MediaMath Developer Blog Authors

A Picture of Vishnu Viswanath
Vishnu Viswanath Data Engineer at MediaMath

Vishnu Viswanath is a Data Engineer at MediaMath, with over 5 years of experience in designing and building various scalable and efficient systems and has expertise in most of the BigData stacks. He is a relentless tech-enthusiast and likes to keep himself up to date with the technologies in vogue and a keen open source believer and contributor too. When he is not coding his way to “geek” status, he loves traveling and has a serious case of wanderlust.  

A Picture of Vishnu Viswanath
Vishnu Viswanath Data Engineer at MediaMath

Vishnu Viswanath is a Data Engineer at MediaMath, with over 5 years of experience in designing and building various scalable and efficient systems and has expertise in most of the BigData stacks. He is a relentless tech-enthusiast and likes to keep himself up to date with the technologies in vogue and a keen open source believer and contributor too. When he is not coding his way to “geek” status, he loves traveling and has a serious case of wanderlust.  

articles by this author:

Queryable States in ApacheFlink – Part 2: Implementation

This is part 2 of the blog Queryable States in Apache Flink. In the previous blog, we saw how Apache Flink enabled Queryable States. In this part, we will create a Streaming Job with Queryable States and create a QueryClient to query the state. I assume that Flink is already installed and setup. If not you can check out my earlier blog post on installation here. I will be using a Tumbling window in this example, to read about Windows in Flink, please read this blog post. All the code used in this blog post will be available on my GitHub. Creating the Pipeline Let […]

QueryableState in Apache Flink – Part 1

QueryableStates allows users to do real-time queries on the internal state of the stream without having to store the result on to any external storage. This opens up many interesting possibilities since we no longer need to wait for the system to write to the external storage (which has always been one of the main bottlenecks in these kinds of systems). It might be even possible to not have any kind of database and make the user facing applications directly query the stream, which will make the application faster and cheaper. This might not be applicable to all the use […]

Real-time Streaming Attribution Using Apache Flink

// 09.12.2016 // Data

In this blog post, I will share a proof of concept for real-time attribution using Apache Flink from streaming data sources of impressions and events, and how we handled some of the specific problems inherent in windowing and processing real-time data streams at scale. Our goal was to determine if we could use Flink to stream impression and event data so that we could determine attribution in real time in order to optimize advertising strategies immediately. In digital advertising, we refer to ads – whether they are served on social networks, Mobile, Video, or display – as impressions. Once the […]