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Lynda - Extending Hadoop for Data Science: Streaming, Spark, Storm, and Kafka
Categories: Tutorials
Lynda - Extending Hadoop for Data Science: Streaming, Spark, Storm, and Kafka - 516574
Lynda - Extending Hadoop for Data Science: Streaming, Spark, Storm, and Kafka
Extend your Hadoop data science knowledge by learning how to use other Apache data science platforms, libraries, and tools. This course goes beyond the basics of Hadoop MapReduce, into other key Apache libraries to bring flexibility to your Hadoop clusters. Coverage of core Spark, SparkSQL, SparkR, and SparkML is included. Learn how to scale and visualize your data with interactive Databricks clusters and notebooks and other implementations. This course is designed to help those working data science, development, or analytics get familiar with attendant technologies.


Table of Contents

  • Introduction
  • 1. Hadoop Core Fundamentals
  • 2. Setting Up a Hadoop Dev Environment
  • 3. Hadoop Batch Processing
  • 4. Fast Hadoop Options
  • 5. Spark Basics
  • 6. Using Spark
  • 7. Spark Libraries
  • 8. Spark Streaming
  • 9. Hadoop Streaming
  • 10. Modern Hadoop Architectures
  • Conclusion

    • Lynda - Extending Hadoop for Data Science: Streaming, Spark, Storm, and Kafka


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