Apache Spark Programming with Databricks

Price
$1,500.00 USD

Duration
2 Days

 

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

In this course, you will explore the fundamentals of Apache Spark and Delta Lake on Databricks. You will learn the architectural components of Spark, the DataFrame and Structured Streaming APIs, and how Delta Lake can improve your data pipelines. Lastly, you will execute streaming queries to process streaming data and understand the advantages of using Delta Lake.

This course will prepare you to take the Databricks Certified Associate Developer for Apache Spark exam.

Course Objectives

  • Define Spark’s architectural components
  • Describe how DataFrames are transformed, executed
  • , and optimized in Spark
  • Apply the DataFrame API to explore, preprocess, join, and ingest data in Spark
  • Apply the Structured Streaming API to perform analysis on streaming data
  • Use Delta Lake to improve the quality and performance of data pipelines
  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

Course Prerequisites

  • Completion of Introduction to Python for Data Science & Data Engineering, OR familiarity with Python and basic programming concepts, including data types, lists, dictionaries, variables, functions, loops, conditional statements, exception handling, accessing classes, and using third-party libraries
  • Basic knowledge of SQL, including writing queries using SELECT, WHERE, GROUP BY, ORDER BY, LIMIT, and JOIN

Agenda

Day 1

  • Spark overview
  • Databricks platform overview Spark SQL
  • DataFrame reader, writer, transformation, and aggregation
  • Datetimes
  • Complex types

Day 2

  • User-defined functions (UDFs) and vectorized UDFs
  • Spark internals
  • Query optimization
  • Partitioning
  • Streaming API
  • Delta Lake
 

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