This article demonstrates how to implement elegant partial updates in Spring Boot 3 by combining @JsonMerge and @JsonSetter(nulls = Nulls.SKIP), addressing null‑value handling, reducing boilerplate code, and ensuring nested objects and maps are merged correctly.
This article details Ctrip Business Travel’s implementation of a near‑real‑time data warehouse using Flink CDC and the Paimon lakehouse engine, covering order wide‑table construction, ticket refund alerts, ad attribution, batch‑stream integration, and practical lessons on Partial Update, Aggregation, and Tag‑based incremental processing.
This article details Ctrip Business Travel’s implementation of a near‑real‑time data warehouse and lakehouse using Flink CDC and Apache Paimon, covering order wide‑table construction, automated ticket reminders, ad attribution, batch‑stream integration, and lessons on Partial Update, Aggregation, and Tag‑based incremental processing.
The article explains why analytical databases struggle with real‑time data changes due to columnar storage, complex indexes and distributed processing, and then details StarRocks' primary‑key model, adaptive update mode, bitmap indexes, row/column partial updates, and practical SQL upsert techniques to achieve low‑latency updates without sacrificing query performance.
The article describes how NetEase News' recommendation team replaced a slow, batch‑oriented data‑warehouse pipeline with a Flink‑based, Apache Paimon real‑time wide‑table solution that supports partial updates, reduces latency from hours to minutes, and lowers processing costs while handling both deduplication and non‑deduplication recommendation scenarios.
