- Scala for Data Science
- Pascal Bugnion
- 102字
- 2021-07-23 14:33:08
Summary
By providing high-level concurrency abstractions, Scala makes writing parallel code intuitive and straightforward. Parallel collections and futures form an invaluable part of a data scientist's toolbox, allowing them to parallelize their code with minimal effort. However, while these high-level abstractions obviate the need to deal directly with threads, an understanding of the internals of Scala's concurrency model is necessary to avoid race conditions.
In the next chapter, we will put concurrency on hold and study how to interact with SQL databases. However, this is only temporary: futures will play an important role in many of the remaining chapters in this book.
推薦閱讀
- Getting Started with React
- vSphere High Performance Cookbook
- JavaScript 網頁編程從入門到精通 (清華社"視頻大講堂"大系·網絡開發視頻大講堂)
- Troubleshooting PostgreSQL
- BIM概論及Revit精講
- 批調度與網絡問題的組合算法
- RubyMotion iOS Develoment Essentials
- MySQL 8從零開始學(視頻教學版)
- ANSYS FLUENT 16.0超級學習手冊
- Mastering PostgreSQL 11(Second Edition)
- Opa Application Development
- Web應用程序設計:ASP
- 思維黑客:讓大腦重裝升級的75個超頻用腦法
- C程序員從校園到職場
- 架構真意:企業級應用架構設計方法論與實踐