Partitioning {arrow}R Documentation

Define Partitioning for a Dataset


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.


Both DirectoryPartitioning$create() and HivePartitioning$create() methods take a Schema as a single input argument. The helper function hive_partition(...) is shorthand for HivePartitioning$create(schema(...)).

With DirectoryPartitioningFactory$create(), you can provide just the names of the path segments (in our example, c("year", "month")), and the DatasetFactory will infer the data types for those partition variables. HivePartitioningFactory$create() takes no arguments: both variable names and their types can be inferred from the file paths. hive_partition() with no arguments returns a HivePartitioningFactory.

[Package arrow version 9.0.0 Index]