这是Facebook在FlinkForward2021上的一个talk, 主题如下 在前面的论文中分析了Facebook的实时计算引擎的设计和选型的考量,里面提到了Facebook的实时计算引擎为了满足易用性和性能不同维度的需求,研发了多套实时计算系统如Puma``Stylus``Swift分别使用SQL,C++,Swift来进行研发.但是多套引擎也带来了很多问题,可选择的引擎太多,不同的引擎的功能重叠,对用户和对于引擎维度都有很大的成本.为了能让用户获得一致性的体验,其内部选择将多套引擎整合成…

January 25, 2019Use Cases, Apache Flink The Big Data Team at Tencent     In recent years, the increasing need for timeliness, together with advances in software and hardware technologies, drive the emergence of real-time stream processing. Real-time…

转自:https://wso2.com/library/articles/2018/02/stream-processing-101-from-sql-to-streaming-sql-in-ten-minutes/ We have entered an era where competitive advantage comes from analyzing, understanding, and responding to an organization’s data. When doing…

转自:https://blog.minio.io/stream-processing-with-apache-flink-and-minio-10da85590787 Modern technology trends like Machine Learning, Deep Learning, Artificial intelligence, and IoT have pushed the need for a reliable, scaleable storage platform that i…

Introduction This chapter will present an implementation recipe for an enterprise log storage and a search and analysis solution based on the Storm processor. Log data processing isn't necessarily a problem that needs solving again; it is, however, a…

从总体上看:akka-stream是由数据源头Source,流通节点Flow和数据流终点Sink三个框架性的流构件(stream components)组成的.这其中:Source和Sink是stream的两个独立端点,而Flow处于stream Source和Sink中间可能由多个通道式的节点组成,每个节点代表某些数据流元素转化处理功能,它们的链接顺序则可能代表整体作业的流程.一个完整的数据流(可运行数据流)必须是一个闭合的数据流,即:从外表上看,数据流两头必须连接一个Source和一个Sin…

http://engineering.linkedin.com/data-streams/apache-samza-linkedins-real-time-stream-processing-framework http://samza.incubator.apache.org/ 前两年一直在使用Kafka, 虽说Kafka一直说可用于online分析, 但是实际在使用的时候会发现问题很多, 比如deploy, 调度, failover等, 我们也做了一些相应的工作 Samza算是把这个补全了,…

原文:https://iwringer.wordpress.com/2015/08/03/patterns-for-streaming-realtime-analytics/ Introduction More and more use cases, we want to react to data faster, rather than storing them in a disk and periodically processing and acting on the data. This…

不多说,直接上干货! 一切来源于官网 http://kafka.apache.org/documentation/ Stream Processing 流处理 Many users of Kafka process data in processing pipelines consisting of multiple stages, where raw input data is consumed from Kafka topics and then aggregated, enriched,…

不多说,直接上干货! 一切来源于官网 http://kafka.apache.org/documentation/ Kafka for Stream Processing kafka的流处理 It isn't enough to just read, write, and store streams of data, the purpose is to enable real-time processing of streams. 仅仅读,写和存储是不够的,kafka的目标是实时的流处理. In…