InfoQ Homepage Streaming Content on InfoQ
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The Power of Distributed Snapshots in Apache Flink
Stephan Ewen talks about how Apache Flink handles stateful stream processing and how to manage distributed stream processing & data driven applications efficiently with Flink's checkpoints&savepoints.
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Panel: SQL over Streams, Ask the Experts
The panelists discuss the new generation of Stream Processing engines.
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Survival of the Fittest - Streaming Architectures
Michael Hansen talks about the core principles that will stand the tests of streaming evolution, the potential pitfalls that we may stumble over on our path to streaming and how to avoid these.
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Streaming for Personalization Datasets at Netflix
Shriya Arora discusses challenges faced with stream processing unbounded datasets, comparing microbatch with event-based approaches using Spark and Flink.
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Streaming Microservices: Contracts & Compatibility
Gwen Shapira discusses patterns of schema design, schema storage and schema evolution that help development teams build contracts through better collaboration and deliver resilient applications faster
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Adopting Stream Processing for Instrumentation
Sean Cribbs talks about the interface Comcast has designed for their instrumentation system, how it works, how the stream processor manages flows on behalf of the user, and some trade-offs applied.
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When Streams Fail: Kafka Off the Shore
Anton Gorshkov discusses how to evaluate and architect a resilient streaming platform, focusing on Kafka and Spark streaming and sharing his experience of using them to process financial transactions.
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Real-World Java 9
Trisha Gee shows via live coding how we can use the new Flow API to utilize Reactive Programming, how the improvements to the Streams API make it easier to control real-time streaming data, etc.
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From Concurrent to Parallel
Brian Goetz explores the different goals, tools, and techniques involved between concurrency and parallelism approaches, and how to analyze a computation for potential parallelism.
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Streaming APIs
Audrey Neveu discusses why and how to transform a REST API into a Data Streaming API.
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Real-Time Recommendations Using Spark Streaming
Elliot Chow discusses the data pipeline that they built with Kafka, Spark Streaming, and Cassandra to process Netflix user activities in real time for the Trending Now row.
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Stream Processing & Analytics with Flink @Uber
Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.