This article explores five sophisticated data structures—B‑Tree, Radix Tree, Rope, Bloom Filter, and Cuckoo Hash—explaining their design, typical use cases, and why they outperform classic structures when handling massive scale, high‑speed lookups, or complex data manipulation.
This article explains why using Redis List for a message queue is limited, introduces Redis Stream as a purpose‑built MQ with consumer groups, ACKs, and persistence, and dives into its internal Radix‑Tree and listpack structures, command usage, and memory‑saving techniques.
This article explains the Linux kernel's transition from bitmap‑based PID allocation to a radix‑tree (IDR) implementation, describes the underlying data structures and code changes, and presents benchmark results showing roughly a 50% performance improvement for common utilities.
This article analyzes and compares the routing matching processes of the open‑source API gateways APISIX and Kong, detailing their initialization, rule generation, categorization, matching algorithms, performance testing, and concluding why APISIX's radix‑tree approach yields higher efficiency.
The Linux kernel’s page‑cache indexing migrated from the classic radix‑tree structure—using shift‑based multi‑way nodes, RCU‑protected insert, lookup, and delete operations—to the newer XArray API introduced in 4.20, which retains the radix layout while offering automatic resizing, built‑in locking, richer marking, and a cleaner, safer interface.
