Apache Flink: A Very Quick Guide
summary
Shows Apache Flink as a unified stream-and-batch engine that runs Scala DataStream API and Java, uses RocksDB state backend for large operator state outside the JVM, and provides exactly-once semantics end-to-end via checkpointing and user-triggered savepoints that allow resume and migration. Demonstrates local-mode development, session and event-time windows, CEP rules for ICU-style alerts, delta iterations for incremental graphs, and cites a benchmark of up to 50 million events/sec (Kafka excluded).
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chapters (27)
- 0:00Intro
- 5:45Traditional approaches
- 6:10Streaming capabilities
- 7:15Project stratosphere
- 9:05Native support
- 9:53Apache Flink
- 12:00Application Architecture
- 12:45Typical Architecture
- 14:15Data Flow Graph
- 15:03Streaming Architecture
- 16:03Pipelining
- 16:31State
- 17:18Windows
- 19:51Time
- 21:43Fault Tolerance
- 22:20Checkpoints
- 22:37Save Points
- 23:57Benefits
- 31:23Complex Event Processing
- 32:39Example
- 34:02Flink vs Spark
- 34:37Apache Beam
- 35:42Benchmarks
- 36:29Sequel
- 36:56Community
- 37:11Resources
- 37:27Other Resources
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