# Core Data Structures Covered in the architect-awesome Knowledge Base

> Explore core data structures like queues, sets, lists, maps, stacks, and trees in the architect-awesome knowledge base. A key resource for backend architects.

- Repository: [xingshaocheng/architect-awesome](https://github.com/xingshaocheng/architect-awesome)
- Tags: overview
- Published: 2026-03-05

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**The architect-awesome knowledge base documents eight essential data structure categories—queues, sets, lists, maps, stacks, trees (binary, balanced, B-trees, LSM), and BitSets—within its [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md) "数据结构" section, serving as a foundational reference for backend architects.**

The architect-awesome repository serves as a curated knowledge collection for backend architects, organizing essential computer science concepts into the [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md) document. Within this file, the **"数据结构"** (Data Structures) section provides a comprehensive index of language-agnostic structures critical for system design. This guide examines each core data structure documented in the repository, referencing specific implementations and architectural use cases as cataloged in the source.

## Linear Collections: Queue, Stack, List, and Set

The knowledge base groups fundamental linear structures together in [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md), emphasizing their operational characteristics and Java ecosystem implementations.

### Queue (队列)

In the [Queue](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E9%98%9F%E5%88%97) section, the repository defines this **FIFO** (First-In-First-Out) collection as essential for task scheduling and producer-consumer pipelines. The documentation cites Java implementations including non-blocking `ConcurrentLinkedQueue` and blocking variants such as `ArrayBlockingQueue`, `LinkedBlockingQueue`, `DelayQueue`, and `PriorityBlockingQueue`.

### Stack (栈)

Documented in the [Stack](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E6%A0%88) subsection as a **LIFO** container, the knowledge base notes that while Java provides a synchronized `Stack` class, modern implementations prefer `ArrayDeque` for superior performance in single-threaded stack operations. Typical applications include call-stack simulation, back-tracking algorithms, and expression evaluation.

### List and Array (链表、数组)

The [List / Array](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E9%93%BE%E8%A1%A8%E3%80%81%E6%95%B0%E7%BB%84) section catalogs ordered, index-addressable sequences including Java's `ArrayList`, `LinkedList`, and primitive arrays. These structures support random access patterns and dynamic resizing scenarios required for ordered data processing.

### Set (集合)

The [Set](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E9%9B%86%E5%90%88) section covers unordered collections of unique elements, referencing Java's `HashSet`, `TreeSet`, and `LinkedHashSet` implementations. Primary use cases include deduplication, membership testing, and identifier caching.

## Associative Containers: Map (字典、关联数组)

The [Map](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E5%AD%97%E5%85%B8%E3%80%81%E5%85%B3%E8%81%94%E6%95%B0%E7%BB%84) section documents key-value associative containers fundamental to fast lookups and indexing. The knowledge base references Java implementations including `HashMap` for average O(1) operations, `TreeMap` for sorted keys (backed by red-black trees), and `ConcurrentHashMap` for thread-safe concurrent access.

## Hierarchical Structures: The Tree Family

The architect-awesome repository extensively documents tree-based structures under dedicated subsections in [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md), ranging from basic binary trees to disk-optimized storage engines.

### Binary Tree (二叉树)

The foundational [Binary Tree](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E4%BA%8C%E5%8F%89%E6%A0%91) represents the hierarchical model where nodes contain up to two children, suitable for simple expression trees and hierarchical data modeling.

### Complete Binary Tree (完全二叉树)

Defined in the [Complete Binary Tree](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E5%AE%8C%E5%85%A8%E4%BA%8C%E5%8F%89%E6%A0%91) section as trees where all levels are filled except possibly the last (which is left-justified), this structure serves as the theoretical basis for heap implementations and array-based tree representations.

### Balanced Binary Tree (平衡二叉树)

The [Balanced Binary Tree](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E5%B9%B3%E8%A1%A1%E4%BA%8C%E5%8F%89%E6%A0%91) entry describes trees maintaining a height difference of ≤1 between subtrees (such as AVL trees), guaranteeing O(log n) operation bounds for search, insertion, and deletion.

### Binary Search Tree (BST) (二叉查找树)

The [BST](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E4%BA%8C%E5%8F%89%E6%9F%A5%E6%89%BE%E6%A0%91) section covers ordered binary trees where left < node < right, providing average O(log n) lookup performance for dynamic datasets.

### Red-Black Tree (红黑树)

Documented as self-balancing BSTs with color properties ensuring O(log n) height bounds, the [Red-Black Tree](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#%E7%BA%A2%E9%BB%91%E6%A0%91) section notes these underpin Java's `TreeMap` and `TreeSet` implementations.

