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Keen Technologies have excellent Hadoop instructors who have real time experience plus expert orientation in handling Hadoop Technology. Enroll with us and make yourself as a Hadoop professional.
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HADOOP ONLINE TRAINING Training Program By KEEN IT http://www.keentechnologies.com
About Us Keen IT Technologies Pvt Ltd. is one of the leading IT training Institutions, located in Hyderabad with the objective of providing a Training services for various requirements in IT industry. We deliver corporate trainings as per the student requirements colonize and innovator of global eLearning solutions and providing technology enabled online training for individuals and corporate educators. We have highly talented faculty in their respective courses. We furnish with online training given us an edge on numerous Technologies.
Introduction to Hadoop Hadoop is a complete, open-source ecosystem for capturing, organizing, storing, searching, sharing, analyzing, visualizing, and otherwise processing disparate data sources (structured, semi-structured, and unstructured) in a cluster of commodity computers. Hadoop's ability to store and analyze large data sets in parallel on a large cluster of computers yields exceptional performance, while the use of commodity hardware results in a remarkably low cost. In fact, Hadoop clusters often cost 50 to 100 times less on a per-terabyte basis than today's typical data warehouse.
Why Hadoop (and Why Now) Organizations across all industries are confronting the same challenge: data is arriving faster than existing data warehousing platforms are able to absorb and analyze it. The migration to online channels, for example, is driving unprecedented volumes of transaction and click stream data, which are, in turn, driving up the cost of data warehouses, ETL processing, and analytics.
Hadoop Course Out Line Distributed computing Parallel computing Concurrency Cloud Computing Computing Past, Present and Future Hadoop Streaming Distributing Debug Scripts Getting Started With Eclipse
Hadoop Stack CAP Theorem Databases: Key Value, Document, Graph Hive and Pig HDFS Lab 1: Hadoop Hands-on Installing Hadoop Single Node cluster(CDH4) Understanding Hadoop configuration files
Map Reduce Introduction Functional – Concept of Map and Reduce Functional – Ordering, Concurrency, No Lock, Concurrency Functional – Shuffling, Reducing, Key, Concurrency Map Reduce Execution framework Map Reduce Practitioners and Combiners Map Reduce and role of distributed file system Role of Key and Pairs Hadoop Data Types
Lab 2: Map Reduce Exercises Understanding Sample Map Reduce code Executing Map Reduce code HDFS Introduction Architecture File System Data replication and Node Name Node
Lab 3: Hive Hands ON Installation, Setup and Exercises PIG Rationale Pig Latin Input, Output and Relational Operators User Defined Functions Analyzing and designing using Pig Latin
Lab 4: Pig Hands on Installation and Setup Executing Pig Latin scripts on File system Executing Pig Latin scripts on HDFS Writing custom User Defined Functions Flume What is Flume? And How it works ? How it works ? And An example
What is Oozie? And How it works? Introduction to Zoo Keeper Cluster Planning and Cloud Manager Set-up Hadoop Multi node Cluster Setup Installation and Configuration Running Map Reduce Jobs on Multi Node cluster Working with Large data sets Steps involved in analyzing large data Lab walk through High Availability Fed ration, Yarn and Security
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