Avoid the copy-on-modify problem with R

- [Instructor] High-volume data is memory intensive.…No surprise, it's big data.…Whether it's on a hard drive or in computer memory,…it occupies a lot of space.…R has memory management routines that efficiently…allocate memory for objects such as data frames,…vectors, and lists.…For the most part, memory management happens automatically,…and you, as a programmer, don't need to be aware of it…or be involved in it.…However, there is one aspect of memory management…under your control that will make a difference…in execution speed and available memory.…

When an object, such as a data frame, is created,…R allocates memory for that object,…which is a good thing.…But when that object is modified,…it's actually copied, with the new modifications.…A new block of memory is allocated,…and the new object is created.…For a period of time, both objects exist in memory.…So each time you append an observation to an object,…R allocates a new segment in memory…to contain that new object.…

That allocation takes processing time…and occupies memory.…