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Workings of Hadoop Distributed File System (HDFS)

Analytics Vidhya

Introduction This article will discuss the Hadoop Distributed File System, its features, components, functions, and benefits. Hadoop is a powerful platform for supporting an enormous variety of data applications. Both structured and complex data can […].

Hadoop 208
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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

Research Data Scientist Description : Research Data Scientists are responsible for creating and testing experimental models and algorithms. Key Skills: Mastery in machine learning frameworks like PyTorch or TensorFlow is essential, along with a solid foundation in unsupervised learning methods.

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Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

They allow data processing tasks to be distributed across multiple machines, enabling parallel processing and scalability. It involves various technologies and techniques that enable efficient data processing and retrieval. Stay tuned for an insightful exploration into the world of Big Data Engineering with Distributed Systems!

Big Data 195
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How data engineers tame Big Data?

Dataconomy

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

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Simplify Your Data Engineering Journey: The Essential PySpark Cheat Sheet for Success!

Towards AI

I hope that you have sufficient knowledge of big data and Hadoop concepts like Map, reduce, transformations, actions, lazy evaluation, and many more topics in Hadoop and Spark. Extracting day, month and year from date column: #extract year, month, and day details from the data framedf.select(year("date column").distinct().orderBy(year("date

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How Rocket Companies modernized their data science solution on AWS

AWS Machine Learning Blog

Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools. This also led to a backlog of data that needed to be ingested.