Update streaming track schedule

content/sessions/streaming-868206.md

@@ -1,6 +1,6 @@
 ---
 title: "Queue, Process, Predict: Kafka’s New Era with Flink LLMs and Datalake"
-date: "2025-07-26T14:00:00"
+date: "2025-07-26T16:45:00"
 room: "YuanMing Hall"
 track: "streaming"
 presenters: "Shekhar Prasad Rajak"
@@ -22,4 +22,4 @@ Shekhar Prasad Rajak: Passionate Open Source Advocate and Software Engineer at A
 
 Shekhar is deeply passionate about open source software and actively contributes to various projects, including SymPy, Ruby gems like daru and daru-view (which he authored), Bundler, NumPy, and SciPy. 
 He successfully completed Google Summer of Code in 2016 and 2017 and has served as an admin for SciRuby, mentoring multiple organizations. 
-Shekhar has spoken at prominent conferences such as RubyConf 2018, PyCon 2017, ApacheCon 2020, and Community Over Code 2024, as well as numerous regional meetups. Currently, he works at Apple as a Software Development Engineer.
+Shekhar has spoken at prominent conferences such as RubyConf 2018, PyCon 2017, ApacheCon 2020, and Community Over Code 2024, as well as numerous regional meetups. Currently, he works at Apple as a Software Development Engineer.

content/sessions/streaming-868206.zh.md

@@ -1,6 +1,6 @@
 ---
 title: "队列、处理、预测：Kafka 与 Flink LLM 和 Datalake 开启新时代"
-date: "2025-07-26T14:00:00"
+date: "2025-07-26T16:45:00"
 room: "圆明厅"
 track: "streaming"
 presenters: "Shekhar Prasad Rajak"
@@ -21,4 +21,4 @@ Shekhar Prasad Rajak: 热情的开源倡导者，苹果公司软件工程师。
 
 Shekhar 对开源软件充满热情，并积极参与多个项目，包括SymPy、Ruby gems（如他所著的 daru 和daru-view）、Bundler、NumPy 和 SciPy。  
 他于 2016 年和 2017 年成功完成 Google Summer of Code 项目，并担任 SciRuby 的管理员，指导了多个组织。
-谢卡尔曾在 RubyConf 2018、PyCon 2017、ApacheCon 2020 和 Community Over Code 2024 等知名大会上发表演讲，并参与了众多地区性技术聚会。目前，他任职于苹果公司，担任软件开发工程师。
+谢卡尔曾在 RubyConf 2018、PyCon 2017、ApacheCon 2020 和 Community Over Code 2024 等知名大会上发表演讲，并参与了众多地区性技术聚会。目前，他任职于苹果公司，担任软件开发工程师。

content/sessions/streaming-889266.md

@@ -1,12 +1,12 @@
----
+---
 title: "When Flink Meets Fluss: The Future of Streaming Warehouse"
-date: "2025-07-26T16:15:00"
+date: "2025-07-26T15:45:00"
 room: "YuanMing Hall"
 track: "streaming"
 presenters: "Jark Wu"
-stype: "Chinese Session"
----
-
+stype: "Chinese Session"
+---
+
 Kafka and Flink have been widely used together in streaming processing scenarios, becoming a defacto standard paradigm for building streaming warehouses and real-time analytics. However, it still faces many challenging issues that are hard to resolve. This session will explore the challenges and problems this paradigm faces in streaming analytics. 
 
 We will first discuss the limitations and pain points of Kafka when used with Flink. Then we will introduce Fluss, a next-generation streaming storage designed for streaming analytics. We’ll walk through its architecture and core innovations, highlighting how it seamlessly integrates with Flink to power the next generation of streaming warehouses. You’ll discover the game-changing capabilities unlocked by combining Flink and Fluss, such as streaming column pruning, delta joins, union reads, and merge engines. 
@@ -21,4 +21,4 @@ Finally, we’ll explore real-world use cases of Flink + Fluss, showcasing how t
 
