Transformations
Darshini
PySpark is a robust framework for big data processing, offering two main abstractions: RDD (Resilient Distributed Dataset) and DataFrame. Transformations in PySpark are operations applied to these datasets to produce…
Indexing and Query Optimization
Learn how indexing and query optimization can enhance database performance. Explore techniques, tools, and best practices to improve query speed and efficiency. What is Indexing? Indexing is a database optimization…
DDL, DML, TCL, DQL
cheet sheet Welcome to the SQL cheat sheet! This comprehensive guide covers essential SQL commands across different categories: DDL (Data Definition Language), DML (Data Manipulation Language), TCL (Transaction Control Language),…
Normalization and Denormalization
In the world of database management, achieving the right balance between performance and storage efficiency is a critical goal. Two foundational techniques—normalization and denormalization—play a pivotal role in shaping the…
Partitioning and Bucketing
Partitioning and bucketing are essential techniques in big data systems like Hive, Spark, and Hadoop, used to optimize query performance and data management. Both approaches enhance performance, but they serve…
Correlated Subqueries in SQL
Correlated subqueries are a fundamental concept in SQL, widely used for filtering, calculating, and refining data dynamically. These subqueries are “correlated” because they rely on values from the outer query…
SQL
Master Advanced SQL Queries to Ace Your Interviews Are you preparing for SQL-related job interviews? Mastering advanced SQL queries is a game-changer that can set you apart from the competition.…
Query Execution Order
Understanding the order of execution in SQL queries is essential for writing efficient and accurate database operations. SQL (Structured Query Language) processes queries in a specific logical sequence, regardless of…
PySpark vs SQL
PySpark vs SQL: Complete Cheat Sheet for Data Operations Compare PySpark and SQL commands for common DML operations, Group By, Window Functions, and Filters. Learn how to manipulate and analyze…
Python vs SQL
Python vs SQL: Compare Python and SQL commands for DML operations, Group By, Window Functions, and Filters. Learn how SQL subqueries enhance data manipulation and analysis using Python (Pandas, PySpark)…