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R Programming Intermediate: Profiling
Learn how to find the bottlenecks in your R codePreview the first lesson free — get full access to all 3 lessons.
Intermediate Provider : Tom Rosenwinkel 3 Lessons · 9m in English
Course Description
What can you do when your R code takes a long time to run? What are some reasons the code might run so slowly? The profiling package for R provides insights that can answer these questions. Writing fast and memory-efficient code is an essential skill for any R programmer, and the information from the performance profile can help not only to find problems, but suggest how to resolve them. The topics discussed in these lessons will provide you the tools you need for scaling up the size of the R projects you write.
In these lessons, you will learn how to profile the performance of R code. We will use the profiling package of R, explore the different time and memory measurements taken, and interpret the results. By the end of these lessons, you will be able to profile your own R code to identify bottlenecks due to slow code or memory allocation inefficiencies.
What You'll Learn
- Profile the performance of R code using R's profiling tools
- Use the profvis package to measure code execution
- Interpret the time and memory measurements taken by the R profiler
- Identify bottlenecks caused by slow code or memory allocation inefficiencies
- Apply best practices for acting on the results of the R profiler
- Explain the results produced by the R profiler
Key Takeaways
- Profiling provides insights into why R code runs slowly and how to resolve the issues.
- Writing fast and memory-efficient code is an essential skill for any R programmer.
- The R profiling package takes both time and memory measurements that can be interpreted to find problems.
- Performance profile information helps scale up the size of R projects.
- By the end of the lessons, learners can profile their own R code to identify bottlenecks due to slow code or memory allocation inefficiencies.
Frequently Asked Questions
What will I be able to do after completing this course?
You will be able to profile your own R code to identify bottlenecks due to slow code or memory allocation inefficiencies.
Which tool does this course use for profiling?
The course uses the profiling package of R, including the Profvis package, to explore time and memory measurements and interpret the results.
What topics are covered in the lessons?
The lessons cover the Profvis Package, Interpreting Profiling Results, and Memory Profiling.
Who is this course for?
It is intended for R programmers who want to write fast and memory-efficient code and scale up the size of the R projects they write.
What skills does this course help develop?
It helps develop skills in bottleneck analysis and memory management.
