Metadata

This article describes the various data and metadata object types supplied by arrow, and documents how these objects are structured.

Arrow metadata classes

The arrow package defines the following classes for representing metadata:

A Schema is a list of Field objects used to describe the structure of a tabular data object; where
A Field specifies a character string name and a DataType; and
A DataType is an attribute controlling how values are represented

Consider this:

df <- data.frame(x = 1:3, y = c("a", "b", "c"))
tb <- arrow_table(df)
tb$schema

## Schema
## x: int32
## y: string
## 
## See $metadata for additional Schema metadata

The schema that has been automatically inferred could also be manually created:

schema(
  field(name = "x", type = int32()),
  field(name = "y", type = utf8())
)

## Schema
## x: int32
## y: string

The schema() function allows the following shorthand to define fields:

schema(x = int32(), y = utf8())

## Schema
## x: int32
## y: string

Sometimes it is important to specify the schema manually, particularly if you want fine-grained control over the Arrow data types:

arrow_table(df, schema = schema(x = int64(), y = utf8()))

## Table
## 3 rows x 2 columns
## $x <int64>
## $y <string>
## 
## See $metadata for additional Schema metadata

arrow_table(df, schema = schema(x = float64(), y = utf8()))

## Table
## 3 rows x 2 columns
## $x <double>
## $y <string>
## 
## See $metadata for additional Schema metadata

R object attributes

Arrow supports custom key-value metadata attached to Schemas. When we convert a data.frame to an Arrow Table or RecordBatch, the package stores any attributes() attached to the columns of the data.frame in the Arrow object Schema. Attributes added to objects in this fashion are stored under the r key, as shown below:

# data frame with custom metadata
df <- data.frame(x = 1:3, y = c("a", "b", "c"))
attr(df, "df_meta") <- "custom data frame metadata"
attr(df$y, "col_meta") <- "custom column metadata"

# when converted to a Table, the metadata is preserved
tb <- arrow_table(df)
tb$metadata

## $r
## $r$attributes
## $r$attributes$df_meta
## [1] "custom data frame metadata"
## 
## 
## $r$columns
## $r$columns$x
## NULL
## 
## $r$columns$y
## $r$columns$y$attributes
## $r$columns$y$attributes$col_meta
## [1] "custom column metadata"
## 
## 
## $r$columns$y$columns
## NULL

It is also possible to assign additional string metadata under any other key you wish, using a command like this:

tb$metadata$new_key <- "new value"

Metadata attached to a Schema is preserved when writing the Table to Arrow/Feather or Parquet formats. When reading those files into R, or when calling as.data.frame() on a Table or RecordBatch, the column attributes are restored to the columns of the resulting data.frame. This means that custom data types, including haven::labelled, vctrs annotations, and others, are preserved when doing a round-trip through Arrow.

Note that the attributes stored in $metadata$r are only understood by R. If you write a data.frame with haven columns to a Feather file and read that in Pandas, the haven metadata won’t be recognized there. Similarly, Pandas writes its own custom metadata, which the R package does not consume. You are free, however, to define custom metadata conventions for your application and assign any (string) values you want to other metadata keys.

Arrow metadata classes

R object attributes

Further reading