This project analyzes home sales data using PySpark and SparkSQL to extract insights, optimize query performance with caching, and enhance storage efficiency through data partitioning.
-
Updated
Nov 27, 2024 - Jupyter Notebook
This project analyzes home sales data using PySpark and SparkSQL to extract insights, optimize query performance with caching, and enhance storage efficiency through data partitioning.
This repository is a comprehensive Nuxt 3 boilerplate that streamlines frontend development by providing an organized directory structure and integrating powerful tools such as ESLint, Prettier, lint-staged, Husky, and TypeScript. It's your go-to starting point for building modern and performant web applications with Nuxt 3.
The Netflix project describes about the netflix clone, where the users can view latest, popular movies and also can search for an movies
π² Let's Play Rock, Paper, Scissors! π
Add a description, image, and links to the performanceoptimization topic page so that developers can more easily learn about it.
To associate your repository with the performanceoptimization topic, visit your repo's landing page and select "manage topics."