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所在平台: Udemy |
课程主页: https://www.udemy.com/course/spring-cloud-data-flow-cloud-native-data-stream-processing/
课程评论：没有评论
课程名称：Spring Cloud Data Flow - 云原生数据流处理 课程概述： 本课程将深入了解Spring Cloud Data Flow的技术架构，并指导学员进行应用的安装和配置。课程内容涵盖从基本到高级的流处理应用的创建，例如时间记录器到TensorFlow图像检测流处理。您将学习以下内容： 1. Spring Cloud Data Flow的架构 2. Spring Cloud Data Flow的各个组件，如Skipper Server、Spring Cloud Data Flow Server以及Data Flow Shell 3. 使用Data Flow Shell和领域特定语言（DSL） 4. 消息代理的配置与使用，如RabbitMQ和Kafka 5. 在Amazon Web Service（AWS）EC2实例上安装和配置Spring Cloud Data Flow生态系统 6. 配置Grafana仪表盘进行流可视化 7. 源、汇和处理器的配置 8. 创建自定义源、汇和处理器应用 9. 使用Spring Tool Suite（STS）进行自定义代码开发 10. 使用Spring Data Flow WebUI并分析运行时日志 本课程旨在覆盖Spring Cloud Data Flow的所有方面，包括基本安装、Docker中的配置，以及创建各种类型的流应用，如ETL、导入/导出、预测分析和流事件处理等。课程中还包含一些实际示例和用例，以帮助您更好地理解，例如： - 从JDBC数据库提取数据和交互 - 从Twitter提取推文数据 - 对推文进行情感分析、语言分析和话题分析 - 使用TensorFlow处理器进行对象检测/预测 - 使用TensorFlow处理器进行姿态预测 无论您是初学者还是有经验的开发者，本课程都将为您提供全面的知识，以掌握Spring Cloud Data Flow及其应用。
Understand the technical architecture along with installation and configuration of Spring Cloud Data Flow Applications.Create basic to advanced Streaming applications like time logger to TensorFlow Image Detection Stream Flow.You will learn the following as part of this course.Architecture of Spring Cloud Data FlowComponents of Spring Cloud Data Flow like Skipper Server, Spring Cloud Data Flow Server, Data Flow ShellUsing Data Flow Shell and Domain Specific Language (DSL)Configuring and usage of message brokers like RabbitMQ, KafkaInstallation and configuration of Spring Cloud Data Flow Ecosystem in Amazon Web Service (AWS) EC2 InstancesConfiguring Grafana Dashboard for Stream visualizationConfiguration of Source, Sink and ProcessorCreating custom Source, Sink and Processor applicationCoding using Spring Tool Suite (STS) for custom code developmentWorking with Spring Data Flow WebUI and analyzing logs on runtimesThis course is designed to cover all aspects of Spring Cloud Data Flow from basic installation to configuration in Docker as well as creating all type of Streaming applications like ETL, import/export, Predictive Analytics, Streaming Event processing etc.,Few working examples/usecases are covered to have better understanding like Data extracting and interaction with JDBC databaseExtracting Twitter Data (Tweets) from TwitterSentiment analysis, Language Analysis and HashTag Analysis on Tweets from TwitterObject Detection/Prediction using TensorFlow processorPose Prediction using TensorFlow Processor
