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 method to indicate how the file's paths should be interpreted to define
 partitioning.
 DirectoryPartitioning describes how to interpret raw path segments, in
 order. For example, schema(year = int16(), month = int8()) would define
 partitions for file paths like &quot;2019/01/file.parquet&quot;,
 &quot;2019/02/file.parquet&quot;, etc. In this scheme NULL values will be skipped. In
 the previous example: when writing a dataset if the month was NA (or
 NULL), the files would be placed in &quot;2019/file.parquet&quot;. When reading, the
 rows in &quot;2019/file.parquet&quot; would return an NA for the month column. An
 error will be raised if an outer directory is NULL and an inner directory
 is not.
 HivePartitioning is for Hive-style partitioning, which embeds field
 names and values in path segments, such as
 &quot;/year=2019/month=2/data.parquet&quot;. Because fields are named in the path
 segments, order does not matter. This partitioning scheme allows NULL
 values. They will be replaced by a configurable null_fallback which
 defaults to the string &quot;__HIVE_DEFAULT_PARTITION__&quot; when writing. When
 reading, the null_fallback string will be replaced with NAs as
 appropriate.
 PartitioningFactory subclasses instruct the DatasetFactory to detect
 partition features from the file paths."><meta property="og:description" content="Pass a Partitioning object to a FileSystemDatasetFactory's $create()
 method to indicate how the file's paths should be interpreted to define
 partitioning.
 DirectoryPartitioning describes how to interpret raw path segments, in
 order. For example, schema(year = int16(), month = int8()) would define
 partitions for file paths like &quot;2019/01/file.parquet&quot;,
 &quot;2019/02/file.parquet&quot;, etc. In this scheme NULL values will be skipped. In
 the previous example: when writing a dataset if the month was NA (or
 NULL), the files would be placed in &quot;2019/file.parquet&quot;. When reading, the
 rows in &quot;2019/file.parquet&quot; would return an NA for the month column. An
 error will be raised if an outer directory is NULL and an inner directory
 is not.
 HivePartitioning is for Hive-style partitioning, which embeds field
 names and values in path segments, such as
 &quot;/year=2019/month=2/data.parquet&quot;. Because fields are named in the path
 segments, order does not matter. This partitioning scheme allows NULL
 values. They will be replaced by a configurable null_fallback which
 defaults to the string &quot;__HIVE_DEFAULT_PARTITION__&quot; when writing. When
 reading, the null_fallback string will be replaced with NAs as
 appropriate.
 PartitioningFactory subclasses instruct the DatasetFactory to detect
 partition features from the file paths."><meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png"><meta property="og:image:alt" content="Apache Arrow logo, displaying the triple chevron image adjacent to the text"><!-- Matomo --><script>
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       <h1>Define Partitioning for a Dataset</h1>
       <small class="dont-index">Source: <a href="https://github.com/apache/arrow/blob/main/r/R/dataset-partition.R" class="external-link"><code>R/dataset-partition.R</code></a></small>
       <div class="d-none name"><code>Partitioning.Rd</code></div>
     </div>

     <div class="ref-description section level2">
     <p>Pass a <code>Partitioning</code> object to a <a href="Dataset.html">FileSystemDatasetFactory</a>'s <code>$create()</code>
 method to indicate how the file's paths should be interpreted to define
 partitioning.</p>
 <p><code>DirectoryPartitioning</code> describes how to interpret raw path segments, in
 order. For example, <code>schema(year = int16(), month = int8())</code> would define
 partitions for file paths like "2019/01/file.parquet",
 "2019/02/file.parquet", etc. In this scheme <code>NULL</code> values will be skipped. In
 the previous example: when writing a dataset if the month was <code>NA</code> (or
 <code>NULL</code>), the files would be placed in "2019/file.parquet". When reading, the
 rows in "2019/file.parquet" would return an <code>NA</code> for the month column. An
 error will be raised if an outer directory is <code>NULL</code> and an inner directory
 is not.</p>
 <p><code>HivePartitioning</code> is for Hive-style partitioning, which embeds field
 names and values in path segments, such as
 "/year=2019/month=2/data.parquet". Because fields are named in the path
 segments, order does not matter. This partitioning scheme allows <code>NULL</code>
 values. They will be replaced by a configurable <code>null_fallback</code> which
 defaults to the string <code>"__HIVE_DEFAULT_PARTITION__"</code> when writing. When
 reading, the <code>null_fallback</code> string will be replaced with <code>NA</code>s as
 appropriate.</p>
 <p><code>PartitioningFactory</code> subclasses instruct the <code>DatasetFactory</code> to detect
 partition features from the file paths.</p>
     </div>


     <div class="section level2">
     <h2 id="factory">Factory<a class="anchor" aria-label="anchor" href="#factory"></a></h2>


