Streaming System 第二章：The What- Where- When- and How of Data Processing
本文由《Streaming System》一书第二章的提炼翻译而来，译者才疏学浅，若有错误，欢迎指正。转载请注明出处，侵权必究。数据库 本章主要介绍鲁棒的处理乱序数据的核心概念，这些概念的运用使流处理系统超越批处理系统的关键所在。并发 路线图 上一章中，咱们介绍了两个很是关键的概念：app 事件时间和处理时间，只有在事件时间维度对数据进行处理，才能保证计算结果的准确性 窗口：窗口是处理无界数据流的
相关文章
- 1. Streaming System 第二章：The What- Where- When- and How of Data Processing
- 2. What and where are the stack and heap?
- 3. 转：What Are The Pros and Cons of HTTP Live Streaming (HLS)?
- 4. What are Huge Pages and the advantages of using them?
- 5. What the differece between nio and io
- 6. Data Processing with SMACK: Spark, Mesos, Akka, Cassandra, and Kafka
- 7. What is AMQP? and the architecture
- 8. How JavaScript works: an overview of the engine, the runtime, and the call stack
- 9. Project Butter - How It Works And What It Added
- 10. How AHI Fintech and DataVisor are Securing Data through AI and Big Data
- 更多相关文章...
- • XSLT system-property() 函数 - XSLT 教程
- • MyBatis choose、when、otherwise标签 - MyBatis教程
- • RxJava操作符（七）Conditional and Boolean
- • Kotlin学习（二）基本类型
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Streaming System 第二章：The What- Where- When- and How of Data Processing
- 2. What and where are the stack and heap?
- 3. 转：What Are The Pros and Cons of HTTP Live Streaming (HLS)?
- 4. What are Huge Pages and the advantages of using them?
- 5. What the differece between nio and io
- 6. Data Processing with SMACK: Spark, Mesos, Akka, Cassandra, and Kafka
- 7. What is AMQP? and the architecture
- 8. How JavaScript works: an overview of the engine, the runtime, and the call stack
- 9. Project Butter - How It Works And What It Added
- 10. How AHI Fintech and DataVisor are Securing Data through AI and Big Data