A Practical Introduction to Stream Processing培訓

  1. 大數據培訓
  2. Stream processing培訓
  3. A Practical Introduction to Stream Processing培訓

課程代碼

introtostreamprocessing

課程時長

21 時間： 同常來說包括休息是 3天

最低要求

  • Programming experience in any language
  • An understanding of Big Data concepts (Hadoop, etc.)

概觀

Stream Processing指的是“運動中的數據”的實時處理，即，在接收數據時對數據執行計算。這些數據被讀取為來自數據源的連續流，例如傳感器事件，網站用戶活動，金融交易，信用卡刷卡，點擊流等。 Stream Processing框架能夠讀取大量傳入數據並幾乎立即提供有價值的見解。

在這個以講師為主導的現場培訓（現場或遠程）中，參與者將學習如何使用現有的大數據存儲系統和相關的軟件應用程序和微服務來設置和集成不同的Stream Processing框架。

在培訓結束時，參與者將能夠：

  • 安裝和配置不同的Stream Processing框架，例如Spark Streaming和Kafka Streaming。
  • 理解並選擇最合適的工作框架。
  • 數據處理連續，同時，並以逐個記錄的方式進行。
  • 將Stream Processing解決方案與現有數據庫，數據倉庫，數據湖等集成。
  • 將最合適的流處理庫與企業應用程序和微服務集成在一起。

聽眾

  • 開發商
  • 軟件架構師

課程 格式

  • 部分講座，部分討論，練習和繁重的實踐練習

筆記

  • 要申請本課程的定制培訓，請聯繫我們安排。

Machine Translated

課程簡介

Introduction

  • Stream processing vs batch processing
  • Analytics-focused stream processing

Overview Frameworks and Programming Languages

  • Spark Streaming (Scala)
  • Kafka Streaming (Java)
  • Flink
  • Storm

Comparison of Features and Strengths of Each Framework

Overview of Data Sources

  • Live data as a series of events over time
  • Historical data sources

Deployment Options

  • In the cloud (AWS, etc.)
  • On premise (private cloud, etc.)

Setting up the Development Environment

Installing and Configuring

Assessing Your Data Analysis Needs

Integrating the Streaming Framework with Big Data Tools

Transforming the Input Data

Inspecting the Output Data

Integrating the Stream Processing Framework with Existing Applications and Microservices

Troubleshooting

Summary and Conclusion

客戶評論

★★★★★
★★★★★

課程分類

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Alluxio: Unifying Disparate Storage SystemsApache Kafka ConnectBig Data Analytics in HealthBuilding Kafka Solutions with ConfluentBuilding Data Pipelines with Apache KafkaHortonworks Data Platform (HDP) for AdministratorsDistributed Messaging with Apache KafkaBuilding Stream Processing Applications with Kafka StreamsConfluent KSQLMagellan: Geospatial Analytics on SparkSamza for Stream ProcessingApache Spark in the CloudSpark for DevelopersApache Spark SQLSpring Cloud和Kafka微服務

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