Something To Talk About Streaming
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Something to Talk About
A showrunner and her assistant give the world something to talk about when they accidentally fuel a ridiculous rumor in this debut romance. Hollywood powerhouse Jo is photographed making her assistant Emma laugh on the red carpet, and just like that, the tabloids declare them a couple. The so-called scandal couldn't come at a worse time—threatening Emma's promotion and Jo's new movie. As the gossip spreads, it starts to affect all areas of their lives. Paparazzi are following them outside the office, coworkers are treating them differently, and a “source” is feeding information to the media. But their only comment is “no comment”. With the launch of Jo’s film project fast approaching, the two women begin to spend even more time together, getting along famously. Emma seems to have a sixth sense for knowing what Jo needs. And Jo, known for being aloof and outwardly cold, opens up to Emma in a way neither of them expects. They begin to realize the rumor might not be so off base after all…but is acting on the spark between them worth fanning the gossip flames?
Streaming by the Rest of Us
An in-depth investigation of the Twitch streamers who make up the largest population on the platform: those streaming to small audiences or even no one. The vast majority of people who stream themselves playing videogames online do so with few or no viewers. In Streaming by the Rest of Us, Mia Consalvo, Marc Lajeunesse, and Andrei Zanescu investigate who they are, why they do so, and why this form of leisure activity is important to understand. Unlike the esports athletes and streaming superstars who receive the lion’s share of journalistic and academic attention, microstreamers are not in it for the money and barely have an audience. In this, the first book dedicated to the latter group, the authors gather interviews from dozens of microstreamers from 2017 to 2019 to discuss their lives, struggles, hopes, and goals. For readers interested in livestreaming, and Twitch in particular, the book rethinks the medium’s history through accounts of the everyday uses of webcams, with particular attention to notions of liveness and authenticity. These two concepts have become calling cards for the videogame livestreaming platform and underlie streamer motivations, the construction of their practices (whether casual, serious, or anywhere in between), and the complex “metas” that take shape over time. The book also looks at the authors’ own practices of livestreaming, focusing on what can be gained through experiencing the lived reality of the practice. Finally, the authors explain how Twitch’s platform (studied from 2017–2023) informs how streamers structure their every day and how corporate ideologies bleed into real-world spaces like TwitchCon.
Streaming Systems
Author: Tyler Akidau
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2018-07-16
Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra