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People use Hadoop to solve many types of problems, and a number of teams have built packages on top of Hadoop Core to address an even larger scope of problems. This chapter will walk through some of the many tools being built on top of Hadoop and one tool that can be built into Hadoop
Apache Hadoop is ideal for organizations with a growing need to store and process massive application datasets. With this book developers will find details for analyzing large datasets with Hadoop, and administrators will learn how to set up and run Hadoop clusters.
NoSQL databases have a lot more to offer than just solving the problems of scale which are mentioned as follows:
Schemaless data representation: Almost all NoSQL implementations offer schemaless data representation. This means that you don’t have to think too far ahead to define a structure and you can continue to evolve over time—including adding new fields or even nesting the data, for example, in case of JSON representation.
Development time: I have heard stories about reduced development time because one doesn’t have to deal with complex SQL queries. Do you remember the JOIN query that you wrote to collate the data across multiple tables to create your final view?
Speed: Even with the small amount of data that you have, if you can deliver in milliseconds rather than hundreds of milliseconds—especially over mobile and other intermittently connected devices—you have much higher probability of winning users over.
Plan ahead for scalability: You read it right. Why fall into the ditch and then try to get out of it? Why not just plan ahead so that you never fall into one. Or in other words, your application can be quite elastic—it can handle sudden spikes of load. Of course, you win users over straightaway.
NoSQL is a generic term used to refer to any data store that does not follow the traditional RDBMS model—specifically, the data is non-relational and it does not use SQL as the query language. It is used to refer to the databases that attempt to solve the problems of scalability and availability against that of atomicity or consistency.
NoSQL is not a database. It is not even a type of database. In fact, it is a term used to filter out (read reject) a set of databases out of the ecosystem. There are several distinct family trees available. In Chapter 4, Advantages and Drawbacks, we explore various types of data models (or simply, database types) available under this umbrella.
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Big Data Training for 5-days at Mumbai on 15th June' 2013 - 19th June 2013
Training will begin promptly at 10:00am and conclude at 5:00pm
Course Completion Certificate + BigData Associate Certificate - unique verification code
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Work on Real time Task Assignment - POC / our Big Data Analytics Platform
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+91-9789968765, 044-42645495
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Course Outline:
What is Big Data & Why Hadoop?
Hadoop Overview & it’s Ecosystem
HDFS – Hadoop Distributed File System
Map Reduce Anatomy
Developing Map Reduce Programs
Advanced Map Reduce Concepts
Advanced Map Reduce Algorithms
Advanced Tips & Techniques
Monitoring & Management of Hadoop
Using Hive & Pig ( Advanced )
HBase
NoSQL
Sqoop
Deploying Hadoop on Cloud
Extensively a practical oriented training
http://www.hadooptrainingindia.in/bigdata-hadoop
-training-mumbai/
http://www.bigdatatraining.in/events/ha
doop-bigdata-training-mumbai/
Key Features :
* Practice on production level Cloud Servers
* Primary focus - hands-on sessions
* Real time Task Assignment - POC / our Big Data Analytics Platform
Register now !
+91-9789968765, 044-42645495
www.bigdatatraining.in