Category Archives: apache spark

Apache Hadoop vs Apache Spark


The term Big Data has created a lot of hype already in the business world. Hadoop and Spark are both Big Data frameworks – they provide some of the most popular tools used to carry out common Big Data-related tasks. … Continue reading

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Assimilation of Spark Streaming With Kafka


As we know Spark is used at a wide range of organizations to process large datasets. It seems like spark becoming main stream. In this blog we will talk about Integration of Kafka with Spark Streaming. So, lets get started. How Kafka … Continue reading

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What’s new in Apache Spark 2.2


Apache recently released a newer version of Spark i.e Apache Spark2.2. The new version comes with new improvements as well as the addition of new functionalities. The major addition to this release is Structured Streaming. It has been marked as production … Continue reading

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Deep Dive into Spark Cluster Managers


This blog aims to dig into the different Cluster Management modes in which you can run your spark application. Spark applications run as independent sets of processes on a cluster, coordinated by the SparkContext object in your main program which … Continue reading

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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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Difference between RDD , DF and DS in Spark


In this blog I try to cover the difference between RDD, DF and DS. much of you have a little bit confused about RDD, DF and DS. so don’t worry after this blog everything will be clear. With Spark2.0 release, … 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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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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