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The project orientation is very much unique and it helps to understand the real time scenarios most of the industries are dealing with. And there is no limit, one can go through as many projects... Read More
Recently I became interested in Hadoop as I think its a great platform for storing and analyzing large structured and unstructured data sets. The experts did a great job not only explaining the... Read More
The era of IOT brought with it the need to stream data, process and sometimes display its information in real or near-real time.
In this spark streaming project, we will be using a dataset that passes for real-time data sensor feeds for tracking auto vehicles around the city of Bejing. We will track each vehicle as the signal is received from our streaming simulation (using Flume). We will receive the streams of data using Spark Streaming and use the Redis as a pub/sub middleware.
Furthermore, we will use a java swing based application to display real-time information about all vehicles being tracked. While tracking the vehicle, we will be looking for indexes like current speed, total time and distance covered.
While this spark project is about tracking autos, the principles shared in this big data project will cover wide areas of implementing real-time sensor data processing and much more IOT.
The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture.
In this hadoop project, we are going to be continuing the series on data engineering by discussing and implementing various ways to solve the hadoop small file problem.
In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.