Author: Anmol Sarna

Is Apache Flink the future of Real-time Streaming?

In our last blog, we had a discussion about the latest version of Spark i.e 2.4 and the new features that it has come up with. While trying to come up with various approaches to improve our performance, we got the chance to explore one of the major contenders in the race, Apache Flink. Apache Flink is an open source platform which is a streaming Continue Reading

kafka with spark

Apache Spark 2.4: Adding a little more Spark to your code

Continuing with the objectives to make Spark faster, easier, and smarter, Apache Spark recently released its fifth release in the 2.x version line i.e Spark 2.4. We were lucky enough to experiment with it so soon in one of our projects. Today we will try to highlight the major changes in this version that we explored as well as experienced in our project. In our Continue Reading

Alpakka – Connecting Kafka and ElasticSearch to Akka streams

In our previous blog, we had a look at what Akka streams are and how they are different from the other streaming mechanisms we have. In this blog, we will be taking a little step forward into the world of Akka Streams. In order to work with Akka streams, we need a mechanism to connect Akka Streams to the existing system components. That is where Alpakka Continue Reading

Akka Streams: Is it a Solution to Your Streaming Problems?

A few days earlier, in our project, we were using Spark streaming and initially, it worked like a charm. But as we were very close to completion of our use case, the unexpected occurred. Spark does have a lot of interesting features, but we had some more custom needs such as running a ton of varying jobs with different actors/flows. Also, we needed something which Continue Reading

Is Apache Cassandra really the Database you need?

Welcome back, everyone. It has been quite some time since I have been working with Cassandra. To be honest, it is a quite cool database. Its decentralized nature, as well as its ability to handle such a large volume of writes, is really commendable. But as we know nothing is perfect. So is the Cassandra Database. What I mean by this is that you cannot Continue Reading

CuriosityX: RDDs – The backbone of Apache Spark

In our last blog, we tried to understand about using the spark streaming to transform and transport data between Kafka topics. After reading that many of the readers asked us to give a brief description of RDDs in Spark which we used. So, this blog is totally dedicated to the RDDs in Spark. So let’s start with the very basic question that comes to our mind Continue Reading

Code Combat II : The Code Battle For The Vanguard Continues…

“If you can dream it, you can do it. ”  -Walt Disney For some coding is a job. For some, it is an exercise. But for us folks here at Knoldus, it’s a Passion. So in order to bring a twist in the daily work schedule, Knoldus held an overnight Hackathon competition within the organization on 18th May 2018 which presented an opportunity for every Knolder(employees Continue Reading

Do you think your code is Perfect? Well, Think again.

“Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” – Martin Fowler “I can code.” I always say to myself. But do others think the same? Is my code good enough for people to understand? Do other people think “Damn I wish I could write such code.?” –  that’s the main question I always had in Continue Reading

A Simple walk-through to set up a local Cassandra multi-node cluster

In our earlier blogs we have already gone through The basic Introduction to Cassandra and also tried to explore the Cassandra Reads and Writes. Today we will be discussing something apart from the in-depth theoretical knowledge of Cassandra. In one of our projects , we came through a basic requirement in which we needed to required a local Cassandra cluster for some kind of testing.  Continue Reading

Is Shifting to Domain Driven Design worth your Efforts?

In our earlier blog, we explored a bit about Microservices. But let’s take a step back and look into how microservices can be effectively designed. Yes, you guessed it right. We will be talking about the Domain Driven Design or what we call the DDD approach. But before jumping into the concepts of Domain Driven Design, let’s understand 2 basic terminologies : Domain: A domain is the sphere Continue Reading

Kafka And Spark Streams: The happily ever after !!

Hi everyone, Today we are going to understand a bit about using the spark streaming to transform and transport data between Kafka topics. The demand for stream processing is increasing every day. The reason is that often, processing big volumes of data is not enough. We need real-time processing of data especially when we need to handle continuously increasing volumes of data and also need Continue Reading

“Why do you always choose Microservices over me?” said the Monolithic architecture

Ever wondered why do companies like Apple, eBay and Netflix care so much about microservices? What makes this simple architecture so special that it is being hyped so much? Is it worth the pain and efforts to shift an entire running application from monolithic to microservices architecture? Many such questions came to our minds when we started using the microservices in our projects. In this Continue Reading

The curious case of Cassandra Reads

In our previous blog, we discovered how Cassandra handles its write queries. Now it’s time to understand how it ensures all the read requests are fulfilled. Let’s first have an overall view of Cassandra. Apache Cassandra is a free and open-source distributed NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of Continue Reading

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