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Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
Hadoop course curriculm
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Hadoop course curriculm

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Transcript

  • 1.  Introduction to Distributed Programming › Background of Hadoop › What is Hadoop ? › How Hadoop works ?  Installing Hadoop › Setting up SSH › Setting up Environment Variables › Running Hadoop › Web-Based Cluster
  • 2.  Components of Hadoop › Working with Hadoop File-System › Understanding Hadoop Map-Reduce › Reading and Writing  Writing Basic Map Reduce Program › Getting the Patent Data Set › Constructing Basic Map-Reduce Program › Working with Hadoop Streaming › Improving Performance with Combiners
  • 3.  Advanced MapReduce › Summarization Patterns › Filtering Patterns › Data Organization Patterns › Join Patterns › Meta Patterns › Input and Output Patterns  Programming Practices › Developing Map-Reduce Programs › Monitoring and Debugging on a cluster › Tuning for performance
  • 4.  Hadoop Cookbook › Passing Job-Specific Parameters to your tasks › Probing for Task-Specific Parameters › Partitioning into multiple output files › Inputting from and output to database › Keeping Output in Sorted Order  Managing Hadoop › Checking System’s Health › Setting permissions › Managing Quotas , Enabling Trash , Adding/Deleting Nodes, Recovering from a failed NameNode
  • 5.  Running Hadoop in the Cloud › Introducing Amazon Web Services › Setting up AWS and Setting up cloud on EC2 › Running Map-Reduce Programs on EC2 › Cleaning up and Shutting down your EC2 instances. › Amazon Elastic Map-Reduce and other AWS Services
  • 6.  Programming with Pig › Thinking like a pig › Installing Pig › Running Pig › Learning Pig Latin through Grunt › Pig Latin Syntax › Working with UDF › Working with Scripts
  • 7.  Getting Started on Hive  Data Types and File Formats  HiveQL – Data Definition  HiveQL - Data Manipulation  HiveQL – Queries, Views and Indexes  Schema Design , Tuning & Record Formats  Hive Integration with Oozie  Hive and Amazon Web Services
  • 8.  NoSQL Database › Why No SQL ? › Aggregate Data Models › Distribution Models › Consistency  No SQL DBs › Key-Value DataBases › Document Databases › Column Family Stores › Graph Databases
  • 9.  MongoDB › Introduction › MongoDB through JavaScript Shell › Writing Programs using MongoDB › Document Oriented Data › Queries and Aggregation › Updates, Atomic Operations and Deletes › Indexing, Replication and Sharding
  • 10.  Mahout – Machine Learning › Introduction › Recommenders  Representing Recommender Data  Making Recommendations › Clustering  Clustering Algorithms in Mahout › Classification  Training a Classifier  Evaluating and Tuning a Classifier
  • 11.  Moving Data in and out of Hadoop › Flume › Oozie › Sqoop › Hbase  Data Serialization Formats › XML, JSON › SequenceFiles, Protocol Buffers, Thrift and Avro
  • 12.  Utilizing Data Structures and Algorithms › Modelling Data & Solving Problems with Graphs › Parallelized Bloom Filter Creation in Map- Reduce  Programming Pipelines with Pig › Using Pig to find malicious actors in log data. › Optimizing user workflow with Pig.
  • 13.  Crunch  Cascading  Puppet  Unit Testing Map-Reduce  Heavyweight Job Testing using LocalJobRunner  Debugging User-Space Problems

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