The article explains how database indexes, built on sorted data and binary search, dramatically reduce query time compared to full table scans, while also covering storage fundamentals, the cost of excessive indexes, clustered indexes, index failure scenarios, and practical SQL optimization techniques.
The article examines how the explosive compute, storage, network, and fault‑tolerance demands of AI large‑model training force a fundamental redesign of system architecture, covering layered storage, optimized All‑Reduce communication, elastic resource orchestration, observability, and cost‑saving strategies.
The article explains the four main categories of computer storage—primary, secondary, tertiary, and offline—detailing their connection to the CPU, typical devices, the concept of direct‑attached storage, and an overview of RAID technology for performance and redundancy.
This article explains how databases store data on various storage media, why indexes dramatically speed up queries through sorted structures and binary search, discusses different index types such as clustered indexes, and outlines common SQL optimization practices while warning against excessive indexing and typical pitfalls.
This article explains the storage hierarchy from CPU registers and caches to RAM, SSD, and HDD, quantifies their speed differences (L1 cache vs. memory, SSD, HDD) and cost ratios, and provides Linux commands to inspect cache sizes, helping readers understand why each level exists and how they interact.
