1.
About Me
2.
Tokio Tutirial (译)
❱
2.1.
Hello
2.2.
Spawning
2.3.
Shared State
2.4.
Channel
2.5.
I/O
2.6.
Framing
2.7.
Async In Depth
2.8.
Select
2.9.
Streams
3.
Database Internals
❱
3.1.
Storage Engine
❱
3.1.1.
Introduction and Overview
❱
3.1.1.1.
DBMS Architecture
3.1.1.2.
Memory- Versus Disk-Based DBMS
3.1.1.3.
Column- Versus Row-Oriented DBMS
3.1.1.4.
Data Files and Index Files
3.1.1.5.
Buffering Immutability and Ordering
3.1.1.6.
Summary
3.1.2.
BTree Basics
❱
3.1.2.1.
Binary Search Trees
3.1.2.2.
Disk Based Structures
3.1.2.3.
Ubiquitous B-Trees
3.1.2.4.
Summary
3.1.3.
File Format
❱
3.1.3.1.
Motivation
3.1.3.2.
Binary Encoding
3.1.3.3.
General Principles
3.1.3.4.
Page Structure
3.1.3.5.
Slotted Pages
3.1.3.6.
Cell Layout
3.1.3.7.
Combining Cell into Slotted Pages
3.1.3.8.
Managing Variable Size Data
3.1.3.9.
Versioning
3.1.3.10.
Checksumming
3.1.3.11.
Summary
3.1.4.
Implementing BTrees
❱
3.1.4.1.
Page Header
3.1.4.2.
Binary Search
3.1.4.3.
Propagating Splits and Merges
3.1.4.4.
Rebalacing
3.1.4.5.
Right-Only Appends
3.1.4.6.
Compression
3.1.4.7.
Vacuum and Maintenance
3.1.4.8.
Summary
3.1.5.
Transaction Processing and Recovery
❱
3.1.5.1.
Buffer Management
3.1.5.2.
Recovery
3.1.5.3.
Concurrenty Control
3.1.6.
B-Trees Variant
❱
3.1.6.1.
Copy-on-Write
3.1.6.2.
Abstracting Node Updates
3.1.6.3.
Lazy B-Trees
3.1.6.4.
FD-Trees
3.1.6.5.
Bw-Trees
3.1.6.6.
Cache-Oblivious B-Trees
3.1.6.7.
Summary
3.1.7.
Log-Structure Storage
❱
3.1.7.1.
LSM Trees
3.1.7.2.
Read, Write, and Space Amplification
3.1.7.3.
Implemetation Details
3.1.7.4.
Unordered LSM Storage
3.1.7.5.
Concurrency in LSM Trees
3.1.7.6.
Log Stacking
3.1.7.7.
LLAMA and Mindful Stacking
3.1.7.8.
Summary
3.1.8.
Conclusion
3.2.
Distributed Systems
❱
3.2.1.
Introduction and Overview
❱
3.2.1.1.
Concurrent Execution
3.2.1.2.
Fallacies of Distributed Computing
3.2.1.3.
Distributed Systems Abstriction
3.2.1.4.
Two Generals Problem
3.2.1.5.
FLP Impossibility)
3.2.1.6.
System Synchrony
3.2.1.7.
Failure Models
3.2.1.8.
Summary
3.2.2.
Failure Dectection
❱
3.2.2.1.
Heartbeats and Pinga
3.2.2.2.
Phi-Accural Failure Dector
3.2.2.3.
Gossip and Failure Detection
3.2.2.4.
Reversing Failure Detection
3.2.2.5.
Summary
3.2.3.
Leader Election
❱
3.2.3.1.
Bully Algorithm
3.2.3.2.
Next-in-Line Failover
3.2.3.3.
Candidate/Ordinary Optimization
3.2.3.4.
Invitation Algorithm
3.2.3.5.
Ring Algorithm
3.2.3.6.
Summary
3.2.4.
Replication and Consistency
❱
3.2.4.1.
Achieving Availability
3.2.4.2.
Infamous CAP
3.2.4.3.
Shared Memory
3.2.4.4.
Ordering
3.2.4.5.
Consistency Models
3.2.4.6.
Eventual Consistency
3.2.4.7.
Tunable Consistency
3.2.4.8.
Witness Replicas
3.2.4.9.
Strong Eventual Consistency and CRDTs
3.2.4.10.
Summary
4.
Distributed
❱
4.1.
MapReduce (译)
4.2.
Raft (译)
5.
Tracing
❱
5.1.
Concept - Data Source
5.2.
Concept - Instrumenting
5.3.
Concept - Instrumenting Libraries
5.4.
Concept - Data Collection
5.5.
Concept - Distributions
5.6.
Collector - Getting Started
5.7.
Metrics - API
6.
DataStruct
❱
6.1.
sds
6.2.
dict
6.3.
skiplist
6.4.
intset
6.5.
ziplist
7.
Redis
❱
7.1.
1. 基本定义
7.2.
2. 分析起步
7.3.
3. 请求处理
7.4.
4. 执行命令
Light
Rust
Coal
Navy
Ayu
SinSay's Note Book
说明
本章节内容翻译自 OpenTelemetry 官网文档，只为个人学习使用。