补充个outline吧还是：
Spark01
1. Introduction to Data Analysis with Spark. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2. Downloading Spark and Getting Started. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3. Programming with RDDs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4. Working with Key/Value Pairs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5. Loading and Saving Your Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6. Advanced Spark Programming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
7. Running on a Cluster. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
8. Tuning and Debugging Spark. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
9. Spark SQL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
10. Spark Streaming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
11. Machine Learning with MLlib. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213


Spark02
1. Analyzing Big Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2. Introduction to Data Analysis with Scala and Spark. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3. Recommending Music and the Audioscrobbler data set. . . . . . . . . . . . . . . . . . . . . . . . . . 37
4. Predicting Forest Cover with Decision Trees. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5. Anomaly Detection in Network Traffic with K-means clustering. . . . . . . . . . . . . . . . . . . 79
6. Understanding Wikipedia with Latent Semantic Analysis. . . . . . . . . . . . . . . . . . . . . . . . . 9
7. Analyzing Co-occurrence Networks with GraphX. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
8. Geospatial and Temporal Data Analysis on the New York City Taxicab Data. . . . . . . . . 145
9. Financial Risk through Monte Carlo Simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
10. Analyzing Genomics Data and the BDG Project. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
11. Analyzing Neuroimaging Data with PySpark and Thunder. . . . . . . . . . . . . . . . . . . . . . . 207
12. Appendix: Deeper Into Spark. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
13. Appendix: Upcoming MLlib Pipelines API. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

Spark03
Chapter 1: Getting Up and Running with Spark  7
Chapter 2: Designing a Machine Learning System  37
Chapter 3: Obtaining, Processing, and Preparing Data with Spark  51
Chapter 4: Building a Recommendation Engine with Spark  83
Chapter 5: Building a Classification Model with Spark  117
Chapter 6: Building a Regression Model with Spark  161
Chapter 7: Building a Clustering Model with Spark  197
Chapter 8: Dimensionality Reduction with Spark  221
Chapter 9: Advanced Text Processing with Spark  247
Chapter 10: Real-time Machine Learning with Spark Streaming  279

所有专题索引：
01.数据挖掘专题：https://bbs.pinggu.org/thread-2161511-1-1.html
02.机器学习专题：https://bbs.pinggu.org/thread-3702096-1-1.html
03.Hadoop大数据平台专题：https://bbs.pinggu.org/thread-2515116-1-1.html
04.Spark大数据平台专题：https://bbs.pinggu.org/thread-3702039-1-1.html
05.算法专题(CLRS, DPV, KT, SW 4合1)：https://bbs.pinggu.org/thread-4621817-1-1.html

hadoop hive  spark

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