Real World Spark 2 ScalaIDE Spark Core 2 Developer
- Development
- Apr 30, 2025

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
Who Should Attend
Target Audiences
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
Rating Distribution
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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