Part I: Data Logistics
  2: Moving Data in and out of Hadoop
  3: Data Serialization: Working with Text and BeyondPart II: Big Data Patterns
  4: Applying MapReduce Patterns to Big Data
  5: Streamlining HDFS for Big Data
  6: Measuring and Optimizing Performance

Part III: Data Science
  7: Utilizing Data Structures and Algorithms
  8. Applying Statistics
  9. Machine Learning

Part IV: Taming the Elephant
10. Hive
11. Pig
12. Crunch and Other Technologies
13. Testing and Debugging
14: Job Coordination
15. Proficient Administration

Appendixes
  A: Related Technologies
  B: Hadoop Built-in Ingress and Egress Tools
  C: HDFS Dissected
  D: Optimized MapReduce Join Frameworks