舉報 
會員
Pig Design Patterns
最新章節：
Index
Acomprehensivepracticalguidethatwalksyouthroughthemultiplestagesofdatamanagementinenterpriseandgivesyounumerousdesignpatternswithappropriatecodeexamplestosolvefrequentproblemsineachofthesestages.ThechaptersareorganizedtomimickthesequentialdataflowevidencedinAnalyticsplatforms,buttheycanalsobereadindependentlytosolveaparticulargroupofproblemsintheBigDatalifecycle.IfyouareanexperienceddeveloperwhoisalreadyfamiliarwithPigandislookingforausecasestandpointwheretheycanrelatetotheproblemsofdataingestion,profiling,cleansing,transforming,andegressingdataencounteredintheenterprises.KnowledgeofHadoopandPigisnecessaryforreaderstograsptheintricaciesofPigdesignpatternsbetter.
目錄(73章)
倒序
- coverpage
- Pig Design Patterns
- Credits
- Foreword
- About the Author
- Acknowledgments
- About the Reviewers
- www.PacktPub.com
- Support files eBooks discount offers and more
- Preface
- What this book covers
- What you need for this book
- Who this book is for
- Conventions
- Reader feedback
- Customer support
- Chapter 1. Setting the Context for Design Patterns in Pig
- Understanding design patterns
- The scope of design patterns in Pig
- Hadoop demystified – a quick reckoner
- Pig – a quick intro
- Understanding Pig through the code
- Summary
- Chapter 2. Data Ingest and Egress Patterns
- The context of data ingest and egress
- Types of data in the enterprise
- Ingest and egress patterns for multistructured data
- The ingress and egress patterns for the NoSQL data
- The ingress and egress patterns for structured data
- The ingress and egress patterns for semi-structured data
- JSON ingress and egress patterns
- Summary
- Chapter 3. Data Profiling Patterns
- Data profiling for Big Data
- Rationale for using Pig in data profiling
- The data type inference pattern
- The basic statistical profiling pattern
- The pattern-matching pattern
- The string profiling pattern
- The unstructured text profiling pattern
- Summary
- Chapter 4. Data Validation and Cleansing Patterns
- Data validation and cleansing for Big Data
- Choosing Pig for validation and cleansing
- The constraint validation and cleansing design pattern
- The regex validation and cleansing design pattern
- The corrupt data validation and cleansing design pattern
- The unstructured text data validation and cleansing design pattern
- Summary
- Chapter 5. Data Transformation Patterns
- Data transformation processes
- The structured-to-hierarchical transformation pattern
- The data normalization pattern
- The data integration pattern
- The aggregation pattern
- The data generalization pattern
- Summary
- Chapter 6. Understanding Data Reduction Patterns
- Data reduction – a quick introduction
- Data reduction considerations for Big Data
- Dimensionality reduction – the Principal Component Analysis design pattern
- Numerosity reduction – the histogram design pattern
- Numerosity reduction – sampling design pattern
- Numerosity reduction – clustering design pattern
- Summary
- Chapter 7. Advanced Patterns and Future Work
- The clustering pattern
- The topic discovery pattern
- The natural language processing pattern
- The classification pattern
- Future trends
- Summary
- Index 更新時間：2021-07-16 12:08:11
推薦閱讀
- 機器學習實戰：基于Sophon平臺的機器學習理論與實踐
- Machine Learning for Cybersecurity Cookbook
- Deep Learning Quick Reference
- 自動控制原理
- Mobile DevOps
- 機器人智能運動規劃技術
- Associations and Correlations
- 機器學習流水線實戰
- 21天學通Visual Basic
- Moodle Course Design Best Practices
- Linux嵌入式系統開發
- 大數據技術基礎：基于Hadoop與Spark
- Learn Microsoft Azure
- PHP求職寶典
- 網站規劃與網頁設計
- 傳感器應用技術
- Microsoft 365 Mobility and Security：Exam Guide MS-101
- 深度學習實戰
- Internet of Things for Architects
- 仿魚機器人的設計與制作
- 微機原理與接口技術
- 電氣控制及PLC技術：羅克韋爾Micro800系列
- Machine Learning with Core ML
- Photoshop修圖實用速查通典
- Installation，Storage，and Compute with Windows Server 2016：Microsoft 70-740 MCSA Exam Guide
- Apache Tomcat 7 Essentials
- 粗糙關系數據庫
- Machine Learning with R
- Voicebot and Chatbot Design
- UG NX 5中文版完美自學手冊
