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R High Performance Programming

R High Performance Programming

By : Aloysius Shao Qin Lim, Tjhi W Chandra
4.4 (14)
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R High Performance Programming

R High Performance Programming

4.4 (14)
By: Aloysius Shao Qin Lim, Tjhi W Chandra

Overview of this book

This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem.
Table of Contents (12 chapters)
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11
Index

Chapter 7. Processing Large Datasets with Limited RAM

In the previous chapter, we learned how to optimize the memory consumption of R programs by reducing the copying of data and by removing temporary data. Sometimes, that is still not enough. We might have data that is too large to even fit into memory, let alone perform any computations on them, or even if the data can fit into memory, there is not much free memory left for the analyses that we need to perform.

In this chapter, we will learn advanced techniques to overcome memory limitations and process large datasets.

This chapter covers:

  • Using memory-efficient data structures
  • Using memory-mapped files and processing data in chunks

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