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Flink Forward 201904 PPT资料下载

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。

Flink Forward 201904 PPT资料下载

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

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