This book aims to showcase the power, performance, and unique programming elegance of DolphinDB through real-world data analysis use cases. The content is structured progressively across 14 chapters, divided into three main parts.
Part I: Foundations (Chapters 1-2)
Designed for newcomers, this section introduces DolphinDB's core programming elements—data types, structures, control statements, and operators—providing the essential foundation for quick adoption.
Part II: Data Analysis and Visualization (Chapters 3-8)
This part explores practical analytics applications. Chapter 3 covers data cleaning and preparation techniques. Chapter 4 examines DolphinDB's windowing capabilities, showing how to leverage various window functions for sophisticated analysis. Chapters 5 and 6 showcase two pillars of DolphinDB's multi-paradigm approach—functional and SQL programming—through hands-on examples that highlight the language's versatility. Chapter 7 demonstrates building low-latency real-time applications using DolphinDB's streaming framework. Chapter 8 presents DolphinDB's visualization tools and integration with external visualization platforms.
Part III: Advanced Applications (Chapters 9-14)
The final part tackles sophisticated implementations. Chapter 9 explores parallel and distributed computing strategies. Chapter 10 details methods for importing and exporting diverse data formats. Chapter 11 examines DolphinDB's just-in-time (JIT) compilation for iterative and streaming computations. Chapter 12 focuses on statistical analysis and optimization features. Chapter 13 covers machine learning and AI model support, including GPU-accelerated computing applications. Chapter 14 concludes with interoperability solutions for integrating DolphinDB with platforms like Python and Excel.