《大数据实时计算系统实践》第一期 2018年小象学院 高清视频+资料 共2.83G
课程名称:
《大数据实时计算系统实践》第一期
课程简介：
本次的课程主要包括三大部分：
1.Flink基本原理概述。指导学员了解并掌握Flink使用过程中设计到的基本概念和简要API，介绍大数据实时流计算相关生态体系，着重梳理清楚Flink上下游体系，掌握Flink的核心技术原理，建立大数据实时流计算的方法论思维。
2.Flink实战生产技术。从实战出发，围绕实时流计算业务场景分析、基本编程模型、高级特性等系统性介绍Flink实时流计算的实战技术，使得学员具备研发Flink实时流计算相关应用的基础能力。
3.Druid是一款支持数据实时写入、低延时、高性能的OLAP引擎，具有优秀的数据聚合能力与实时查询能力。在大数据分析、实时计算、监控等领域都有特定的应用场景，是大数据基础架构建设中重要的一环。本次课程我们将介绍Druid的核心特性与原理，以及在性能调优以及最佳实践经验。
面向人群：
1.希望学习大数据实时流计算和实时OLAP的学生；
2.希望了解大数据实时流计算和OLAP实战技术的IT从业人员；
3.未来希望成为大数据实时流计算的求职者；
4.想在大数据实时流计算方向和OLAP方面进行深入研究者。
课程收益：
通过本课程的学习，学员将会收获：
1. 学员将系统性的了解并掌握大数据实时流计算的基本技术原理，结合Flink的生产技术案例，可基本实现独立开发、业务场景分析能力；
2. 了解大数据实时流计算上下游生态；
3. 理解Druid基础特性与正确使用方式，基本工作原理，并了解Druid面向的问题域以及典型的使用场景；
4. 对有志于从事大数据实时流计算以及OLAP研发的学员，提供系统实现原理的讲解与指导。
课程目录：
1、Flink基本概念与部署
2、DataStreamAPI介绍与实战
3、Window与Time
4、Connector
5、状态管理与恢复机制
6、Metrics与监控
7、Flink应用案例介绍
8、Druid基本概念与架构设计
9、Druid数据存储与写入
10、Druid实践介绍
视频截图：
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