Frequently Faced Challenges in Implementing Spark Code in Data Engineering Pipelines

Pyspark has become one of the most popular tools for data processing and data engineering applications. It is a fast and efficient tool that can handle large volumes of data and provide scalable data processing capabilities. However, Pyspark applications also come with their own set of challenges that data engineers face on a day-to-day basis. In this article, we will discuss some of the common challenges faced by data engineers in Pyspark applications and the possible solutions to overcome these challenges.

1. Serialization Issues in Pyspark

Serialization issues in PySpark are a common problem that can lead to slow and inefficient processing. This article will discuss what serialization is, why it is important, and how to identify and resolve serialization issues in PySpark.

Build an Advanced RAG App: Query Rewriting
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In the last article, I established the basic architecture for a basic RAG app. In case you missed that, I recommend that you first read that article. That will set the base from which we can improve our RAG system. Also in that last article, I listed s... […]
Contexts in Go: A Comprehensive Guide
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Contexts in Go provide a standard way to pass metadata and control signals between goroutines. They are mainly used to manage task execution time, data passing, and operation cancellation. This article covers different types of contexts in Go and examp... […]
Next-Gen Lie Detector: Stack Selection
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The first lie detector which relied on eye movement appeared in 2014. The Converus team together with Dr. John C. Kircher, Dr. David C. Raskin, and Dr. Anne Cook launched EyeDetect — a brand-new solution to detect deception quickly and accurately. This... […]
Applying the Pareto Principle To Learn a New Programming Language
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In this article, I will discuss how you can apply the Pareto principle to quickly learn a new programming language and start solving real-world problems while you develop a deeper understanding of the programming language. What Is the Pareto Principle?... […]
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Whether on the cloud or setting up your AIOps pipeline, automation has simplified the setup, configuration, and installation of your deployment. Infrastructure as Code(IaC) especially plays an important role in setting up the infrastructure. With IaC t... […]