Why pick range partitioning over hash for an analytics table?

Problem Statement

Explanation

Range partitions let the engine skip entire partitions for queries like last 7 days or Q2 2025, reducing I/O. Hash partitions are better for even distribution of random writes but offer less pruning for temporal scans.

Code Solution

SolutionRead Only

PARTITION BY RANGE (event_date) (p2025q1, p2025q2, ...)

Practice Sets

This question appears in the following practice sets:

Database Sharding & Partitioning

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Why pick range partitioning over hash for an analytics table?

Problem Statement

Explanation

Code Solution

Practice Sets

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Master Interviews Anywhere, Anytime

Why pick range partitioning over hash for an analytics table?

Problem Statement

Explanation

Code Solution

Practice Sets

Related Questions

Which statement best describes the Single Responsibility Principle?

Open–Closed Principle encourages what practice when adding features?

High-Level Design (HLD) typically focuses on which artifacts?

Which UML diagram best captures interactions over time between components?

Which pairing describes a healthy design goal?

More from System Design

Master Interviews
Anywhere, Anytime