Uber Interview Experience/Asking Suggestions

This page summarizes the projects mentioned and recommended in the original post on /r/dataengineering

Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers
Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
www.nutrient.io
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Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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  1. system-design-primer

    Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

    System design interviews can definitely be tough especially if weren't expecting one or haven't had one before. I'd recommend you check out this system design interview GitHub repo, it'll help you get the basics down for system design interviews.

  2. Nutrient

    Nutrient – The #1 PDF SDK Library, trusted by 10K+ developers. Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.

    Nutrient logo
  3. SparkInternals

    Notes talking about the design and implementation of Apache Spark

    If you're looking to better understand execution plans for spark I'd start by reading Spark the Definitive Guide, it's a bit higher level and broader than I'd like but will give you a good overview of spark's design. If you don't want to get a book this is repo does a good job breaking down how spark develops physical and logical plans https://github.com/JerryLead/SparkInternals.

  4. Apache Spark

    Apache Spark - A unified analytics engine for large-scale data processing

    One place to look are the projects repo's and docs, once you have a good idea of how the system is architected poking around pieces of the codebase can be helpful in letting you really understand their internals. I personally enjoy going through spark repo and trino repo and the documentation for both projects is decent and can answer many of your questions.

  5. Trino

    Official repository of Trino, the distributed SQL query engine for big data, former

    One place to look are the projects repo's and docs, once you have a good idea of how the system is architected poking around pieces of the codebase can be helpful in letting you really understand their internals. I personally enjoy going through spark repo and trino repo and the documentation for both projects is decent and can answer many of your questions.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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