DataBricks  -  Deduplicate Data with Window function and QUALIFY || Remove Duplicate скачать в хорошем качестве

DataBricks  -  Deduplicate Data with Window function and QUALIFY || Remove Duplicate

In this tutorial, you will learn "How to remove Deduplicate Data with Window function and QUALIFY" in DataBricks. Data deduplication is a crucial step in data engineering to ensure clean and accurate datasets. In Databricks (Apache Spark SQL), Window Functions help identify duplicate records by assigning a rank or row number to each row within a partition. Traditionally, ROW_NUMBER() is used along with a subquery or Common Table Expression (CTE) to remove duplicates. With the QUALIFY clause, Databricks simplifies this process by filtering window function results directly in the SQL query, eliminating the need for subqueries. Task - Write a spark solution to remove duplicate entries from the dataset by retaining only the record with the most recent date . Focus on keeping the dataset clean and deduplicated based on the most recent date. ✅ Scenario: Removing Duplicates from a Dataset Assume we have a dataset of customer transactions where duplicate records exist based on the First_Name, Last_Nameand Date. We want to keep only the latest score date for each user. 🎯 Goal: Identify duplicate User (First_Name, Last_Name)entries. Retain only the latest score date per user(based on Date). Your support is greatly appreciated! If you found this article valuable, don’t forget to clap👏, follow✌️, and subscribe❤️💬🔔 to stay connected and receive more insightful content. Let’s grow and learn together! ⭐To learn more, please follow us — http://www.sql-datatools.com ⭐To Learn more, please visit our YouTube channel at —    / sql-datatools   ⭐To Learn more, please visit our Instagram account at —   / asp.mukesh   ⭐To Learn more, please visit our twitter account at —   / macxima   ⭐To Learn more, please visit our Medium account at —   / macxima