What's in a Vector?

Gabriel Becker, Luke Tierney, Tomas Kalibera


1 Some background

1.1 An aside

R-core is not the enemy, even when they 'refuse' to do what you want

  • R's footprint is MASSIVE
    • Breaking changes are serious business, generally not going to happen
      • Think stringsAsFactors, drop
    • Despite this, I've found most (active) members receptive and pleasant

1.2 Our ultimate goal

Improve R without changing the final result of any R code

1.3 Previous "invisible" improvements to R

  • copy-on-modify - Gentleman and Ihaka, R-core team
  • byte compilation - Tierney [R 2.13+ ~2011-current]
  • shallow copying - Lawrence and Tierney [R.3.1.0 ~2014]

2 The ALTREP framework

2.1 knowing things about vectors


2.2 Maybe, sometimes

A contiguous block of memory isn't the best way to store a particular vector


Two main concepts

  1. Some things get really easy given prior knowledge
  2. If vectors get smarter, R gets smarter

3 "Smart vectors"

3.1 Knowing is (a lot more than) half the battle

Easy to guess answer of:

  • sort(x) when you know x is sorted
  • is.na(x) when you know x contains no NA s
  • match(5, x) / 5 %in% x when you know x is sorted
  • x < 5 when you know x is sorted

3.2 ALTREP introduces

  1. the concept of vectors that know whether they
    • are sorted
    • have no NAs
  2. changes in base R to take advantage of 'smart' vectors
  3. changes in base R to automatically create 'smart' vectors when appropriate

4 Custom vector implementations

4.1 Compact sequences

Lets be real for a second - how many numbers do we need before we know everything about n:m?

4.2 Run-length encoded vectors

Quick, ask a 3rd grader: what's the sum of three 5s, two 7s, and three more 5s?

4.3 Deferred-conversion strings

Strings are expensive compared to numeric values. Only make the ones you need.

(this makes default rownames for big data.frames fast)

4.4 Virtual subsetting

Do I really need two copies of x to know what rev(x)[4] is?

4.5 What else?


5 Defining custom vector representations

5.1 Time for some lowish level details


5.2 ALTREP vectors have 2 parts

  1. SEXP containing alt representation of the data
  2. SEXP containing R_NilValue or the vector expanded to traditional form

5.3 Once expanded part is non-null


5.4 An ALTREP class is

  • An (implicit) specific low-level representation of vector data
  • A set of methods which assume that representation to do things cheaper/faster

5.5 Mandatory methods

  • Length - Self explanatory
  • Dataptr - "Escape valve" if R internals really need a pointer
  • Elt - retrieve value of element i without using dataptr
  • Set_elt - Set the value of element i without using dataptr
  • Sort_check - Perform (and memoise) check for sortedness
  • Inspect - info to display when inspect internal is called

5.6 Metadata-related methods

  • Is_sorted - immediately return known sortedness info
  • No_NA - immediately return known "no NAs" info

5.7 Fastpass methods

  • Is_NA
  • Sum
  • Sort / Order
  • Match
  • Min / Max
  • Which_min / Which_max
  • Unique

Defaults make use of sortedness and no NA info

5.8 Acknowledgements

  • Luke Tierney
  • Tomas Kalibera
  • Michael Lawrence
  • The R-core team
  • You