Real-Time Big Data Analytics > PACKT 원서리스트

: Introducing the Big Data Technology Landscape and Analytics Platform
Big Data – a phenomenon
The Big Data dimensional paradigm
The Big Data ecosystem
The Big Data infrastructure
Components of the Big Data ecosystem
Distributed batch processing
Distributed databases (NoSQL)
Real-time processing
Summary

2: Getting Acquainted with Storm
An overview of Storm
Storm architecture and its components
How and when to use Storm
Storm internals
Summary

3: Processing Data with Storm
Storm input sources
Other sources for input to Storm
Reliability of data processing
Storm simple patterns
Storm persistence
Summary

4: Introduction to Trident and Optimizing Storm Performance
Working with Trident
Understanding LMAX
Storm internode communication
Understanding the Storm UI
Optimizing Storm performance
Summary

5: Getting Acquainted with Kinesis
Architectural overview of Kinesis
Creating a Kinesis streaming service
Summary

6: Getting Acquainted with Spark
An overview of Spark
The architecture of Spark
Resilient distributed datasets (RDD)
Writing and executing our first Spark program
Summary

7: Programming with RDDs
Understanding Spark transformations and actions
Programming Spark transformations and actions
Handling persistence in Spark
Summary

8: SQL Query Engine for Spark – Spark SQL
The architecture of Spark SQL
Coding our first Spark SQL job
Converting RDDs to DataFrames
Working with Parquet
Working with Hive tables
Performance tuning and best practices
Summary

9: Analysis of Streaming Data Using Spark Streaming
High-level architecture
Coding our first Spark Streaming job
Querying streaming data in real time
Deployment and monitoring
Summary

10: Introducing Lambda Architecture
What is Lambda Architecture
The technology matrix for Lambda Architecture
Realization of Lambda Architecture
Summary
backindex: Appendix A: Index