 Jark Wu: Alibaba
 
-Jark Wu is a committer and PMC member of Apache Flink. He leads both the Fluss and Flink SQL teams at Alibaba Cloud. With a decade of experience in Flink, he has been deeply involved in developing and evolving Flink SQL from zero to now. Throughout this journey, he has also initiated and incubated Flink CDC and Fluss projects, further expanding the Flink ecosystem.
+Jark Wu is a committer and PMC member of Apache Flink. He leads both the Fluss and Flink SQL teams at Alibaba Cloud. With a decade of experience in Flink, he has been deeply involved in developing and evolving Flink SQL from zero to now. Throughout this journey, he has also initiated and incubated Flink CDC and Fluss projects, further expanding the Flink ecosystem.

content/sessions/streaming-889266.zh.md

@@ -1,6 +1,6 @@
 ---
 title: "当 Flink 遇见 Fluss：流式数据仓库的未来"
-date: "2025-07-26T16:15:00"
+date: "2025-07-26T15:45:00"
 room: "圆明厅"
 track: "streaming"
 presenters: "Jark Wu"
@@ -20,4 +20,4 @@ Kafka 和 Flink 已广泛应用于流处理场景，成为构建流式数据仓
 
 Jark Wu: 阿里巴巴
 
-Jark Wu 是 Apache Flink 的提交者和 PMC 成员。他领导着阿里云的 Fluss 和 Flink SQL 团队。凭借十年的 Flink 经验，他深度参与了 Flink SQL 从零到现在的开发和演进。在此期间，他还发起并孵化了 Flink CDC 和 Fluss 项目，进一步扩展了 Flink 生态系统。
+Jark Wu 是 Apache Flink 的提交者和 PMC 成员。他领导着阿里云的 Fluss 和 Flink SQL 团队。凭借十年的 Flink 经验，他深度参与了 Flink SQL 从零到现在的开发和演进。在此期间，他还发起并孵化了 Flink CDC 和 Fluss 项目，进一步扩展了 Flink 生态系统。

content/sessions/streaming-903630.md

@@ -1,12 +1,12 @@
----
+---
 title: "Practice of Flink Memory Governance at ByteDance"
-date: "2025-07-26T14:30:00"
+date: "2025-07-26T14:00:00"
 room: "YuanMing Hall"
 track: "streaming"
 presenters: "Yiheng Tang, Shaojun Wang"
-stype: "Chinese Session"
----
-
+stype: "Chinese Session"
+---
+
 As the demand for streaming tasks continues to grow within ByteDance, Flink has been widely adopted across various business domains at scale. Among the resource costs of these large-scale tasks, memory stands out as a significant contributor—especially heap memory. The total allocated memory for all tasks has reached tens of thousands of terabytes, yet the JVM heap utilization remains below 50%, and container-level memory usage is under 70%. Against the backdrop of company-wide cost reduction and efficiency improvement, we have carried out a series of memory optimizations focused on heap memory usage prediction, off-heap memory usage tracking, and simplifying Flink’s memory model. These efforts have been successfully rolled out across ByteDance, resulting in memory savings of over a thousand terabytes.
 In this talk, we will present the key joint optimizations led by the Flink and JVM teams at ByteDance, and share the results we’ve achieved.
 
@@ -38,4 +38,4 @@ Shaojun Wang: ByteDance, China, Programming Language Engineer
 
 1. The PPMC of the Apache incubating project teaclave
 2. A Gopher since 2017
-3. A Programming Language Engineer @ByteDance
+3. A Programming Language Engineer @ByteDance

content/sessions/streaming-903630.zh.md

@@ -1,6 +1,6 @@
 ---
 title: "字节跳动 Flink 内存治理实践"
-date: "2025-07-26T14:30:00"
+date: "2025-07-26T14:00:00"
 room: "圆明厅"
 track: "streaming"
 presenters: "唐以恒, 汪少军"
@@ -35,4 +35,4 @@ stype: "中文演讲"
 
 1. Apache 孵化项目 teaclave 的 PPMC
 2. 自 2017 年起成为 Gopher 开发者
-3. 字节跳动编程语言工程师
+3. 字节跳动编程语言工程师

content/sessions/streaming-909075.md

@@ -1,12 +1,12 @@
----
+---
 title: "Scalable Join & Aggregation with External State and Dynamic Tables"
-date: "2025-07-26T15:00:00"
+date: "2025-07-26T14:30:00"
 room: "YuanMing Hall"
 track: "streaming"
 presenters: "Feng Jin"
-stype: "Chinese Session"
----
-
+stype: "Chinese Session"
+---
+
 1.	Background & Motivation
 	•	Flink SQL challenges at scale: large state, long joins, complex maintenance
 	•	Business use case: automotive data warehouse and alerting systems
@@ -34,4 +34,4 @@ stype: "Chinese Session"
 
