中This course provides a complete journey into Apache Spark with Scala, designed for learners who want to analyze, design, implement, and evaluate big data applications. Beginning with the foundations of Spark architecture and Scala programming, learners will explore variables, functions, collections, and advanced Scala concepts such as traits, abstract classes, and exception handling. The course then advances into Spark RDD operations, streaming, windowing, and checkpointing, helping learners apply distributed transformations and implement real-time data pipelines. Finally, learners will construct integrated projects using Maven, connect Spark to external systems like Twitter APIs, and evaluate the impact of Hadoop 1.x vs 2.x in managing resources for scalable applications.
您将学到什么
Apply Scala fundamentals including variables, functions, and advanced concepts.
Implement Spark RDD operations, streaming, and fault-tolerant pipelines.
Build real-time big data solutions integrating Spark with external systems.
您将获得的技能
要了解的详细信息
添加到您的领英档案
August 2025
8 项作业
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该课程共有2个模块
This module introduces learners to the fundamentals of Apache Spark and the Scala programming language, equipping them with the foundational knowledge to build and manage big data applications. Starting with an overview of Spark’s architecture, flow, and integration with YARN, the module progresses to Scala essentials, covering variables, functions, loops, and collections. It then advances into key Scala concepts such as abstract classes, traits, exception handling, and access modifiers. By the end of this module, learners will be able to confidently apply Scala programming constructs within Spark environments to process and analyze data efficiently.
涵盖的内容
24个视频4个作业
This module explores the advanced features of Apache Spark, focusing on Resilient Distributed Datasets (RDDs), Spark Streaming, and real-time application integration. Learners will understand how to perform transformations and actions on RDDs, process live streaming data, and implement checkpointing for fault tolerance. The module also covers integration with external systems such as Twitter, project setup using Maven and Scala, and explains the differences between Hadoop 1.x and 2.x for Spark compatibility. By completing this module, learners will gain the ability to build scalable, fault-tolerant, real-time big data applications using Spark and Scala.
涵盖的内容
18个视频4个作业
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