Real World Spark 2 – ScalaIDE Spark Core 2 Developer

Real World Spark 2 – ScalaIDE Spark Core 2 Developer, available at $19.99, has an average rating of 4, with 22 lectures, based on 1 reviews, and has 102 subscribers.

You will learn about Simply run a single command on your desktop, go for a coffee, and come back with a running distributed environment for cluster deployment Code in Scala against Spark. Transformation, Actions and Spark Monitoring Debug Spark Code within ScalaIDE This course is ideal for individuals who are Software engineers who want to expand their skills into the world of distributed computing or Developers who want to write/test their code against Scala / Spark It is particularly useful for Software engineers who want to expand their skills into the world of distributed computing or Developers who want to write/test their code against Scala / Spark.

Enroll now: Real World Spark 2 – ScalaIDE Spark Core 2 Developer

Summary

Title: Real World Spark 2 – ScalaIDE Spark Core 2 Developer

Price: $19.99

Average Rating: 4

Number of Lectures: 22

Number of Published Lectures: 22

Number of Curriculum Items: 22

Number of Published Curriculum Objects: 22

Original Price: £89.99

Quality Status: approved

Status: Live

What You Will Learn

Simply run a single command on your desktop, go for a coffee, and come back with a running distributed environment for cluster deployment
Code in Scala against Spark. Transformation, Actions and Spark Monitoring
Debug Spark Code within ScalaIDE

Who Should Attend

Software engineers who want to expand their skills into the world of distributed computing
Developers who want to write/test their code against Scala / Spark

Target Audiences

Software engineers who want to expand their skills into the world of distributed computing
Developers who want to write/test their code against Scala / Spark

Note : This course is built on top of the “Real World Vagrant – Build an Apache Spark Development Env! – Toyin Akin” course. So if you do not have a Spark + ScalaIDE environment already installed (within a VM or directly installed), you can take the stated course above.

Scala IDE provides advanced editing and debugging support for the development of pure Scala and mixed Scala-Java applications.�

Now with a shiny Scala debugger, semantic highlight, more reliable JUnit test finder, an ecosystem of related plugins, and much more.

Scala Debugger. Stepping through closures and Scala-aware display of debugging information.

Spark Monitoring and Instrumentation

While creating RDDs, performing transformations and executing actions, you will be working heavily within the monitoring view of the Web UI.

Every SparkContextlaunches a web UI, by default on port 4040, that displays useful information about the application. This includes:

A list of scheduler stages and tasks
A summary of RDD sizes and memory usage
Environmental information.
Information about the running executors

Why Apache Spark …

Apache Spark�run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing. Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Apache Spark can combine SQL, streaming, and complex analytics.

Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.

Course Curriculum

Chapter 1: Introduction to Scala, Spark Core via ScalaIDE

Lecture 1: A quick tour of ScalaIDE with Spark

Lecture 2: Suggested Spark Udemy curriculum courses to follow …

Chapter 2: Author, Equipment and Compensation

Lecture 1: My experience within the Enterprise

Lecture 2: Spark job compensation for those in this field.

Lecture 3: Memory Requirements

Lecture 4: Recommended Hardware for Spark and Hadoop labs …

Chapter 3: Setup the Environment

Lecture 1: Resource files for the course

Lecture 2: Spark setup

Lecture 3: Walking through the Base Vagrant Spark Box

Lecture 4: Upgrade and Package the Vagrant Box to Spark 2

Lecture 5: Register the updated Vagrant Spark Box

Chapter 4: Spark Core for Scala Developers (ScalaIDE)

Lecture 1: Boot up and Walkthrough of Spark ScalaIDE Environment

Lecture 2: Configure and Startup a Spark Environment for Distributed Computing

Lecture 3: Scala Spark RDD, Transformations, Actions and Monitoring I

Lecture 4: Scala Spark RDD, Transformations, Actions and Monitoring II

Lecture 5: Scala Spark RDD, Transformations, Actions and Monitoring III

Lecture 6: Scala Spark RDD, Transformations, Actions and Monitoring IV

Lecture 7: Scala Spark RDD, Transformations, Actions and Monitoring V

Lecture 8: Scala Spark RDD, Transformations, Actions and Monitoring VI

Lecture 9: Scala Spark RDD, Transformations, Actions and Monitoring VII

Lecture 10: Scala Spark RDD, Transformations, Actions and Monitoring VIII

Chapter 5: Conclusion

Lecture 1: Conclusion

Instructors

Toyin Akin
Big Data Engineer, Capital Markets FinTech Developer

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Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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