流式计算相关文章
2014-02-19 21:21
169 查看
What’s the Difference Between ESP and CEP?
http://www.complexevents.com/2006/08/01/what%E2%80%99s-the-difference-between-esp-and-cep/
主要介绍了ESP和CEP的区别
Event stream processing is focused more on high-speed querying of data in streams of events and applying mathematical algorithms to the event data.
CEP is focused more on extracting information from clouds of events created in enterprise IT and business systems. CEP includes event data analysis, but places emphasis on patterns of events, and abstracting and simplifying information in the patterns. The idea is to support as wide an area of enterprise management decision making as possible.
The difference between complex event processing and event stream processing
http://www.it-analysis.com/content.php?cid=8541
A typical ESP application is one such as algorithmic trading (stock tick information comes in, you apply calculations and rules, and decide on whether to buy or sell). That is, you have an event, a condition and an action. The event, in this case, is very simple.
However, CEP is about what we might call über-events or, more specifically, patterns of events. In fraud detection, for example, the fraud ‘event’ may in fact be made up of a sequence of inter-related events which, while simple on an individual basis, are complex when combined. Further, the individual events that make up such a complex event may be spread out over time, so a CEP engine needs to be able to handle long running processes. Moreover, the sequence in which these events can appear may vary so CEP needs to be able to handle non-linear vents.
To cut a long story short, CEP is a superset of ESP.
Papers in Stream Processing
http://jamielewis.me.uk/posts/2014-02-10-Stream-Processing-Papers.html
主要介绍有关流式计算方面的论文
Spark Streaming:大规模流式数据处理的新贵
http://www.csdn.net/article/2014-01-27/2818282-Spark-Streaming-big-data
主要介绍Berkeley 所提出的三种数据处理的模型,已经spark在这方面所对应的软件栈,包括Spark,Shark, Spark Streaming ,分别对应 batch data processing, ineractive query, streaming data processing
Understanding Big Data Processing and Analytics
http://www.developer.com/db/understanding-big-data-processing-and-analytics.html
同样总结了data processing的三种类型
http://www.complexevents.com/2006/08/01/what%E2%80%99s-the-difference-between-esp-and-cep/
主要介绍了ESP和CEP的区别
Event stream processing is focused more on high-speed querying of data in streams of events and applying mathematical algorithms to the event data.
CEP is focused more on extracting information from clouds of events created in enterprise IT and business systems. CEP includes event data analysis, but places emphasis on patterns of events, and abstracting and simplifying information in the patterns. The idea is to support as wide an area of enterprise management decision making as possible.
The difference between complex event processing and event stream processing
http://www.it-analysis.com/content.php?cid=8541
A typical ESP application is one such as algorithmic trading (stock tick information comes in, you apply calculations and rules, and decide on whether to buy or sell). That is, you have an event, a condition and an action. The event, in this case, is very simple.
However, CEP is about what we might call über-events or, more specifically, patterns of events. In fraud detection, for example, the fraud ‘event’ may in fact be made up of a sequence of inter-related events which, while simple on an individual basis, are complex when combined. Further, the individual events that make up such a complex event may be spread out over time, so a CEP engine needs to be able to handle long running processes. Moreover, the sequence in which these events can appear may vary so CEP needs to be able to handle non-linear vents.
To cut a long story short, CEP is a superset of ESP.
Papers in Stream Processing
http://jamielewis.me.uk/posts/2014-02-10-Stream-Processing-Papers.html
主要介绍有关流式计算方面的论文
Spark Streaming:大规模流式数据处理的新贵
http://www.csdn.net/article/2014-01-27/2818282-Spark-Streaming-big-data
主要介绍Berkeley 所提出的三种数据处理的模型,已经spark在这方面所对应的软件栈,包括Spark,Shark, Spark Streaming ,分别对应 batch data processing, ineractive query, streaming data processing
Understanding Big Data Processing and Analytics
http://www.developer.com/db/understanding-big-data-processing-and-analytics.html
同样总结了data processing的三种类型
相关文章推荐
- 并行计算相关文章
- 大数据入门第十六天——流式计算之storm详解(三)集群相关进阶
- 流式计算storm,spark文章
- 云计算相关犀利文章
- 网站架构相关PPT、文章整理
- tornado.ioloop.IOLoop相关文章
- javascript的相关技术文章的收藏
- sails 相关文章
- 一个简单的SpringMVC项目到底需要哪些JAR包(文章最后附上最简单的方法导相关包)
- 关于Spark运行流式计算程序中跑一段时间出现GC overhead limit exceeded
- Java 基础知识相关好文章
- Visual Assist插件使用的一些相关文章
- ndk相关文章
- p3p header相关的文章
- 一些跟开源相关的文章链接
- 电商之梳理MR/storm相关知识---计算
- cglib和asm相关的文章
- WordPress代码实现相关文章的几种方法(一)
- 使用IKAnalyzer分词计算文章关键字
- 读朱镕基辞职清华相关文章的启示