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Building Hypermedia Clients
Todd Brackley demonstrates provisioning a network of data through a JavaScript client to show that there is no magic and talks through some of the major design issues.
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Straggler Free Data Processing in Cloud Dataflow
Eugene Kirpichov describes the theory and practice behind Cloud Dataflow's approach to straggler elimination, and the associated non-obvious challenges, benefits, and implications of the technique.
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Goodbye PrintGCDetails... and Other JDK 9 Changes!
Tony Printezis talks about the major changes and improvements coming in JDK 9 that will affect (but also help) anyone who's interested in Java performance monitoring, profiling, and tuning.
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Building Data Pipelines in Python
Marco Bonzanini discusses the process of building data pipelines and all the steps necessary to prepare data, focusing on data plumbing and going from prototype to production.
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Data Driven Products Now!
Dan McKinley discusses how Etsy is using data to validate their ideas and prototypes, turning some into real products.
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Practical Data Synchronization Using CRDTs
Dmitry Ivanov discusses the basic CRDTs implementations in Scala, explaining the advantages of these data structures to solve many synchronization problems as well as their limitations.
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Build to Learn: Rapid Prototyping Methods
Sara Bayless da Costa discusses several prototyping methods helping to learn about product, gather quality feedback, and get the best version of a product out there as quickly as possible.
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Speedup Your Java Apps with Hardware Counters
Sergey Kuksenko discusses how Performance Monitoring Unit works, what Hardware Counters are, which tools have friendship with Java and how to use HWC for speeding up our Java applications.
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Java SE 9: Continuing to Thrive in the Cloud!
Bernard Traversat discusses JVM enhancements addressing cloud deployment requirements such as G1 GC, segmented code cache, contended locking, and density String.
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Java Puzzlers NG S02: down the Rabbit Hole
Baruch Sadogursky and Viktor Gamov talk about Java puzzlers - streams, lambdas, monads, Optionals and CompletableFutures.
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Machine Learning and End-to-End Data Analysis Processes in Spark Using Python and R
Debraj GuhaThakurta discusses ML and data analysis processes in Spark using examples written in Python and R.
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IoT in the Cloud: Build & Unleash the Value in Your Renewable Energy System
Mark Heckler introduces the IoT & Cloud concepts and demonstrates how one necessitates the other.