| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # 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 |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| #' @title Table class |
| #' @description A Table is a sequence of [chunked arrays][ChunkedArray]. They |
| #' have a similar interface to [record batches][RecordBatch], but they can be |
| #' composed from multiple record batches or chunked arrays. |
| #' @usage NULL |
| #' @format NULL |
| #' @docType class |
| #' |
| #' @section Factory: |
| #' |
| #' The `Table$create()` function takes the following arguments: |
| #' |
| #' * `...` arrays, chunked arrays, or R vectors, with names; alternatively, |
| #' an unnamed series of [record batches][RecordBatch] may also be provided, |
| #' which will be stacked as rows in the table. |
| #' * `schema` a [Schema], or `NULL` (the default) to infer the schema from |
| #' the data in `...` |
| #' |
| #' @section S3 Methods and Usage: |
| #' Tables are data-frame-like, and many methods you expect to work on |
| #' a `data.frame` are implemented for `Table`. This includes `[`, `[[`, |
| #' `$`, `names`, `dim`, `nrow`, `ncol`, `head`, and `tail`. You can also pull |
| #' the data from an Arrow table into R with `as.data.frame()`. See the |
| #' examples. |
| #' |
| #' A caveat about the `$` method: because `Table` is an `R6` object, |
| #' `$` is also used to access the object's methods (see below). Methods take |
| #' precedence over the table's columns. So, `tab$Slice` would return the |
| #' "Slice" method function even if there were a column in the table called |
| #' "Slice". |
| #' |
| #' A caveat about the `[` method for row operations: only "slicing" is |
| #' currently supported. That is, you can select a continuous range of rows |
| #' from the table, but you can't filter with a `logical` vector or take an |
| #' arbitrary selection of rows by integer indices. |
| #' |
| #' @section R6 Methods: |
| #' In addition to the more R-friendly S3 methods, a `Table` object has |
| #' the following R6 methods that map onto the underlying C++ methods: |
| #' |
| #' - `$column(i)`: Extract a `ChunkedArray` by integer position from the table |
| #' - `$ColumnNames()`: Get all column names (called by `names(tab)`) |
| #' - `$GetColumnByName(name)`: Extract a `ChunkedArray` by string name |
| #' - `$field(i)`: Extract a `Field` from the table schema by integer position |
| #' - `$select(spec)`: Return a new table with a selection of columns. |
| #' This supports the usual `character`, `numeric`, and `logical` selection |
| #' methods as well as "tidy select" expressions. |
| #' - `$Slice(offset, length = NULL)`: Create a zero-copy view starting at the |
| #' indicated integer offset and going for the given length, or to the end |
| #' of the table if `NULL`, the default. |
| #' - `$serialize(output_stream, ...)`: Write the table to the given |
| #' [OutputStream] |
| #' - `$cast(target_schema, safe = TRUE, options = cast_options(safe))`: Alter |
| #' the schema of the record batch. |
| #' |
| #' There are also some active bindings |
| #' - `$num_columns` |
| #' - `$num_rows` |
| #' - `$schema` |
| #' - `$columns`: Returns a list of `ChunkedArray`s |
| #' @rdname Table |
| #' @name Table |
| #' @examples |
| #' \donttest{ |
| #' tab <- Table$create(name = rownames(mtcars), mtcars) |
| #' dim(tab) |
| #' dim(head(tab)) |
| #' names(tab) |
| #' tab$mpg |
| #' tab[["cyl"]] |
| #' as.data.frame(tab[4:8, c("gear", "hp", "wt")]) |
| #' } |
| #' @export |
| Table <- R6Class("Table", inherit = Object, |
| public = list( |
| column = function(i) { |
| assert_is(i, c("numeric", "integer")) |
| assert_that(length(i) == 1) |
| shared_ptr(ChunkedArray, Table__column(self, i)) |
| }, |
| ColumnNames = function() Table__ColumnNames(self), |
| GetColumnByName = function(name) { |
| assert_is(name, "character") |
| assert_that(length(name) == 1) |
| shared_ptr(ChunkedArray, Table__GetColumnByName(self, name)) |
| }, |
| field = function(i) shared_ptr(Field, Table__field(self, i)), |
| |
| serialize = function(output_stream, ...) write_table(self, output_stream, ...), |
| ToString = function() ToString_tabular(self), |
| |
| cast = function(target_schema, safe = TRUE, options = cast_options(safe)) { |
| assert_is(target_schema, "Schema") |
| assert_is(options, "CastOptions") |
| assert_that(identical(self$schema$names, target_schema$names), msg = "incompatible schemas") |
| shared_ptr(Table, Table__cast(self, target_schema, options)) |
| }, |
| |
| select = function(spec) { |
| spec <- enquo(spec) |
| if (quo_is_null(spec)) { |
| self |
| } else { |
| all_vars <- self$ColumnNames() |
| vars <- vars_select(all_vars, !!spec) |
| indices <- match(vars, all_vars) |
| shared_ptr(Table, Table__select(self, indices)) |
| } |
| }, |
| |
| Slice = function(offset, length = NULL) { |
| if (is.null(length)) { |
| shared_ptr(Table, Table__Slice1(self, offset)) |
| } else { |
| shared_ptr(Table, Table__Slice2(self, offset, length)) |
| } |
| }, |
| |
| Equals = function(other) { |
| Table__Equals(self, other) |
| } |
| ), |
| |
| active = list( |
| num_columns = function() Table__num_columns(self), |
| num_rows = function() Table__num_rows(self), |
| schema = function() shared_ptr(Schema, Table__schema(self)), |
| columns = function() map(Table__columns(self), shared_ptr, class = ChunkedArray) |
| ) |
| ) |
| |
| Table$create <- function(..., schema = NULL){ |
| dots <- list2(...) |
| # making sure there are always names |
| if (is.null(names(dots))) { |
| names(dots) <- rep_len("", length(dots)) |
| } |
| stopifnot(length(dots) > 0) |
| shared_ptr(Table, Table__from_dots(dots, schema)) |
| } |
| |
| #' @export |
| as.data.frame.Table <- function(x, row.names = NULL, optional = FALSE, use_threads = TRUE, ...){ |
| Table__to_dataframe(x, use_threads = option_use_threads()) |
| } |
| |
| #' @export |
| dim.Table <- function(x) { |
| c(x$num_rows, x$num_columns) |
| } |
| |
| #' @export |
| names.Table <- function(x) x$ColumnNames() |
| |
| #' @export |
| `[.Table` <- `[.RecordBatch` |
| |
| #' @export |
| `[[.Table` <- `[[.RecordBatch` |
| |
| #' @export |
| `$.Table` <- `$.RecordBatch` |
| |
| #' @export |
| head.Table <- head.RecordBatch |
| |
| #' @export |
| tail.Table <- tail.RecordBatch |