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
open_dataset()
to point to a directory of data files and return a
Dataset
, then use dplyr
methods to query it.
open_dataset(sources, schema = NULL, partitioning = hive_partition(), ...)
Either a string path to a directory containing data files,
or a list of SourceFactory
objects as created by open_source()
.
Schema for the dataset. If NULL
(the default), the schema
will be inferred from the data sources.
When sources
is a file path, one of
A Schema
, in which case the file paths relative to sources
will be
parsed, and path segments will be matched with the schema fields. For
example, schema(year = int16(), month = int8())
would create partitions
for file paths like "2019/01/file.parquet", "2019/02/file.parquet", etc.
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 Schema
but the types will be autodetected)
A HivePartitioning
or HivePartitioningFactory
, as returned
by hive_partition()
which parses explicit or autodetected fields from
Hive-style path segments
NULL
for no partitioning
additional arguments passed to open_source()
when sources
is
a file path, otherwise ignored.
A Dataset R6 object. Use dplyr
methods on it to query the data,
or call $NewScan()
to construct a query directly.
vignette("dataset", package = "arrow")