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Apache Spark and Scala

Track :

Programming

Lessons no : 57

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What will you learn in this course?
  • Master data processing with Apache Spark's high-level APIs in Scala, Java, Python, and R for scalable analytics
  • Implement efficient big data transformations and actions using Spark's core components and RDDs in Scala
  • Design and develop Spark applications optimized for large-scale data analysis and machine learning tasks
  • Utilize Spark SQL and DataFrames for structured data querying and manipulation in Scala and Python
  • Apply Spark Streaming for real-time data processing and analytics in Scala and Java
  • Optimize Spark performance through tuning, caching, and resource management techniques
  • Integrate Spark with Hadoop, Kafka, and other big data tools for comprehensive data pipelines
  • Develop scalable machine learning models using Spark MLlib in Scala and Python
  • Implement best practices for debugging, testing, and deploying Spark applications in production environments
  • Leverage Spark's GraphX for graph processing and analysis on large datasets
  • Utilize Spark's ecosystem to build end-to-end data analytics and data science solutions
  • Understand the architecture and execution model of Spark for efficient large-scale data processing

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Lessons | 57
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Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs.