Tour of Apache PredictionIO in 10 Minuteschibochibo
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The document provides an overview of the Apache PredictionIO framework for building machine learning applications. It describes PredictionIO as an open source machine learning framework for building end-to-end machine learning platforms. It outlines the basic process for using PredictionIO, which involves cloning a template, collecting training data, building, training and deploying a predictive model, and making queries to the model. It also briefly describes the train and predict algorithms and notes that community support is available via email and the PredictionIO website.
Deadly Code! (seriously) Blocking & Hyper Context Switching Patternchibochibo
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The document discusses the issues faced when using blocking and hyper context switching patterns in Scala applications, particularly regarding database access and execution context management. It highlights the inefficiencies caused by unnecessary switching and blocking, which can lead to degraded response times even with a small number of users. The presentation concludes with a summary emphasizing the importance of avoiding blocking operations in asynchronous frameworks and the proper handling of execution contexts.
The document discusses the improvements made in the Doobie library version 0.4.0, particularly around dynamic SQL query construction using composable statement fragments. It highlights how to set up imports, define SQL literals, and use various combinators for more complex queries. The conclusion expresses optimism about the ability to write dynamic SQL while noting some uncertainty around specific features.
Is spark streaming based on reactive streams?chibochibo
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What is Reactive Streams? What if a subscriber was very slow in asynchronous stream processing? In this talk we will briefly introduce you to the basics of Reactive Streams and the importance of back-pressure and then explain the architecture (implementations) of Spark Streaming back-pressure.
The document discusses Scala macros, highlighting their definition as code that generates code and their ease of use despite the complexity of development. It provides practical examples of using macros in logging and matcher generation, as well as distinctions between blackbox and whitebox macro implementations. Additionally, it mentions the upcoming Scala.meta API aimed at simplifying metaprogramming and enhancing macro capabilities.