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Real-time Event Joining in Practice with Kafka and Flink
Abstract
Paper presentation at the CIKM Online and Adaptive Recommender Systems workshop. Presented a production-grade approach to real-time event joining using Kafka and Flink, with war stories from running event streams that power a ~200M-user recommender system. Covered watermark handling, side-output patterns for late events, and cost/latency trade-offs between in-memory joins and materialized projections.