arrow (version 0.16.0.2)

RecordBatch: RecordBatch class

Description

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.

Usage

record_batch(..., schema = NULL)

Arguments

...

A data.frame or a named set of Arrays or vectors. If given a mixture of data.frames and vectors, the inputs will be autospliced together (see examples).

schema

a Schema, or NULL (the default) to infer the schema from the data in ...

S3 Methods and Usage

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".

A caveat about the [ method for row operations: only "slicing" is currently supported. That is, you can select a continuous range of rows from the table, but you can't filter with a logical vector or take an arbitrary selection of rows by integer indices.

R6 Methods

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))

  • $GetColumnByName(name): Extract an Array by string name

  • $RemoveColumn(i): Drops a column from the batch by integer position

  • $select(spec): Return a new record batch with a selection of columns. This supports the usual character, numeric, and logical selection methods as well as "tidy select" expressions.

  • $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): return an RecordBatch with rows at positions where logical vector (or Arrow boolean Array) i is TRUE.

  • $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

  • $columns: Returns a list of Arrays

Examples

Run this code
# NOT RUN {
batch <- record_batch(name = rownames(mtcars), mtcars)
dim(batch)
dim(head(batch))
names(batch)
batch$mpg
batch[["cyl"]]
as.data.frame(batch[4:8, c("gear", "hp", "wt")])
# }

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