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| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
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| |
| #' @include arrow-package.R |
| #' @include array.R |
| #' @title 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][Field], each a contiguous Arrow [Array]. |
| #' @usage NULL |
| #' @format NULL |
| #' @docType class |
| #' |
| #' @section 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". |
| #' |
| #' @section 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)`) |
| #' - `$RenameColumns(value)`: Set all column names (called by `names(batch) <- value`) |
| #' - `$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 `Array`s |
| #' @rdname RecordBatch |
| #' @name RecordBatch |
| #' @export |
| RecordBatch <- R6Class("RecordBatch", inherit = ArrowTabular, |
| public = list( |
| column = function(i) RecordBatch__column(self, i), |
| column_name = function(i) RecordBatch__column_name(self, i), |
| names = function() RecordBatch__names(self), |
| RenameColumns = function(value) RecordBatch__RenameColumns(self, value), |
| Equals = function(other, check_metadata = FALSE, ...) { |
| inherits(other, "RecordBatch") && RecordBatch__Equals(self, other, isTRUE(check_metadata)) |
| }, |
| GetColumnByName = function(name) { |
| assert_that(is.string(name)) |
| RecordBatch__GetColumnByName(self, name) |
| }, |
| SelectColumns = function(indices) RecordBatch__SelectColumns(self, indices), |
| AddColumn = function(i, new_field, value) { |
| RecordBatch__AddColumn(self, i, new_field, value) |
| }, |
| SetColumn = function(i, new_field, value) { |
| RecordBatch__SetColumn(self, i, new_field, value) |
| }, |
| RemoveColumn = function(i) RecordBatch__RemoveColumn(self, i), |
| Slice = function(offset, length = NULL) { |
| if (is.null(length)) { |
| RecordBatch__Slice1(self, offset) |
| } else { |
| RecordBatch__Slice2(self, offset, length) |
| } |
| }, |
| # Take, Filter, and SortIndices are methods on ArrowTabular |
| serialize = function() ipc___SerializeRecordBatch__Raw(self), |
| to_data_frame = function() { |
| RecordBatch__to_dataframe(self, use_threads = option_use_threads()) |
| }, |
| cast = function(target_schema, safe = TRUE, ..., options = cast_options(safe, ...)) { |
| assert_is(target_schema, "Schema") |
| assert_that(identical(self$schema$names, target_schema$names), msg = "incompatible schemas") |
| RecordBatch__cast(self, target_schema, options) |
| }, |
| invalidate = function() { |
| .Call(`_arrow_RecordBatch__Reset`, self) |
| super$invalidate() |
| } |
| ), |
| |
| active = list( |
| num_columns = function() RecordBatch__num_columns(self), |
| num_rows = function() RecordBatch__num_rows(self), |
| schema = function() RecordBatch__schema(self), |
| metadata = function(new) { |
| if (missing(new)) { |
| # Get the metadata (from the schema) |
| self$schema$metadata |
| } else { |
| # Set the metadata |
| new <- prepare_key_value_metadata(new) |
| out <- RecordBatch__ReplaceSchemaMetadata(self, new) |
| # ReplaceSchemaMetadata returns a new object but we're modifying in place, |
| # so swap in that new C++ object pointer into our R6 object |
| self$set_pointer(out$pointer()) |
| self |
| } |
| }, |
| columns = function() RecordBatch__columns(self) |
| ) |
| ) |
| |
| RecordBatch$create <- function(..., schema = NULL) { |
| arrays <- list2(...) |
| if (length(arrays) == 1 && inherits(arrays[[1]], c("raw", "Buffer", "InputStream", "Message"))) { |
| return(RecordBatch$from_message(arrays[[1]], schema)) |
| } |
| # Else, list of arrays |
| # making sure there are always names |
| if (is.null(names(arrays))) { |
| names(arrays) <- rep_len("", length(arrays)) |
| } |
| stopifnot(length(arrays) > 0) |
| |
| # TODO: should this also assert that they're all Arrays? |
| RecordBatch__from_arrays(schema, arrays) |
| } |
| |
| RecordBatch$from_message <- function(obj, schema) { |
| # Message/Buffer readers, previously in read_record_batch() |
| assert_is(schema, "Schema") |
| if (inherits(obj, c("raw", "Buffer"))) { |
| obj <- BufferReader$create(obj) |
| on.exit(obj$close()) |
| } |
| if (inherits(obj, "InputStream")) { |
| ipc___ReadRecordBatch__InputStream__Schema(obj, schema) |
| } else { |
| ipc___ReadRecordBatch__Message__Schema(obj, schema) |
| } |
| } |
| |
| #' @param ... A `data.frame` or a named set of Arrays or vectors. If given a |
| #' mixture of data.frames and vectors, the inputs will be autospliced together |
| #' (see examples). Alternatively, you can provide a single Arrow IPC |
| #' `InputStream`, `Message`, `Buffer`, or R `raw` object containing a `Buffer`. |
| #' @param schema a [Schema], or `NULL` (the default) to infer the schema from |
| #' the data in `...`. When providing an Arrow IPC buffer, `schema` is required. |
| #' @rdname RecordBatch |
| #' @examples |
| #' \donttest{ |
| #' batch <- record_batch(name = rownames(mtcars), mtcars) |
| #' dim(batch) |
| #' dim(head(batch)) |
| #' names(batch) |
| #' batch$mpg |
| #' batch[["cyl"]] |
| #' as.data.frame(batch[4:8, c("gear", "hp", "wt")]) |
| #' } |
| #' @export |
| record_batch <- RecordBatch$create |
| |
| #' @export |
| names.RecordBatch <- function(x) x$names() |