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Flink for Stream Processing

Event time, watermarks, state backends, checkpoints, savepoints, exactly-once sinks, Flink SQL and CDC.

Master true streaming with Apache Flink — event time and watermarks, keyed state and RocksDB state backends, checkpointing and savepoints, exactly-once with two-phase-commit sinks, Flink SQL, and the Flink CDC connector.

Advanced12 chapters· 4h 10m· in Ingestion & Transport

Course content

  1. 01Why Flink: True Streaming & the Dataflow ModelFree
  2. 02The Flink Architecture: JobManager, TaskManagers, Slots🔒
  3. 03Event Time vs Processing Time🔒
  4. 04Watermarks: Handling Out-of-Order Events🔒
  5. 05State in Flink: Keyed State & State Backends (RocksDB)🔒
  6. 06Checkpointing & the Chandy-Lamport Algorithm🔒
  7. 07Savepoints, Rescaling & Upgrades🔒
  8. 08Windows & Triggers🔒
  9. 09Exactly-Once with Sinks (Two-Phase Commit)🔒
  10. 10Flink SQL & the Table API🔒
  11. 11Flink CDC Connector🔒
  12. 12Capstone: A Fraud-Detection Pipeline for TheWorldShop🔒

Prerequisites

↗Apache Kafka: Fundamentals

What to learn next

↗Stream Processing Architecture: Kafka Streams vs Flink vs Spark· next

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