I have recently uploaded a video on my YT channel where we dive into an incredibly popular PySpark feature that’s frequently asked about in interviews: the ๐๐๐ฅ๐ญ๐ ๐๐๐๐ฅ๐!
Delta Tables have become a game-changer in big data analytics, especially for cloud-based data platforms. Developed by Databricks and now open-source, Delta Tables offer fantastic features like Time Travel, schema evolution, and in-built ACID properties.
In this video, we walk through:
1. ๐๐๐ญ๐ญ๐ข๐ง๐ ๐๐ฉ ๐ ๐๐๐ฅ๐ญ๐ ๐๐๐๐ฅ๐: Using a simple DataFrame in Azure Databricks, weโll create a Delta Table in the Hive Metastore.
2. ๐๐ง๐ญ๐๐ซ๐ฏ๐ข๐๐ฐ ๐๐ฉ๐จ๐ญ๐ฅ๐ข๐ ๐ก๐ญ:ย We tackle a key interview question: “How to create Delta Tables with friendly column names?” This involves handling spaces and special characters in column namesโa common requirement for making data more understandable and usable in reports and dashboards.
3. ๐๐ซ๐๐๐ญ๐ข๐๐๐ฅ ๐๐ฉ๐ฉ๐ซ๐จ๐๐๐ก๐๐ฌ:
โ ๐๐ซ๐๐๐ญ๐ข๐ง๐ ๐๐ข๐๐ฐ๐ฌ: Transform standard columns to friendly names via views based on Delta Tables.
โ ๐๐จ๐ฅ๐ฎ๐ฆ๐ง ๐๐๐ฉ๐ฉ๐ข๐ง๐ ๐ ๐๐๐ญ๐ฎ๐ซ๐: Utilize Databricksโ new column mapping feature to directly create Delta Tables with user-friendly column names.
๐ Check out the full video for a detailed walk-through and see these methods in action! Whether youโre prepping for an interview or looking to optimize your data workflows, this guide will be super helpful.
๐กย ๐๐๐ฒ ๐๐๐ค๐๐๐ฐ๐๐ฒ:ย Views are great for existing Delta Tables, ensuring compatibility and minimal disruption. For new tables, leveraging column mapping can streamline your setup, provided you consider the featureโs limitations.
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Letโs make data work smarter for us! Cheers! ๐ฅ
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Watch the video here!!
