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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