- Practical Real-time Data Processing and Analytics
- Shilpi Saxena Saurabh Gupta
- 131字
- 2021-07-08 10:23:06
NRT – The Storm solution
This solution captures the high–level streaming data in real–time and routes it through some Queue/broker: Kafka or RabbitMQ. Then, the distributed processing part is handled through Storm topology, and once the insights are computed, they can be written to a fast write data store like Cassandra or some other queue like Kafka for further real–time downstream processing:

As per the figure, we collect real–time streaming data from diverse data sources, through push/pull collection agents like Flume, Logstash, FluentD, or Kafka adapters. Then, the data is written to Kafka partitions, Storm topologies pull/read the streaming data from Kafka and processes this flowing data in its topology, and writes the insights/results to Cassandra or some other real–time dashboards.
- 編寫整潔的Python代碼(第2版)
- C#程序設計(慕課版)
- 新手學Visual C# 2008程序設計
- Learning AWS Lumberyard Game Development
- 新編Premiere Pro CC從入門到精通
- Scala謎題
- PhoneGap Mobile Application Development Cookbook
- Protocol-Oriented Programming with Swift
- C語言開發(fā)基礎教程(Dev-C++)(第2版)
- Learning Apache Cassandra
- C語言從入門到精通
- Spring+Spring MVC+MyBatis從零開始學
- Python網(wǎng)絡爬蟲實例教程(視頻講解版)
- 算法超簡單:趣味游戲帶你輕松入門與實踐
- C++面向對象程序設計教程