Course Content:
Chapter 1 Why Flink
poor flow of 1.1 deal with the consequences
1.1.1 Retail and Marketing
1.1.2 Things
1.1.3 Telecommunications
1.1.4 Banking and finance
1.2 continuous event processing target
1.3 streaming evolution of technology
1.4 Preliminary Flink
1.5 Flink production environment
1.5.1 commoner grid Telecom
1.5.2 other cases
applicable 1.6 Flink scene of
Chapter 2 stream processing architecture
2.1 stream processing architecture and traditional architecture
2.2 messaging layer and the stream processing layer
2.3 messaging layer over the functional
2.3.1 both performance and persistence
producers and consumers 2.3.3 decoupling
2.4 streaming data services architecture support micro
2.4.1 stream as a central data source
2.4.2 fraud detection: Example stream processing architecture with
the flexibility of the developer brought to 2.4.3
2.5 is not limited to real-time applications
2.6 geographies stream replication
Chapter 3 Flink uses
3.1 different types of validity
3.1.1 generated data as unnatural
3.1. 2 event time
remain accurate after failure 3.1.3
3.1.4 timely given the desired results
3.1.5 the development and operation and maintenance easier
Flink stages using 3.2
Chapter 4 of the Time
4.1 using batch processing architecture and infrastructure Lambda count
4.2 counting stream processing architecture using
4.3 time concept
4.4 Window
4.4.1 time window
4.4.2 count window
4.4.3 Session window
4.4.4 trigger
achieved 4.4.5 windows
4.5 space shuttle
4.6 watermark
4.7 real case: Ericsson's Kappa architecture
Chapter 5 calculated stateful
5.1 consistency
5.2 checkpoint: Once-guarantee exactly
5.3 points saved: status version control
5.4 end consistency and ends the processing flow database as
5.5 Flink performance
! Yahoo streaming Benchmark 5.5.1
5.5.2 change 1: use state of Flink
5.5.3 change 2: improvement and increasing the throughput of the data generator
5.5.4 change 3: eliminates network bottlenecks and
5.5.5 change 4: streams using MapR
5.5.6 change 5: Key base increased
5.6 Conclusion
Chapter 6 batch: a special stream processing
6.1 batch base
6.2 case Study: Flink as a batch processor
appendix other resources
Download: Flink Flink based tutorial project core members write