Category Archives: Streaming

Having Issue How To Order Streamed Dataframe ?


A few days ago, i have to perform aggregation on streaming dataframe. And the moment, i apply groupBy for aggregation, data gets shuffled. Now the situation arises how to maintain order? Yes, i can use orderBy with streaming dataframe using … Continue reading

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Self-Learning Kafka Streams with Scala – #1


A few days ago, I came across a situation where I wanted to do a stateful operation on the streaming data. So, I started finding possible solutions for it. I came across many solutions which were using different technologies like … Continue reading

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Unit Testing Of Kafka


Apache Kafka is a distributed publish-subscribe messaging system and a robust queue that can handle a high volume of data and enables you to pass messages from one end-point to another. Generally, data is published to topic via Producer API … Continue reading

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Meetup: Stream processing using Kafka


Knoldus organized a Meetup on Friday, 7th April 2017 at 4:00 PM which was presented by Himani Arora and me(Prabhat Kashyap). Topics which were covered in this meetup: What is Stream processing Advantages of stream processing Type of stream processing What are KStreams Use cases … Continue reading

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Integrating Kafka With Spark Structure Streaming


Kafka is a messaging broker system which facilitates the passing of messages between producer and consumer whereas Spark Structure streaming consumes static and streaming data from various sources like kafka, flume, twitter or any other socket which can be processed … Continue reading

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Spark Structured Streaming: A Simple Definition


“Structured Streaming”, nowadays we are hearing this term in Apache Spark ecosystem quite a lot, as it is being preached as next big thing in scalable big data world. Although, we all know that Structured Streaming means a stream having … Continue reading

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Exploring Spark Structured Streaming


Hello Spark Enthusiasts, Streaming apps are growing more complex. And it is getting difficult to do with current distributed streaming engines. Why streaming is hard ? Streaming computations don’t run in isolation. Data arriving out of time order is a … Continue reading

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Spark Streaming vs Kafka Stream


The demand for stream processing is increasing a lot these days. The reason is that often processing big volumes of data is not enough. Data has to be processed fast, so that a firm can react to changing business conditions … Continue reading

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Streaming in Spark, Flink and Kafka


There is a lot of buzz going on between when to use use spark, when to use flink, and when to use Kafka. Both spark streaming and flink provides exactly once guarantee that every record will be processed exactly once … Continue reading

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Introducing Kafka Streams: Processing made easy


If you are working on huge amount of data, you might have heard about Kafka. At a very high level, Kafka is a fault tolerant, distributed publish-subscribe messaging system that is designed for fast processing of data and the ability … Continue reading

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