0 views collected around this technical thread.
This article details Bilibili's implementation of a streaming data lake using Hudi and Flink, covering background challenges, four case studies, batch‑stream integration optimizations, infrastructure and kernel enhancements, and future work directions.
This article explains Apache Pulsar’s cloud‑native, storage‑compute separated architecture, its data model and scalability features, and how it integrates with Flink to provide a unified platform for both real‑time streaming and batch processing in big‑data applications.
The article reviews the current state of offline Hive‑based data warehouses, explains the emergence of real‑time data warehouses (1.0) built on Kafka and Flink, discusses their limitations, and outlines the progression toward batch‑stream unified architectures (2.0 and 3.0) leveraging data‑lake technologies such as Iceberg.
This article, presented by senior data platform engineer Mao Xiangyi of TAL Education, details the design and implementation of the company’s real‑time T‑Streaming platform, covering its three‑layer data architecture, batch‑stream integration techniques, ODS layer real‑timeization, Flink SQL development workflow, hybrid‑cloud deployment, and a case study of K‑12 renewal reporting.
This article details Jingdong's evolution from Storm to Flink, the architecture of its Kubernetes‑based real‑time computing platform, extensive containerization practices, performance and stability optimizations, and the future plan to unify batch‑stream processing while expanding SQL support and intelligent operations.