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How To Fetch Data From Range Partitioning In PostgreSQL || Best PostgreSQL Tutorial Shorts

Автор: Knowledge 360

Загружено: 2025-02-12

Просмотров: 80

Описание: #knowledge360 #akramsohail #akramsohailproject
You Are Hearty Welcomed To My Channel Knowledge 360. Here I post technical videos, mainly related to computer science and programming. I am posting project videos with coding explanations. I make tutorial videos on Technical Topics. Stay Connected, Stay Tuned, and Study Smart.
Knowledge 360 (Akram Sohail)

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Best PostgreSQL Tutorial -    • Best PostgreSQL Tutorial  
Best PostgreSQL Tutorial Shorts -    • PostgreSQL Full Playlist Shorts  

Learn how to fetch data efficiently from Range Partitioning in PostgreSQL! Use partition pruning to speed up queries and improve performance. 🚀

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Watch Complete Video -    • How to Create Partitions in PostgreSQL || ...  
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Description
Fetching data from Range Partitioning in PostgreSQL requires efficient querying techniques to take full advantage of partition pruning and index optimization. In this video, you'll learn the best ways to fetch data efficiently from partitioned tables! 🚀

🔹 What You'll Learn in This Video:
✅ How PostgreSQL retrieves data from range partitions
✅ How to optimize queries for partition pruning
✅ Performance benefits of fetching partitioned data

📌 Fetching Data from a Partitioned Table
When selecting data, PostgreSQL scans only the relevant partitions if partition pruning is enabled.

SELECT * FROM sales WHERE sale_date BETWEEN '2023-01-01' AND '2023-06-30';

📌 Using Indexes on Partitions
Adding indexes to individual partitions can improve query performance:

CREATE INDEX idx_sales_date ON sales_2023_q1 (sale_date);

📌 Partition Pruning for Faster Queries
PostgreSQL automatically skips unnecessary partitions, making queries much faster.

👉 Watch now to master fetching data from Range Partitioning in PostgreSQL and optimize your queries!

#PostgreSQL #SQL #Database #Partitioning #RangePartitioning #QueryOptimization #PostgreSQLTutorial #SQLPerformance #PostgreSQLShorts

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