These functions are wrappers around their `dplyr` equivalents that set Spark SQL-compliant values for the `suffix` argument by replacing dots (`.`) with underscores (`_`). See [join] for a description of the general purpose of the functions.
# S3 method for tbl_spark
inner_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c("_x", "_y"),
auto_index = FALSE,
...,
sql_on = NULL
)# S3 method for tbl_spark
left_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c("_x", "_y"),
auto_index = FALSE,
...,
sql_on = NULL
)
# S3 method for tbl_spark
right_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c("_x", "_y"),
auto_index = FALSE,
...,
sql_on = NULL
)
# S3 method for tbl_spark
full_join(
x,
y,
by = NULL,
copy = FALSE,
suffix = c("_x", "_y"),
auto_index = FALSE,
...,
sql_on = NULL
)
A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
A character vector of variables to join by.
If NULL
, the default, *_join()
will perform a natural join, using all
variables in common across x
and y
. A message lists the variables so that you
can check they're correct; suppress the message by supplying by
explicitly.
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
.
To join by multiple variables, use a vector with length > 1.
For example, by = c("a", "b")
will match x$a
to y$a
and x$b
to
y$b
. Use a named vector to match different variables in x
and y
.
For example, by = c("a" = "b", "c" = "d")
will match x$a
to y$b
and
x$c
to y$d
.
To perform a cross-join, generating all combinations of x
and y
,
use by = character()
.
If x
and y
are not from the same data source,
and copy
is TRUE
, then y
will be copied into a
temporary table in same database as x
. *_join()
will automatically
run ANALYZE
on the created table in the hope that this will make
you queries as efficient as possible by giving more data to the query
planner.
This allows you to join tables across srcs, but it's potentially expensive operation so you must opt into it.
If there are non-joined duplicate variables in x
and
y
, these suffixes will be added to the output to disambiguate them.
Should be a character vector of length 2.
if copy
is TRUE
, automatically create
indices for the variables in by
. This may speed up the join if
there are matching indexes in x
.
Other parameters passed onto methods.
A custom join predicate as an SQL expression. The SQL
can refer to the LHS
and RHS
aliases to disambiguate
column names.