOP.
Overview of SQOOP
• Solving Case studies
what is Hadoop Admin.
Introduction to Big Data.
• Characteristics of Big Data
• Why is parallel computing important
• Discuss various products developed by vendors
• Components of Hadoop
• Starting Hadoop
• Identify various processes
Working with HDFS.
• Basic file commands
• Web Based User Interface
• Reading & Writing to files
• Run a word count program
• View jobs in the Web UI
How to Installation & Configuration of Hadoop.
• Types of installation (RPM’s & Tar files)
• Set up ‘ssh’ for the Hadoop cluster
• Tree structure
• XML, masters and slaves files
• Checking system health
• Discuss block size and replication factor
• Benchmarking the cluster
what is Advanced administration activities.
• Adding and decommissioning nodes
• Purpose of secondary name node
• Recovery from a failed name node
• Managing quotas
• Enabling trash
how do Monitoring the Hadoop Cluster.
• Hadoop flow monitoring
• Hadoop specific monitoring
Types of Other Components of the Hadoop ecosystem.
• Discuss Hive, Sqoop, Pig, HBase, Flume
• Use cases of each
• Use Hadoop streaming to write code in Perl / Python
what is Hadoop Architecture.
Introduction to Data Storage and Processing.
how to Installing the Hadoop Distributed File System (HDFS).
• Defining key design assumptions and architecture
• Configuring and setting up the file system
• Issuing commands from the console
• Reading and writing files
How to Setting the stage for MapReduce.
• Reviewing the Map Reduction approach
• Introducing the computing daemons
• Dissecting a MapReduce job
Defining Hadoop Cluster Requirements?
Planning the architecture
• Selecting appropriate hardware
• Designing a scalable cluster
how to Building the cluster.
• Installing Hadoop daemons
• Optimizing the network architecture
Configuring a Cluster
how to Preparing HDFS.
• Setting basic configuration parameters
• Configuring block allocation, redundancy and replication
how to Deploying MapReduce.
• Installing and setting up the MapReduce environment
• Delivering redundant load balancing via Rack Awareness
Maximizing HDFS Robustness.
How to Creating a fault-tolerant file system.
Isolating single points of failure
Maintaining High Availability
Triggering manual failover
Automating failover with Zookeeper
Leveraging NameNode Federation.
Extending HDFS resources
Managing the namespace volumes
Critiquing the YARN architecture
Identifying the new daemons
Managing Resources and Cluster Health.
Setting quotas to constrain HDFS utilization
Prioritizing access to MapReduce using schedulers
How to Maintaining HDFS..
Starting and stopping Hadoop daemons
Monitoring HDFS status
Adding and removing data nodes
How to Administering MapReduce.
Managing MapReduce jobs
Tracking progress with monitoring tools
Commissioning and decommissioning compute nodes
How to Extending Hadoop
Simplifying information access.
• Enabling SQL-like querying with Hive
• Installing Pig to create MapReduce jobs
Integrating additional elements of the ecosystem
• Imposing a tabular view on HDFS with HBase
• Configuring Oozie to schedule workflows
How to Implementing Data Ingress and Egress
Facilitating generic input / output.
• Moving bulk data into and out of Hadoop
• Transmitting HDFS data over HTTP with WebHDFS
How to Acquiring application-specific data.
• Collecting multi-sourced log files with Flume
• Importing and exporting relational information with Sqoop
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