 <p>Both <code>DirectoryPartitioning$create()</code> and <code>HivePartitioning$create()</code>
 methods take a <a href="Schema-class.html">Schema</a> as a single input argument. The helper
 function <code><a href="hive_partition.html">hive_partition(...)</a></code> is shorthand for
 <code>HivePartitioning$create(schema(...))</code>.</p>
 <p>With <code>DirectoryPartitioningFactory$create()</code>, you can provide just the
 names of the path segments (in our example, <code>c("year", "month")</code>), and
 the <code>DatasetFactory</code> will infer the data types for those partition variables.
 <code>HivePartitioningFactory$create()</code> takes no arguments: both variable names
 and their types can be inferred from the file paths. <code><a href="hive_partition.html">hive_partition()</a></code> with
 no arguments returns a <code>HivePartitioningFactory</code>.</p>
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	method to indicate how the file's paths should be interpreted to define
	partitioning.
	DirectoryPartitioning describes how to interpret raw path segments, in
	order. For example, schema(year = int16(), month = int8()) would define
	partitions for file paths like "2019/01/file.parquet",
	"2019/02/file.parquet", etc. In this scheme NULL values will be skipped. In
	the previous example: when writing a dataset if the month was NA (or
	NULL), the files would be placed in "2019/file.parquet". When reading, the
	rows in "2019/file.parquet" would return an NA for the month column. An
	error will be raised if an outer directory is NULL and an inner directory
	is not.
	HivePartitioning is for Hive-style partitioning, which embeds field
	names and values in path segments, such as
	"/year=2019/month=2/data.parquet". Because fields are named in the path
	segments, order does not matter. This partitioning scheme allows NULL
	values. They will be replaced by a configurable null_fallback which
	defaults to the string "__HIVE_DEFAULT_PARTITION__" when writing. When
	reading, the null_fallback string will be replaced with NAs as
	appropriate.
	PartitioningFactory subclasses instruct the DatasetFactory to detect
	partition features from the file paths."><meta property="og:description" content="Pass a Partitioning object to a FileSystemDatasetFactory's $create()
	method to indicate how the file's paths should be interpreted to define
	partitioning.
	DirectoryPartitioning describes how to interpret raw path segments, in
	order. For example, schema(year = int16(), month = int8()) would define
	partitions for file paths like "2019/01/file.parquet",
	"2019/02/file.parquet", etc. In this scheme NULL values will be skipped. In
	the previous example: when writing a dataset if the month was NA (or
	NULL), the files would be placed in "2019/file.parquet". When reading, the
	rows in "2019/file.parquet" would return an NA for the month column. An
	error will be raised if an outer directory is NULL and an inner directory
	is not.
	HivePartitioning is for Hive-style partitioning, which embeds field
	names and values in path segments, such as
	"/year=2019/month=2/data.parquet". Because fields are named in the path
	segments, order does not matter. This partitioning scheme allows NULL
	values. They will be replaced by a configurable null_fallback which
	defaults to the string "__HIVE_DEFAULT_PARTITION__" when writing. When
	reading, the null_fallback string will be replaced with NAs as
	appropriate.
	PartitioningFactory subclasses instruct the DatasetFactory to detect
	partition features from the file paths."><meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png"><meta property="og:image:alt" content="Apache Arrow logo, displaying the triple chevron image adjacent to the text"><!-- Matomo --><script>
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	<h1>Define Partitioning for a Dataset</h1>
	<small class="dont-index">Source: <a href="https://github.com/apache/arrow/blob/main/r/R/dataset-partition.R" class="external-link"><code>R/dataset-partition.R</code></a></small>
	<div class="d-none name"><code>Partitioning.Rd</code></div>
	</div>

	<div class="ref-description section level2">
	<p>Pass a <code>Partitioning</code> object to a <a href="Dataset.html">FileSystemDatasetFactory</a>'s <code>$create()</code>
	method to indicate how the file's paths should be interpreted to define
	partitioning.</p>
	<p><code>DirectoryPartitioning</code> describes how to interpret raw path segments, in
	order. For example, <code>schema(year = int16(), month = int8())</code> would define
	partitions for file paths like "2019/01/file.parquet",
	"2019/02/file.parquet", etc. In this scheme <code>NULL</code> values will be skipped. In
	the previous example: when writing a dataset if the month was <code>NA</code> (or
	<code>NULL</code>), the files would be placed in "2019/file.parquet". When reading, the
	rows in "2019/file.parquet" would return an <code>NA</code> for the month column. An
	error will be raised if an outer directory is <code>NULL</code> and an inner directory
	is not.</p>
	<p><code>HivePartitioning</code> is for Hive-style partitioning, which embeds field
	names and values in path segments, such as
	"/year=2019/month=2/data.parquet". Because fields are named in the path
	segments, order does not matter. This partitioning scheme allows <code>NULL</code>
	values. They will be replaced by a configurable <code>null_fallback</code> which
	defaults to the string <code>"__HIVE_DEFAULT_PARTITION__"</code> when writing. When
	reading, the <code>null_fallback</code> string will be replaced with <code>NA</code>s as
	appropriate.</p>
	<p><code>PartitioningFactory</code> subclasses instruct the <code>DatasetFactory</code> to detect
	partition features from the file paths.</p>
	</div>


	<div class="section level2">
	<h2 id="factory">Factory<a class="anchor" aria-label="anchor" href="#factory"></a></h2>


	<p>Both <code>DirectoryPartitioning$create()</code> and <code>HivePartitioning$create()</code>
	methods take a <a href="Schema-class.html">Schema</a> as a single input argument. The helper
	function <code><a href="hive_partition.html">hive_partition(...)</a></code> is shorthand for
	<code>HivePartitioning$create(schema(...))</code>.</p>
	<p>With <code>DirectoryPartitioningFactory$create()</code>, you can provide just the
	names of the path segments (in our example, <code>c("year", "month")</code>), and
	the <code>DatasetFactory</code> will infer the data types for those partition variables.
	<code>HivePartitioningFactory$create()</code> takes no arguments: both variable names
	and their types can be inferred from the file paths. <code><a href="hive_partition.html">hive_partition()</a></code> with
	no arguments returns a <code>HivePartitioningFactory</code>.</p>
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