r/man/open_dataset.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dataset.R
\name{open_dataset}
\alias{open_dataset}
\title{Open a multi-file dataset}
\usage{
open_dataset(
  sources,
  schema = NULL,
  partitioning = hive_partition(),
  unify_schemas = NULL,
  ...
)
}
\arguments{
\item{sources}{Either:
\itemize{
\item a string path to a directory containing data files
\item a list of \code{Dataset} objects as created by this function
\item a list of \code{DatasetFactory} objects as created by \code{\link[=dataset_factory]{dataset_factory()}}.
}}

\item{schema}{\link{Schema} for the dataset. If \code{NULL} (the default), the schema
will be inferred from the data sources.}

\item{partitioning}{When \code{sources} is a file path, one of
\itemize{
\item a \code{Schema}, in which case the file paths relative to \code{sources} will be
parsed, and path segments will be matched with the schema fields. For
example, \code{schema(year = int16(), month = int8())} would create partitions
for file paths like "2019/01/file.parquet", "2019/02/file.parquet", etc.
\item a character vector that defines the field names corresponding to those
path segments (that is, you're providing the names that would correspond
to a \code{Schema} but the types will be autodetected)
\item a \code{HivePartitioning} or \code{HivePartitioningFactory}, as returned
by \code{\link[=hive_partition]{hive_partition()}} which parses explicit or autodetected fields from
Hive-style path segments
\item \code{NULL} for no partitioning
}

The default is to autodetect Hive-style partitions.}

\item{unify_schemas}{logical: should all data fragments (files, \code{Dataset}s)
be scanned in order to create a unified schema from them? If \code{FALSE}, only
the first fragment will be inspected for its schema. Use this
fast path when you know and trust that all fragments have an identical schema.
The default is \code{FALSE} when creating a dataset from a file path (because
there may be many files and scanning may be slow) but \code{TRUE} when \code{sources}
is a list of \code{Dataset}s (because there should be few \code{Dataset}s in the list
and their \code{Schema}s are already in memory).}

\item{...}{additional arguments passed to \code{dataset_factory()} when
\code{sources} is a file path, otherwise ignored. These may include "format" to
indicate the file format, or other format-specific options.}
}
\value{
A \link{Dataset} R6 object. Use \code{dplyr} methods on it to query the data,
or call \code{\link[=Scanner]{$NewScan()}} to construct a query directly.
}
\description{
Arrow Datasets allow you to query against data that has been split across
multiple files. This sharding of data may indicate partitioning, which
can accelerate queries that only touch some partitions (files). Call
\code{open_dataset()} to point to a directory of data files and return a
\code{Dataset}, then use \code{dplyr} methods to query it.
}
\seealso{
\code{vignette("dataset", package = "arrow")}
}