这次整理的 PPT 来自于2018年09月03日至05日在 Berlin 进行的 flink forward 会议，这种性质的会议和大家熟知的Spark summit类似。本次会议的官方日程参见：https://berlin-2018.flink-forward.org/。本次会议共有超过350个 Flink 社区会员的人参与，因为原始的 PPT 是在 http://www.slideshare.net/ 网站，这个网站需要翻墙；为了学习交流的方便，本博客将这些 PPT 全部下载了，希望对大家有所帮助。完整 PPT 共54个，由于本次会议的 PPT 资料还在更新中，本次只提供其中42个 PPT 资料的下载，其他的本站会陆续更新，请关注本博客或公众号。

如果想及时了解Spark、Hadoop或者Hbase相关的文章，欢迎关注微信公共帐号：iteblog_hadoop

所有列表

• A streaming Quantitative Analytics engine
• Managing Flink operations at GoJek
• Flink SQL in Action
• Tuning Flink for Robustness and Performance
• Elastic Streams at Scale
• Stream Join in Flink: from Discrete to Continuous
• Streaming Digital Fingerprints
• The Apache Way! … ?
• Flink as a Library (and still as a Framework)
• Unified Engine for Data Processing and AI
• The convergence of stream processing and microservice architecture
• A Year In Flink
• Unlocking the next wave of applications with Stream Processing
• Assisting millions of active users in real-time
• Stream Loops on Flink: Reinventing the wheel for the streaming era
• Lessons learned from Migrating to a Stateful Streaming Framework
• Data lossless event time streaming processing for revenue calculation
• Our successful journey with Flink
• Democratizing data in GO-JEK
• Using a sharded Akka distributed data cache as a Flink pipelines integration buffer
• Approximate standing queries on Stream Processing
• Exploiting Apache Flink's Stateful Operators
• Using Apache Flink for Smart Cities: Warsaw case study
• Detecting Patterns in Event Streams with Flink SQL
• Improving throughput and latency with Flink's network stack
• Flink Positive/Flinking Positive
• Streaming topic model training and inference with Apache Flink
• Streaming ETL with Flink and Elasticsearch
• Real-time Processing of Noisy Data from Connected Vehicles
• Python Streaming Pipelines with Beam on Flink
• How to keep our flock happy with Apache Flink on AWS
• Automating Flink Deployments to Kubernetes
• Anomaly Detection Engine for Cloud Activities using Flink
• data Artisans Product Announcement
• Upgrading Apache Flink Applications: State of the Union
• Universal Machine Learning with Apache Beam
• Threading Needles in a Haystack: Sessionizing the Uber firehose in realtime
• Real-time driving score service using Flink
• MERA: Trading precision for performance
• Hardware-efficient Stream Processing
• Failure is not fatal: what is your recovery story?
• Efficient Window Aggregation with Stream Slicing
• Deploying a secured Flink cluster on Kubernetes
• Play it again, Sam: Bookmarking, Slicing, and Replaying Unbounded Data Streams for Analytics Applications

完整 PPT 列表

https://www.iteblog.com/FlinkForward/，本地址有效期七天，七天过后将自动失效。