Course Outline

Introduction

  • Overview of Spark and Hadoop features and architecture
  • Understanding big data
  • Python programming basics

Getting Started

  • Setting up Python, Spark, and Hadoop
  • Understanding data structures in Python
  • Understanding PySpark API
  • Understanding HDFS and MapReduce

Integrating Spark and Hadoop with Python

  • Implementing Spark RDD in Python
  • Processing data using MapReduce
  • Creating distributed datasets in HDFS

Machine Learning with Spark MLlib

Processing Big Data with Spark Streaming

Working with Recommender Systems

Working with Kafka, Sqoop, Kafka, and Flume

Apache Mahout with Spark and Hadoop

Troubleshooting

Summary and Next Steps

Requirements

  • Experience with Spark and Hadoop
  • Python programming experience

Audience

  • Data scientists
  • Developers
  21 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

Testimonials (3)

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