內行人才知道的系統設計面試指南. 第二集 (1版)

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【簡介】 內容簡介:🏆 Amazon.com ★★★★★1200+ 則五星評價，IT類連續三年霸榜雙榜首📌 FAANG 級別的系統設計面試攻略，全面強化技術與應試實力📌 漸進式解題架構×豐富實戰案例，自信迎戰高階技術面試📌 全彩印刷×心智圖總結，歸納解題重點與脈絡這本書非常出色！是第一本書的精彩延續。我強烈推薦給所有正在準備系統設計面試的人。—— Sunny Patel，微軟軟體工程經理我曾在 FAANG 擔任技術主管，但當要快速理解某些不熟悉的領域時，我還是需要一些協助。 如果你投入時間學習，本書可以在你討論到系統瓶頸與替代方案時，協助你獲得許多兼具廣度與深度的知識，而這正是大家對於技術主管的期待。—— Herbert Degano，Coinbase 資深軟體工程師本書為《內行人才知道的系統設計面試指南》的續作，收錄全新的系統設計面試問題與解決方案。但無須閱讀過前冊也可以輕鬆理解並受益於本書的內容。具備分散式系統基礎知識的讀者更能順利閱讀本書。本書提供了一套可靠的策略與知識庫，幫助您應對各種系統設計問題，使您在關鍵面試中更具信心。此外，本書建立了一套循序漸進的解題架構，透過豐富的真實案例，詳細解析系統設計方法，搭配清晰易懂的步驟，讓您能夠有效掌握解題思路。本書包含以下內容：．面試官想從答題中看到的真正重點，以及其中內行人才懂的門道。．用來解決任何系統設計面試問題的四步驟框架。．13道真實的系統設計面試問題及詳細解決方案。．300+個直觀圖表，以視覺化方式解釋不同系統的運作原理。來自讀者的讚譽👍「對通過senior+級別的面試非常有幫助」「優質內容，對通過FANNG+的系統設計面試輪有很大的幫助」「軟體工程師都應該看這本書」「對於需要準備系統面試的人而言，這本書很值得一看！」「不僅對面試有幫助，對日常的實際設計也很有用，是最好的系統設計書」「用大量的圖表和簡單易懂的方式解說觀念，看完一定會有收獲」「除了書中發現的大量例子之外，對我來說最重要的方面是向面試官展示設計的正式方法」「不僅有利於面試準備，而且有足夠的技術深度，非常實用，可以作為日常工作的靈感來源」「準備系統設計面試的最佳資源，讓我更有信心」 【目錄】 章節說明:第1章：附近的場所 第2章：人在附近的朋友 第3章：Google 地圖 第4章：分散式訊息佇列 第5章：指標監控警報系統 第6章：廣告點擊事件彙整 第7章：飯店預訂系統 第8章：分散式 Email 服務 第9章：類似 S3 的物件儲存系統 第10章：即時遊戲排行榜 第11章：支付系統 第12章：數位錢包 第13章：證券交易所後記

COMPREHENSIVE SUMMARY OF THE BENFORD\'S LAW PHENOME

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Numbers are written in our digital language system by conveniently and efficiently utilizing the ten digits 0 to 9 in much the same way as sentences and books are written in the English language system by conveniently utilizing the 26 letters A to Z. Surprisingly, and against all common sense or intuition, the spread of these ten digits within numbers of random data is not uniform, but rather highly uneven. Benford's Law predicts that the first digit on the left-most side of numbers is proportioned between all possible digits 1 to 9 approximately according to LOG(1 + 1/digit), so that occurrences of low digits such as {1, 2, 3} in the first position are much more frequent than occurrences of high digits such as {7, 8, 9}. Remarkably, Benford's Law is found to be valid in almost all real life statistics, from data relating to physics, astronomy, chemistry, geology, and biology to data relating to economics, accounting, finance, engineering, and governmental census information. Therefore, Benford's Law stands as the only common thread running through and uniting all scientific disciplines! This book represents an intense and concentrated effort by the author to narrate this digital, numerical, and quantitative story of the Benford's Law phenomenon as briefly and as concisely as possible, while still ensuring a comprehensive coverage of all its aspects, results, causes, explanations, and perspectives. The most recent research results and discoveries in this field are included within this book in such a way as to be comprehensible and engaging to readers of all proficiencies. Errata(s) Errata (177 KB) Sample Chapter(s) Sample of Section I: The Digits Phenomenon Contents: About the Author Introduction The Digits Phenomenon: The First Digit on the Left Side of Numbers Benford's Law and the Predominance of Low Digits Second-Digits and Third-Digits Distributions The Quantitative Origin of the Digital-Numerical Phenomenon The Scale Invariance Principle The Base Invariance Principle Physical Order of Magnitude of Data Robust Measure of Physical Order of Magnitude Two Essential Requirements for Benford Behavior Sum of Squared Deviations Measure The Mistaken Use of the Chi-Square Test in Benford's Law Causes and Explanations: Multiplication Processes Lead to Positive Skewness and Often to Benford Addition Processes Lead to the Symmetrical Normal away from Benford The Multiplicative Central Limit Theorem and Lognormal Distribution Multiplications are More Prevalent than Additions in Real-Life Data Tugs of War between Addition and Multiplication Partitions Typically Lead to Positive Skewness and Often to Benford One-Dimensional Random Staged Partition One-Dimensional Chaotic Repeated Partition One-Dimensional Random Real Partition Two-Dimensional Random Partition The General Requirements for Partitions to Converge to Benford Benford Model for Planet and Star Formations Consolidation and Fragmentation Processes Random Exponential Growth Leads to Positive Skewness and Benford Data Aggregation Leads to Positive Skewness and Often to Benford Chains of Statistical Distributions and Benford's Law Meta-Explanation or the Explanation of all Explanations The Logarithmic Perspective: Benford's Law as Uniformity of Mantissa Rising or Falling Mantissa Distributions Uniqueness of k/x Distribution and Its Central Role in Benford's Law Related Log Conjecture The Random and Deterministic Flavors in Benford's Law The Great Prevalence of the Digital Development Pattern in Data The Absence of the Digital Development Pattern in k/x Distribution Benford's Law in Its Purest Form Constant Base Raised to a Random Power General Results: General Results in Benford's Law First Two Digits versus Last Two Digits The Law of Relative Quantities: The Relating Concepts of Digits, Numbers, and Quantities The Arbitrariness of our Positional Number System Two Radically Different Interpretations of the Benford Phenomenon The Quest for a Universal and Number-System-Invariant Measure The Shape and Nature of Histograms are Number-System Invariant Constructing a Three-Bin Histogram Signifying Small, Medium, and Big Constructing a Set of Infinitely Expanding Histograms Numerical Consistency in Bin Schemes for 15 Real-Life Data Sets The Postulate on Relative Quantities Application of the Postulate via Generic Bin Scheme on k/x The Infinite Sequence Result for the Bin Scheme on k/x The General Law of Relative Quantities Benford's Law as a Special Case and Direct Consequence of GLORQ The Universal Law of Relative Quantities Benford Second-Order Digits Interpreted as an Irregular Bin Scheme Concluding Historical and Conceptual Perspectives Appendices: Infinite Sequence Reduction Data Sets Glossary of Frequently Used Abbreviations First Two Digits versus Last Two Digits Index Readership: This book is suitable for expert mathematicians, statisticians, and scientists, as well as university students of these disciplines. This book is also suitable for the layman, the non-expert, and the educated general public, who are not necessarily proficient in mathematics, statistics, and the sciences, but who have enough interest to still be able to understand the topic on the whole.