Java EE勉強会

MakingSenseofStreamProcessing

http://www.oreilly.com/data/free/stream-processing.csp

Chapter 1. Events and Stream Processing †

Events and Stream Processing岡澤
Implementing Google Analytics: A Case Study鶴田
Event Sourcing From the DDD Community高木
Bringing Together Event Sourcing and Stream Processing山下
Using Append-Only Streams of Immutable Eventsせと
Tools: Putting Ideas into Practice岡澤
CEP, Actors, Reactive, and More角田

Chapter 2. Using Logs to Build a Solid Data Infrastructure †

Using Logs to Build a Solid Data Infrastructure岡澤
Case Study Web Application Developers Driven to Insanity高木
Making Sure Data Ends Up in the Right Places山下
The Ubiquitous Log鶴田
How Logs Are Used in Practice瀬賀
Solving the Data Integration Problem瀬賀
Transactions and Integrity Constraints鶴田
Conclusion: Use Logs to Make Your Infrastructure Solid岡澤
Further Reading角田

Chapter 3. Integrating Databases and Kafka with Change Data Capture †

Introducing Change Data Capture瀬賀
Database = Log of Changes岡澤
Implementing the Snapshot and the Change Streamせと
Bottled Water: Change Data Capture with PostgreSQL and Kafka高木
Why Kafka?山下
Why Avro?鶴田
The Logical Decoding Output Plug-In角田
Status of Bottled Water岡澤

Chapter 4. The Unix Philosophy of Distributed Data †

The Unix Philosophy of Distributed Data角田
Simple Log Analysis with Unix Tools岡澤
Pipes and Composability鶴田
Unix Architecture versus Database Architecture瀬賀
Composability Requires a Uniform Interface山下
Bringing the Unix Philosophy to the Twenty-First Century高木

Chapter 5. Turning the Database Inside Out †

Turning the Database Inside Outせと
How Databases Are Used角田
└─　1. Replication山下
└─　2. Secondary Indexes鶴田
└─　3. Caching瀬賀
└─　4. Materialized Views角田
└─　Summary: Four Database-Related Ideas瀬賀
Materialized Views: Self-Updating Caches山下
└─　Example: Implementing Twitter高木
└─　The Unbundled Database鶴田
Streaming All the Way to the User Interface高木
Conclusion角田

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