A detailed post‑mortem of a high‑priority fault on AMD servers shows how a split‑lock triggered by Python UDFs caused CPI spikes, CPU overload, and bus‑lock events, and explains the investigation steps, code analysis, reproduction tests, and mitigation measures taken to restore stability.
This article presents NetEase Game's streaming ETL solution built on Flink, covering business background, log characteristics, specialized and generic ETL services, architectural evolution, Python UDF integration, runtime optimizations, fault‑tolerance mechanisms, and future roadmap for unified real‑time and offline data warehouses.
This article explains how NetEase games collect heterogeneous logs, design a Flink‑driven streaming ETL pipeline, handle schema‑free sources, implement Python UDFs with Jython, optimize HDFS writes, manage real‑time and offline warehouses, and share practical tuning and fault‑tolerance techniques.
Apache Flink 1.11.0 introduces a suite of major enhancements—including unaligned checkpoints, a unified source interface, CDC support in Table API/SQL, performance‑boosted PyFlink, a new application deployment mode, and numerous UI, Docker, and catalog improvements—aimed at increasing usability, scalability, and integration across streaming and batch workloads.
The article provides a comprehensive overview of Apache Flink 1.11, detailing enhancements in cluster deployment, resource management, source/sink APIs, state backends, Table & SQL improvements, DataStream extensions, PyFlink/ML support, and runtime optimizations, along with relevant code examples and references.
Apache Flink 1.10 introduces a major upgrade that merges the Blink engine, boosts performance and stability, adds native Kubernetes support, enhances SQL DDL, delivers production‑ready Hive batch compatibility, optimizes memory management, and expands Python UDF capabilities, with detailed feature breakdowns and code examples.
