join.tbl_ffdf: Join ffdf tbls.
In edwindj/ffbase2: Dplyr for 'ff'

Description Usage Arguments Examples

See join for a description of the general purpose of the functions.

## S3 method for class 'ffdf'
inner_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'ffdf'
left_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'ffdf'
semi_join(x, y, by = NULL, ...)

## S3 method for class 'ffdf'
anti_join(x, y, by = NULL, ...)

`x,y`	tbls to join
`by`	a character vector of variables to join by. If `NULL`, the default, `join` will do a natural join, using all variables with common names across the two tables. A message lists the variables so that you can check they're right. To join by different variables on x and y use a named vector. For example, `by = c("a" = "b")` will match `x.a` to `y.b`.
`copy`	If `x` and `y` are not from the same data source, and `copy` is `TRUE`, then `y` will be copied into the same src as `x`. This allows you to join tables across srcs, but it is a potentially expensive operation so you must opt into it.
`...`	Included for compatibility with generic; otherwise ignored.

if (require(Lahman)){
data("Batting", package = "Lahman")
data("Master", package = "Lahman")

batting_ffdf <- tbl_ffdf(Batting)
person_ffdf <- tbl_ffdf(Master)

# Inner join: match batting and person data
inner_join(batting_ffdf, person_ffdf)

# Left join: keep batting data even if person missing
left_join(batting_ffdf, person_ffdf)

# Semi-join: find batting data for top 4 teams, 2010:2012
grid <- expand.grid(
  teamID = c("WAS", "ATL", "PHI", "NYA"),
  yearID = 2010:2012)
top4 <- semi_join(batting_ffdf, grid, copy = TRUE)

# Anti-join: find batting data with out player data
anti_join(batting_ffdf, person_ffdf)
}