DEV-343 | Spark Developer

DEV-343 | Spark Developer

This course introduces the Apache Spark distributed computing engine, and is suitable for developers, data analysts, architects, technical managers, and anyone who needs to use Spark in a hands-on manner.

About this course

Overview:
This course introduces the Apache Spark distributed computing engine, and is suitable for developers, data analysts, architects, technical managers, and anyone who needs to use Spark in a hands-on manner. It is based on the Spark 2.x release.The course provides a solid technical introduction to the Spark architecture and how Spark works. It covers the basic building blocks of Spark (e.g. RDDs and the distributed compute engine), as well as higher-level constructs that provide a simpler and more capable interface.It includes in-depth coverage of Spark SQL, DataFrames, and DataSets, which are now the preferred programming API. This includes exploring possible performance issues and strategies for optimization. Thecourse also covers more advanced capabilities such as the use of Spark Streaming to process streaming data, and integrating with the Kafka server.

Target Audience:
Software engineers that are looking to develop in-memory applications for time sensitive and highly iterative applications in an Enterprise HDP environment.

Prerequisites:
Students should be familiar with programming principles and have previous experience in software development using Scala. Previous experience with data streaming, SQL, and HDP is also helpful, but not required.

Format:
50% Lecture/Discussion
50% Hands-on-labs

Duration:
4 Days


( 20180413 Ver 1.3 LCW)

 

DEV-343 | HDP Developer: Apache Spark 2.x Live Training Schedule

Event Date Spaces left
HDP Developer: Apache Spark 2.x - Public - 4 (Melbourne, Australia) May 28, 2018, 9 a.m. -
May 31, 2018, 5 p.m. AEST
Unlimited

Curriculum

  • Course Logistics
  • DEV-343 | HDP Developer: Apache Spark 2.x Live Training Schedule
  • Course Presentation
  • Lesson Slides.pdf
  • Lab Connectivity Test
  • Spark 2.0 Lab Connectivity Test Instructions
  • Lab Guides
  • Important: Reaching the Spark UI.pdf
  • Lab 0.1 - Set up lab environment.pdf
  • Lab 1.1 - Start Interpreter.pdf
  • Lab 2.1 - First Look at Spark (Optional).pdf
  • Lab 2.2 - Spark Shell.pdf
  • Lab 3.1 - RDD Basics operations.pdf
  • Lab 3.2 - Operations On Multiple RDDs.pdf
  • Lab 4.1 - Data Formats.pdf
  • Lab 4.2 - Spark SQL Basics.pdf
  • Lab 4.3 - DataFrame Transformations.pdf
  • Lab 4.4 - The Dataset Typed API.pdf
  • Lab 4.5 - Splitting Text Data.pdf
  • Lab 5.1 - Exploring Grouping.pdf
  • Lab 5.2 - Seeing Catalyst at Work.pdf
  • Lab 5.3 - Seeing Tungsten at Work.pdf
  • Lab 6.1 - Caching.pdf
  • Lab 6.2 - Joins and Broadcasts.pdf
  • Lab 7.1 - Spark Job Submission.pdf
  • Lab 7.2 - More Complex Spark Standalong Appliction (Optional).pdf
  • Lab 8.1 - Spark Streaming (1.0+).pdf
  • Lab 8.2 - Spark Structured Streaming (2,0+).pdf
  • Lab - Pyspark Structured Streaming
  • Lab 8.3 Spark Structured Streaming with Kafka (2.0+).pdf
  • Give Us Your Feedback
  • Course & Instructor Survey

About this course

Overview:
This course introduces the Apache Spark distributed computing engine, and is suitable for developers, data analysts, architects, technical managers, and anyone who needs to use Spark in a hands-on manner. It is based on the Spark 2.x release.The course provides a solid technical introduction to the Spark architecture and how Spark works. It covers the basic building blocks of Spark (e.g. RDDs and the distributed compute engine), as well as higher-level constructs that provide a simpler and more capable interface.It includes in-depth coverage of Spark SQL, DataFrames, and DataSets, which are now the preferred programming API. This includes exploring possible performance issues and strategies for optimization. Thecourse also covers more advanced capabilities such as the use of Spark Streaming to process streaming data, and integrating with the Kafka server.

Target Audience:
Software engineers that are looking to develop in-memory applications for time sensitive and highly iterative applications in an Enterprise HDP environment.

Prerequisites:
Students should be familiar with programming principles and have previous experience in software development using Scala. Previous experience with data streaming, SQL, and HDP is also helpful, but not required.

Format:
50% Lecture/Discussion
50% Hands-on-labs

Duration:
4 Days


( 20180413 Ver 1.3 LCW)

 

Live events

DEV-343 | HDP Developer: Apache Spark 2.x Live Training Schedule

Event Date Spaces left
HDP Developer: Apache Spark 2.x - Public - 4 (Melbourne, Australia) May 28, 2018, 9 a.m. -
May 31, 2018, 5 p.m. AEST
Unlimited

Curriculum

  • Course Logistics
  • DEV-343 | HDP Developer: Apache Spark 2.x Live Training Schedule
  • Course Presentation
  • Lesson Slides.pdf
  • Lab Connectivity Test
  • Spark 2.0 Lab Connectivity Test Instructions
  • Lab Guides
  • Important: Reaching the Spark UI.pdf
  • Lab 0.1 - Set up lab environment.pdf
  • Lab 1.1 - Start Interpreter.pdf
  • Lab 2.1 - First Look at Spark (Optional).pdf
  • Lab 2.2 - Spark Shell.pdf
  • Lab 3.1 - RDD Basics operations.pdf
  • Lab 3.2 - Operations On Multiple RDDs.pdf
  • Lab 4.1 - Data Formats.pdf
  • Lab 4.2 - Spark SQL Basics.pdf
  • Lab 4.3 - DataFrame Transformations.pdf
  • Lab 4.4 - The Dataset Typed API.pdf
  • Lab 4.5 - Splitting Text Data.pdf
  • Lab 5.1 - Exploring Grouping.pdf
  • Lab 5.2 - Seeing Catalyst at Work.pdf
  • Lab 5.3 - Seeing Tungsten at Work.pdf
  • Lab 6.1 - Caching.pdf
  • Lab 6.2 - Joins and Broadcasts.pdf
  • Lab 7.1 - Spark Job Submission.pdf
  • Lab 7.2 - More Complex Spark Standalong Appliction (Optional).pdf
  • Lab 8.1 - Spark Streaming (1.0+).pdf
  • Lab 8.2 - Spark Structured Streaming (2,0+).pdf
  • Lab - Pyspark Structured Streaming
  • Lab 8.3 Spark Structured Streaming with Kafka (2.0+).pdf
  • Give Us Your Feedback
  • Course & Instructor Survey