What are Big Data, Hadoop & Spark ? What is the relationship among them ?

What are Big Data, Hadoop & Spark ? What is the relationship among them ?

What are Big Data, Hadoop & Spark ? What is the relationship among them ?  Awantik Das
Posted on May 22, 2017, 12:23 p.m.

big data hadop and spark

Big Data - Big Data is a problem statement & what it means is size of data under process has grown to 100's of petabytes ( 1 PB = 1000TB ). Yahoomail generates some 40-50 PB of data everyday. Yahoo has to read those 40-50  PB of data & filter out spans. E-commerence websites generates logs for each shopping & window-shopping. Trust me, window-shopping data are more important for business. Retail store - which products to place next to each other. Processing bills of all buyers & finding relations between each products. Classic case of - Beer & Diper falls under this category. Machine learing can produce fantastic results, if large amount of data can be processed.

Hadoop - This is a solution to big data problems. It provides distributed storage & distributed computing framework. Distributed Storage - By 2015, you can store max. upto 16 TB in one system. If data size is beyond 16 TB, usually it's in order of Peta Bytes. The only way to store such huge amount of data is breaking the data into chunks & storing in distributed systems. Distributed Processing - Data is stored in physically different systems, we can make happen parallel processing on each of the nodes ( system ) & thus leveraging computation power of ech nodes. Hadoop consist of 3 major things - HDFS, YARN & MapReduce. HDFS is all about distributed file system, it break down the data & maps node for each data request. MapReduce - This defines the functions - mapper & reducer. Mapper - Function that executes on each node. Provides parallelism to the application. Reducer - The piece of code which cannot be parallelized is done by reducer & it executes in only one node. YARN  picks the function and executes on each node.

Spark - On current scenario, Hadoop mostly focuses on storing large scale of data. We can see Spark as something which can do fast computation.We generally see Hadoop as underlying storage infrastructure. Spark as a superfast computation framework usually 10X - 50X faster. Apart from Hadoop, Spark can use other technologies to provide distributed storage framework

Awantik Das is a Technology Evangelist and is currently working as a Corporate Trainer. He has already trained more than 3000+ Professionals from Fortune 500 companies that include companies like Cognizant, Mindtree, HappiestMinds, CISCO and Others. He is also involved in Talent Acquisition Consulting for leading Companies on niche Technologies. Previously he has worked with Technology Companies like CISCO, Juniper and Rancore (A Reliance Group Company)

Keywords : spark data-science hadoop

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