### B-Tree, B+ Tree, and B* Tree (B，B+，B*树)

The [B-Tree family](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#b-b%2B-%E6%A0%91) entry describes multi-way balanced trees optimized for disk-based storage systems. The knowledge base identifies these as the primary indexing structures in MySQL, PostgreSQL, and other database management systems.

### LSM Tree (LSM 树)

The [LSM Tree](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#lsm-%E6%A0%91) (Log-Structured Merge Tree) batches writes in memory before flushing to disk, optimizing for write-heavy workloads. The repository cites applications in HBase, LevelDB, and RocksDB storage engines.

## Bit-Level Primitives: BitSet

The [BitSet](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#bitset) section documents compact bitmap structures for large-scale existence checks and flag arrays. These primitives enable memory-efficient deduplication patterns similar to Bloom filters.

## Practical Java Implementation Reference

The architect-awesome knowledge base provides practical usage patterns for each structure. Below are representative implementations mapping directly to the documented categories:

```java
// Queue – non-blocking, unbounded
Queue<String> q = new ConcurrentLinkedQueue<>();
q.offer("task1");
String head = q.poll();               // "task1"

// Set – deduplication
Set<Integer> uniq = new HashSet<>(List.of(1,2,2,3));
System.out.println(uniq);             // [1, 2, 3]

// List / Array – random access
List<String> list = new ArrayList<>();
list.add("a"); list.add("b");
System.out.println(list.get(1));      // "b"

// Map – fast key lookup
Map<String, Integer> map = new HashMap<>();
map.put("one", 1);
System.out.println(map.get("one"));   // 1

// Stack – LIFO (ArrayDeque is preferred)
Deque<Integer> stack = new ArrayDeque<>();
stack.push(10);
stack.push(20);
System.out.println(stack.pop());       // 20

// Binary Search Tree – using TreeMap (red-black tree)
TreeMap<Integer, String> bst = new TreeMap<>();
bst.put(5, "five"); bst.put(2, "two"); bst.put(8, "eight");
System.out.println(bst.floorKey(6)); // 5

// LSM Tree – typical usage via RocksDB (illustrative only)
// RocksDB db = RocksDB.open("path/to/db");
// db.put("k".getBytes(), "v".getBytes());

// BitSet – fast presence test
BitSet bits = new BitSet();
bits.set(5);
System.out.println(bits.get(5));      // true

```

Each snippet corresponds to structures cataloged in the repository's [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md) under their respective "数据结构" subsections.

## Summary

- The architect-awesome knowledge base organizes **eight major data structure categories** in [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md): queues, sets, lists/arrays, maps, stacks, binary trees, advanced balanced trees (including B-trees and LSM), and BitSets.
- All structures are documented in the **"数据结构"** section with Java-centric implementations but language-agnostic architectural principles.
- The repository emphasizes **backend system design** applications, from in-memory caching (`HashMap`) to disk-optimized storage (B+ Trees, LSM Trees).
- Each entry includes **specific implementation classes** (e.g., `ConcurrentLinkedQueue`, `ArrayDeque`, `TreeMap`) and **performance characteristics** essential for architectural decision-making.

## Frequently Asked Questions

### What are the core data structures covered in the architect-awesome knowledge base?

The repository covers eight essential categories: **Queue** (FIFO collections), **Set** (unique element collections), **List/Array** (ordered sequences), **Map** (key-value associations), **Stack** (LIFO containers), **Tree** hierarchies (binary, complete, balanced, BST, red-black, B-trees, and LSM trees), and **BitSet** (compact bitmaps). All are documented in the [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md) "数据结构" section with practical Java examples.

### Does the architect-awesome repository focus on specific programming languages?

While the knowledge base uses **Java** as the primary reference implementation (citing classes like `HashMap`, `ArrayDeque`, and `ConcurrentHashMap`), the architectural concepts are **language-agnostic**. The structures apply equally to C++, Go, Python, or other backend languages, with the Java examples serving as concrete illustrations of abstract data type behavior.

### How does the repository organize its data structure documentation?

All structures are grouped under a dedicated **"数据结构"** (Data Structures) heading in the root [`README.md`](https://github.com/xingshaocheng/architect-awesome/blob/main/README.md) file. The organization follows a logical progression from simple linear collections (queues, stacks) to complex hierarchical structures (B-trees, LSM trees), with direct anchor links to each subsection for quick navigation.

### What distinguishes the tree documentation in architect-awesome from basic algorithm references?

The repository goes beyond fundamental binary trees to document **production-grade storage structures** including B+ Trees for database indexing and LSM Trees for write-optimized storage engines. This reflects the knowledge base's target audience of backend architects designing high-performance persistence layers rather than general software developers implementing basic in-memory trees.