What Is Hadoop In Big Data | Apache Hadoop Introduction | Hadoop Tutorial For Beginners

What is Big data

• Big Data is a collection of data that is huge in volume.
• Big data is also a data but with huge size.
• Big data is collection of large and complex data sets that cannot be processed using traditional computing techniques

Source of big data

• Social networking sites: Facebook, Google, LinkedIn all these sites generates huge amount of data on a day to day basis as they have billions of users worldwide
• E-commerce site: Sites like Amazon, Flipkart, Alibaba generates huge amount of logs from which users buying trends can be traced.
• Weather Station: All the weather station and satellite gives very huge data which are stored and manipulated to forecast weather.
• Telecom company : Telecom giants like Airtel, Vodafone study the user trends and accordingly publish their plans and for this they store the data of its million users.
• Share Market: Stock exchange across the world generates huge amount of data through its daily transaction.

Types Of Big Data

• Structured:- the data that can be stored and processed in a fixed format is called structured data. like table with fixed attribute.
• Unstructured:-the data which has unknown form and cannot be stored in RDBMS and cannot be analyzed unless it is transformed into a structured format is called unstructured data. this type of data usually generated by humans. example:- natural language, voice, twitter posts, Wikipedia etc.
• Semi-structured:- semi structured data is a type of data which does not have a formal structure of a data model, i.e. a table definition in a relational DBMS ,but nevertheless it has some organizational properties like tags and other markers to separate semantic elements that make it easier to analyze. example:- HTML, XML, JSON files etc.

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.

Working Procedure

Hadoop is a framework that allows you to first store Big Data in a distributed environment, so that, you can process it parallel. There are basically three components in Hadoop

• HDFS: (Hadoop distributed File System) it allows us to store data of various formats across a cluster. It states that the files will be broken into blocks and stored in nodes over the distributed architecture.
• YARN: Yet another Resource Negotiator is used for job scheduling and manage the cluster.it is used for for resource management in Hadoop.
• Map Reduce: a parallel processing software framework. This is a framework which helps Java programs to do the parallel computation on data using key value pair. The Map task takes input data and converts it into a data set which can be computed in Key value pair. The output of Map task is consumed by reduce task and then the out of reducer gives the desired result.

Example:-

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Originally published at https://pywix.blogspot.com.