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 a...(展开全部)

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 a...(展开全部)

A friendly, framework-agnostic tutorial that will help you grok how streaming systems work—and how to build your own! In Grokking Streaming Systems you will learn how to: - Implement and troubleshoot streaming systems - Design streaming systems for complex functionalities - Assess parallelization requirements - Spot networking bottlenecks and resolve back pressure - Group data ...(展开全部)

Traditional network television programming has always followed the same script: executives approve a pilot, order a trial number of episodes, and broadcast them, expecting viewers to watch a given show on their television sets at the same time every week. But then came Netflix's House of Cards. Netflix gauged the show's potential from data it had gathered about subscribers' pre...(展开全部)

Large-scale data analysis ("Big Data") is suddenly of crucial importance to virtually every enterprise. Mobile and social technologies are generating massive datasets, and distributed cloud computing is providing better ways to analyzing and processing that data. Accelerating technological change is turning long-accepted ideas about Big Data upside down, forcing companies to ev...(展开全部)

Einstein's General Theory of Relativity leads to two remarkable predictions: first, that the ultimate destiny of many massive stars is to undergo gravitational collapse and to disappear from view, leaving behind a 'black hole' in space; and secondly, that there will exist singularities in space-time itself. These singularities are places where space-time begins or ends, and the...(展开全部)

Einstein's General Theory of Relativity leads to two remarkable predictions: first, that the ultimate destiny of many massive stars is to undergo gravitational collapse and to disappear from view, leaving behind a 'black hole' in space; and secondly, that there will exist singularities in space-time itself. These singularities are places where space-time begins or ends, and the...(展开全部)

Neha Narkhede， Confluent联合创始人、CTO，曾在LinkedIn主导基于Kafka和Apache Samza构建流式基础设施，是Kafka作者之一。 Gwen Shapira， Confluent系统架构师，帮助客户构建基于Kafka的系统，在可伸缩数据架构方面拥有十余年经验；曾任Cloudera公司解决方案架构师。另著有《Hadoop应用架构》。 Todd Palino， LinkedIn主任级SRE，负责部署管理大型的Kafka、Zookeeper和Samza集群。 【译者简介】 薛命灯，毕业于厦门大学软件学院，十余年软件开发和架构经验，InfoQ高级社区编辑。译有《硅谷革命》《生产微服务》等书。微信公众号CodeDeep。