 Feng Jin: Xiaomi, Senior Software Engineer, Apache Flink Committer
 
-Feng Jin is currently a member of the Compute Platform team at Xiaomi, where he is responsible for maintaining the internal Flink framework and building the company’s real-time lakehouse architecture. He has extensive experience in large-scale stream processing, Flink SQL optimization, and state management. He is also an Apache Flink committer and actively contributes to the open-source community.
+Feng Jin is currently a member of the Compute Platform team at Xiaomi, where he is responsible for maintaining the internal Flink framework and building the company’s real-time lakehouse architecture. He has extensive experience in large-scale stream processing, Flink SQL optimization, and state management. He is also an Apache Flink committer and actively contributes to the open-source community.

content/sessions/streaming-909075.zh.md

@@ -1,12 +1,12 @@
----
+---
 title: "使用外部状态和动态表实现可扩展的连接和聚合"
-date: "2025-07-26T15:00:00"
+date: "2025-07-26T14:30:00"
 room: "圆明厅"
 track: "streaming"
 presenters: "Feng Jin"
-stype: "中文演讲"
----
-
+stype: "中文演讲"
+---
+
 1. 背景与动机
   • Flink SQL 在规模化方面的挑战：大状态、长连接、复杂的维护
   • 业务用例：汽车数据仓库和报警系统
@@ -33,4 +33,4 @@ stype: "中文演讲"
 
 Feng Jin: 小米，高级软件工程师，Apache Flink Committer
 
-Feng Jin 目前是小米计算平台团队成员，负责维护内部 Flink 框架并构建公司实时 Lakehouse 架构。他在大规模流处理、Flink SQL 优化和状态管理方面拥有丰富的经验。他也是 Apache Flink 的提交者，积极为开源社区做出贡献。
+Feng Jin 目前是小米计算平台团队成员，负责维护内部 Flink 框架并构建公司实时 Lakehouse 架构。他在大规模流处理、Flink SQL 优化和状态管理方面拥有丰富的经验。他也是 Apache Flink 的提交者，积极为开源社区做出贡献。

content/sessions/streaming-910362.md

@@ -1,12 +1,12 @@
----
+---
 title: "The Intelligent Evolution of Fully Managed Resource Management for Tencent's Real-Time Computing"
-date: "2025-07-26T15:45:00"
+date: "2025-07-26T15:00:00"
 room: "YuanMing Hall"
 track: "streaming"
 presenters: "Zihao Chen, Jiangang Liu"
-stype: "Chinese Session"
----
-
+stype: "Chinese Session"
+---
+
 1. Background and Industry Pain Points
   a. Flink, as a long-running stateful computation, is widely used in scenarios such as real-time data warehousing, real-time analytics, and online training.
   b. Real-time resource configuration and operations are a universal challenge: over-provisioning leads to waste, while under-provisioning causes lag and failover. Additionally, resource demands vary significantly over time.
@@ -38,4 +38,4 @@ Zihao has been engaged in R&D related to the Flink kernel for many years. In rec
 
 Jiangang Liu: Tencent, Head of Real-time Computing Flink
 
-Tencent Real-Time Computing Flink Lead, specializing in the cloud-native evolution, elastic scaling, and separation of storage and computation. Previously served as the Flink Technical Lead at Kuaishou, leading real-time computing architecture design and large-scale implementation, successfully driving the real-time connection project between Kuaishou and CCTV Spring Festival Gala in 2020. Prior to that, participated in Baidu Matrix's development work in offline hybrid computing.
+Tencent Real-Time Computing Flink Lead, specializing in the cloud-native evolution, elastic scaling, and separation of storage and computation. Previously served as the Flink Technical Lead at Kuaishou, leading real-time computing architecture design and large-scale implementation, successfully driving the real-time connection project between Kuaishou and CCTV Spring Festival Gala in 2020. Prior to that, participated in Baidu Matrix's development work in offline hybrid computing.

