Flink Forward 201904 PPT资料下载
过往记忆大数据 过往记忆大数据
本文原文（点击下面阅读原文即可进入） https://www.iteblog.com/archives/2540.html
Flink Forward 是由 Apache 官方授权，Apache Flink China社区支持，有来自阿里巴巴，Ververica（Apache Flink 商业母公司）、腾讯、Google、Airbnb以及 Uber 等公司参加的国际型会议。旨在汇集大数据领域一流人才共同探讨新一代大数据计算引擎技术。通过参会不仅可以了解到Flink社区的最新动态和发展计划，还可以了解到国内外一线大厂围绕Flink生态的生产实践经验，是Flink开发者和使用者不可错过的盛会。2019年04月的 Flink Forward 在美国旧金山进行，本次会议议题涵盖 Flink 使用案例、内部原理、Flink 生态系统的增长以及流处理和实时分析等相关主题。详细的 Schedule 可以参见 https://sf-2019.flink-forward.org/。
本文收集到本次会议的 35 个高清视频以及 12 个对应 ppt，关注本博客微信公众号 iteblog_hadoop，并回复 flink201904 获取本次会议的视频和 PPT 下载地址。
如果想及时了解Spark、Hadoop或者Hbase相关的文章，欢迎关注微信公众号：iteblog_hadoop
本文收集到本次会议的 35 个高清视频以及 12 个对应 ppt，关注本博客微信公众号 iteblog_hadoop，并回复 flink201904 获取本次会议的视频和 PPT 下载地址。
视频和 PPT 列表
下面列表绿色的代表有对应的 PPT，所有的列表都有对应的超清视频。
- From Stream Processor to a Unified Data Processing System
- Flink Powered Customer Experience: Scaling from 5 Billion down to One
- The Trade Desk's Year in Flink
- Managing Flink on Kubernetes - FlinkK8sOperator
- How John Deere uses Flink to process millions of sensor measurements per second
- Building a Streaming Analytics Stack with Open Source Technologies
- Streaming for Enterprises
- High cardinality data stream processing with large states
- Future of Apache Flink Deployments: Containers, Kubernetes and More
- How to Join Two Data Streams?
- TensorFlow Extended: An end-to-end machine learning platform for TensorFlow
- Build a Table-centric Apache Flink Ecosystem
- Building Financial Identity Platform using Apache Flink
- Elastic Data Processing with Apache Flink and Apache Pulsar
- High performance ML library based on Flink
- Building production Flink jobs with Airstream at Airbnb
- Analytics for the masses
- Creating millions of user sessions using Complex Event Processing
- Hunting for Attack Chains in Event Streams
- Deploying ONNX models on Flink
- Integrate Flink with Hive Ecosystem
- Developing and operating real-time applications with Oceanus
- Apache Beam: Portability in the times of Real Time Streaming
- Adventures in Scaling from Zero to 5 Billion Data Points per Day
- Streaming your Lyft Ride Prices
- Practical Experience running Flink in Production
- Scaling a real-time streaming warehouse with Apache Flink, Parquet and Kubernetes
- Massive Scale Data Processing at Netflix using Flink
- Using Flink to inspect live data as it flows through a data pipeline
- Towards Flink 2.0: Rethinking the stack and APIs to unify Batch & Stream
- Moving from Lambda and Kappa Architectures to Kappa+ at Uber
- Build a Table-centric Apache Flink Ecosystem
- Realtime Store Visit Predictions at Scale
- Real-time Processing with Flink for Machine Learning at Netflix
- Becoming a Smooth Operator: A look at low-level Flink APIs and what they enable