An Introduction

Big Data & Hadoop

Hadoop is an open source framework. It is provided by Apache to process and analyze very huge volume of data. It is written in Java and currently used by Google, Facebook, LinkedIn, Yahoo, Twitter etc.

Our Hadoop course includes all topics of Big Data Hadoop with HDFS, MapReduce, Yarn, Hive, HBase, Pig, Sqoop etc.

What is Big Data?

Data which are very large in size is called Big Data. Normally we work on data of size MB(WordDoc ,Excel) or maximum GB(Movies, Codes) but data in Peta bytes i.e. 10^15 byte size is called Big Data. It is stated that almost 90% of today’s data has been generated in the past 3 years.

Hadoop Architecture

The Hadoop architecture is a package of the file system, MapReduce engine and the HDFS (Hadoop Distributed File System). The MapReduce engine can be MapReduce/MR1 or YARN/MR2.

A Hadoop cluster consists of a single master and multiple slave nodes. The master node includes Job Tracker, Task Tracker, NameNode, and DataNode whereas the slave node includes DataNode and TaskTracker.

Modules of

Hadoop

  1. HDFS: Hadoop Distributed File System. Google published its paper GFS and on the basis of that HDFS was developed. It states that the files will be broken into blocks and stored in nodes over the distributed architecture.
  2. Yarn: Yet another Resource Negotiator is used for job scheduling and manage the cluster.
  3. Map Reduce: This is a framework which helps Java programs to do the parallel computation on data using key value pair.
  4. Hadoop Common: These Java libraries are used to start Hadoop and are used by other Hadoop modules.
Important

3V's of Big Data

  1. Velocity: The data is increasing at a very fast rate. It is estimated that the volume of data will double in every 2 years.
  2. Variety: Now a days data are not stored in rows and column. Data is structured as well as unstructured. Log file, CCTV footage is unstructured data. Data which can be saved in tables are structured data like the transaction data of the bank.
  3. Volume: The amount of data which we deal with is of very large size of Peta bytes.

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