
The Implementation of Stream Architecture for Handling Big Data Velocity in Social Media
Author(s) -
Faqih Hamami,
Iqbal Ahmad Dahlan
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1641/1/012021
Subject(s) - nosql , big data , computer science , architecture , social media , the internet , process (computing) , database , data stream , data science , unstructured data , world wide web , data mining , operating system , geography , telecommunications , archaeology
Big data is a term of complex data and difficult to process. It consists of several characteristics called 6 Vs. Many applications generate huge data and grow rapidly in seconds. This kind of data comes from many sources such as social media, Internet of Things, log system, e-commerce and so on. This rapid data should be handled with a different approach in big data solutions. This paper proposes to create stream architecture for big data velocity with open source technologies such as Apache Kafka and NoSQL database. The implementation is to handle massive incoming data from social media with specific keywords from Twitter and ingested to NoSQL Database though stream architecture. Historical data then processed to gain valuable insight for better information.