content/sessions/streaming-910362.zh.md

@@ -1,12 +1,12 @@
----
+---
 title: "腾讯实时计算的智能演进：全托管资源管理"
-date: "2025-07-26T15:45:00"
+date: "2025-07-26T15:00:00"
 room: "圆明厅"
 track: "streaming"
 presenters: "Zihao Chen, Jiangang Liu"
-stype: "中文演讲"
----
-
+stype: "中文演讲"
+---
+
 1. 背景与行业痛点  
   a. Flink 作为一种长期运行的有状态计算，广泛应用于实时数据仓库、实时分析和在线训练等场景。
   b. 实时资源配置与运维是普遍挑战：过度配置导致资源浪费，而配置不足则引发延迟和故障转移。此外，资源需求随时间变化显著。
@@ -37,4 +37,4 @@ Zihao 多年来一直从事与Flink内核相关的研发工作。近年来，他
 
 Jiangang Liu: 腾讯，实时计算 Flink 负责人
 
-腾讯实时计算Flink负责人，专注于云原生演进、弹性扩展以及存储与计算的分离。此前曾担任快手Flink技术负责人，负责实时计算架构设计与大规模落地实施，成功推动了2020年快手与央视春晚的实时连接项目。在此之前，参与了百度Matrix在离线混合计算领域的开发工作。
+腾讯实时计算Flink负责人，专注于云原生演进、弹性扩展以及存储与计算的分离。此前曾担任快手Flink技术负责人，负责实时计算架构设计与大规模落地实施，成功推动了2020年快手与央视春晚的实时连接项目。在此之前，参与了百度Matrix在离线混合计算领域的开发工作。

content/sessions/streaming-910562.md

@@ -1,6 +1,6 @@
 ---
 title: "Kafka 4.0 Highlights: Features, Removals, and Upgrades"
-date: "2025-07-26T16:45:00"
+date: "2025-07-26T16:15:00"
 room: "YuanMing Hall"
 track: "streaming"
 presenters: "Jiunn-Yang Huang, Chia-Ping Tsai, PoAn Yang, TengYao Chi, YiHuan LEE, Kuan Po Tseng"
@@ -59,4 +59,4 @@ My research focuses on "The Effect of Load Balancing on Kafka Performance"
 
 Kuan Po Tseng: ASF, Apache Kafka Contributor
 
-My research focuses on "The Effect of Load Balancing on Kafka Performance"
+My research focuses on "The Effect of Load Balancing on Kafka Performance"

content/sessions/streaming-910562.zh.md

@@ -1,6 +1,6 @@
 ---
 title: "Kafka 4.0 核心亮点：新特性、移除项与升级指南"
-date: "2025-07-26T16:45:00"
+date: "2025-07-26T16:15:00"
 room: "圆明厅"
 track: "streaming"
 presenters: "Jiunn-Yang Huang, Chia-Ping Tsai, PoAn Yang, TengYao Chi, YiHuan LEE, Kuan Po Tseng"
@@ -58,4 +58,4 @@ YiHuan LEE: 国立成功大学研究生
 
 Kuan Po Tseng: ASF, Apache Kafka 贡献者
 
-我对 Kafka 确实充满热情，并致力于提高其性能、优化工具和增加测试覆盖率。与一群志同道合的朋友一起，我们一直在努力让Kafka变得更好。每当我为开源社区做出贡献时，我都感到非常兴奋，因为我们不仅仅是在增强Kafka的功能，我们还在构建一个更强大、更灵活的生态系统，让全球用户受益。对我来说，这是一个不断探索和挑战的旅程，让Kafka成为最好的Kafka是我一直努力的目标！
+我对 Kafka 确实充满热情，并致力于提高其性能、优化工具和增加测试覆盖率。与一群志同道合的朋友一起，我们一直在努力让Kafka变得更好。每当我为开源社区做出贡献时，我都感到非常兴奋，因为我们不仅仅是在增强Kafka的功能，我们还在构建一个更强大、更灵活的生态系统，让全球用户受益。对我来说，这是一个不断探索和挑战的旅程，让Kafka成为最好的Kafka是我一直努力的目标！