A record batch is a collection of equal-length arrays matching a particular Schema. It is a table-like data structure that is semantically a sequence of fields, each a contiguous Arrow Array.
record_batch(..., schema = NULL)
| ... | A |
|---|---|
| schema | a Schema, or |
Record batches are data-frame-like, and many methods you expect to work on
a data.frame are implemented for RecordBatch. This includes [, [[,
$, names, dim, nrow, ncol, head, and tail. You can also pull
the data from an Arrow record batch into R with as.data.frame(). See the
examples.
A caveat about the $ method: because RecordBatch is an R6 object,
$ is also used to access the object's methods (see below). Methods take
precedence over the table's columns. So, batch$Slice would return the
"Slice" method function even if there were a column in the table called
"Slice".
In addition to the more R-friendly S3 methods, a RecordBatch object has
the following R6 methods that map onto the underlying C++ methods:
$Equals(other): Returns TRUE if the other record batch is equal
$column(i): Extract an Array by integer position from the batch
$column_name(i): Get a column's name by integer position
$names(): Get all column names (called by names(batch))
$RenameColumns(value): Set all column names (called by names(batch) <- value)
$GetColumnByName(name): Extract an Array by string name
$RemoveColumn(i): Drops a column from the batch by integer position
$SelectColumns(indices): Return a new record batch with a selection of columns, expressed as 0-based integers.
$Slice(offset, length = NULL): Create a zero-copy view starting at the
indicated integer offset and going for the given length, or to the end
of the table if NULL, the default.
$Take(i): return an RecordBatch with rows at positions given by
integers (R vector or Array Array) i.
$Filter(i, keep_na = TRUE): return an RecordBatch with rows at positions where logical
vector (or Arrow boolean Array) i is TRUE.
$SortIndices(names, descending = FALSE): return an Array of integer row
positions that can be used to rearrange the RecordBatch in ascending or
descending order by the first named column, breaking ties with further named
columns. descending can be a logical vector of length one or of the same
length as names.
$serialize(): Returns a raw vector suitable for interprocess communication
$cast(target_schema, safe = TRUE, options = cast_options(safe)): Alter
the schema of the record batch.
There are also some active bindings
$num_columns
$num_rows
$schema
$metadata: Returns the key-value metadata of the Schema as a named list.
Modify or replace by assigning in (batch$metadata <- new_metadata).
All list elements are coerced to string. See schema() for more information.
$columns: Returns a list of Arrays
batch <- record_batch(name = rownames(mtcars), mtcars) dim(batch) #> [1] 32 12 dim(head(batch)) #> [1] 6 12 names(batch) #> [1] "name" "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" #> [11] "gear" "carb" batch$mpg #> Array #> <double> #> [ #> 21, #> 21, #> 22.8, #> 21.4, #> 18.7, #> 18.1, #> 14.3, #> 24.4, #> 22.8, #> 19.2, #> ... #> 15.2, #> 13.3, #> 19.2, #> 27.3, #> 26, #> 30.4, #> 15.8, #> 19.7, #> 15, #> 21.4 #> ] batch[["cyl"]] #> Array #> <double> #> [ #> 6, #> 6, #> 4, #> 6, #> 8, #> 6, #> 8, #> 4, #> 4, #> 6, #> ... #> 8, #> 8, #> 8, #> 4, #> 4, #> 4, #> 8, #> 6, #> 8, #> 4 #> ] as.data.frame(batch[4:8, c("gear", "hp", "wt")]) #> # A tibble: 5 x 3 #> gear hp wt #> <dbl> <dbl> <dbl> #> 1 3 110 3.22 #> 2 3 175 3.44 #> 3 3 105 3.46 #> 4 3 245 3.57 #> 5 4 62 3.19