Expand description
§serde_arrow - convert sequences of Rust objects to and from Arrow arrays
The Arrow in-memory format is a powerful way to work with data-frame-like structures. However,
the API of the underlying Rust crates can be at times cumbersome to use due to the statically
typed nature of Rust. serde_arrow offers a simple way to convert Rust objects into Arrow
arrays and back. serde_arrow relies on Serde to interpret Rust objects.
Therefore, adding support for serde_arrow to custom types is as easy as using Serde’s derive
macros.
serde_arrow supports the arrow crate. The Arrow
version can be selected via features.
serde_arrow relies on a schema to translate between Rust and Arrow as their type systems do
not directly match. The schema is expressed as a collection of Arrow fields with additional
metadata describing the arrays. For example, to convert a vector of Rust strings representing
timestamps to an Arrow Timestamp array, the schema should contain a field with data type
Timestamp. serde_arrow can derive the schema from the data or the Rust types
themselves via schema tracing, but does not require it. It is always possible to specify the
schema manually. See the schema module and SchemaLike for
further details.
§Overview
See also:
- the quickstart guide for more examples of how to use this package
- the status summary for an overview of the supported Arrow and Rust constructs
§Example
use arrow::datatypes::FieldRef;
use serde_arrow::schema::{SchemaLike, TracingOptions};
#[derive(Serialize, Deserialize)]
struct Record {
a: f32,
b: i32,
}
let records = vec![
Record { a: 1.0, b: 1 },
Record { a: 2.0, b: 2 },
Record { a: 3.0, b: 3 },
];
// Determine Arrow schema
let fields = Vec::<FieldRef>::from_type::<Record>(TracingOptions::default())?;
// Build the record batch
let batch = serde_arrow::to_record_batch(&fields, &records)?;The RecordBatch can then be written to disk, e.g., as parquet using the ArrowWriter from
the parquet crate.
§Features:
The version of arrow used can be selected via features. By default, no Arrow implementation
is used. In that case only the base features of serde_arrow are available.
The highest selected arrow-* version is used if multiple features are activated.
Note that because the highest version is selected, the features are not additive. In particular,
it is not possible to use serde_arrow::to_arrow for multiple different arrow versions at the
same time. See the next section for how to use serde_arrow in library code.
Available features:
| Arrow Feature | Arrow Version |
|---|---|
arrow-59 | arrow=59 |
arrow-58 | arrow=58 |
arrow-57 | arrow=57 |
arrow-56 | arrow=56 |
arrow-55 | arrow=55 |
arrow-54 | arrow=54 |
arrow-53 | arrow=53 |
§Usage in libraries
In libraries, it is not recommended to use the arrow functions directly. Rather it is
recommended to rely on the marrow-based functionality, as the features of marrow
are designed to be strictly additive.
For example, to build a record batch, first build the corresponding marrow types and then use them to build the record batch:
// Determine Arrow schema
let fields = Vec::<marrow::datatypes::Field>::from_type::<Record>(TracingOptions::default())?;
// Build the marrow arrays
let arrays = serde_arrow::to_marrow(&fields, &records)?;
// Build the record batch
let arrow_fields = fields.iter()
.map(arrow::datatypes::Field::try_from)
.collect::<Result<Vec<_>, _>>()?;
let arrow_arrays = arrays.into_iter()
.map(arrow::array::ArrayRef::try_from)
.collect::<Result<Vec<_>, _>>()?;
let record_batch = arrow::array::RecordBatch::try_new(
Arc::new(arrow::datatypes::Schema::new(arrow_fields)),
arrow_arrays,
);Re-exports§
pub use marrow;
Modules§
- _impl
- Internal. Do not use
- deserializer
- Deserialization of items
- schema
- Type mappings between Rust, Serde, and Arrow
- utils
- Helpers that may be useful when using
serde_arrow
Structs§
- Array
Builder - Construct arrays by pushing individual records
- Deserializer
- A structure to deserialize Arrow arrays into Rust objects
- Error
- Common errors during
serde_arrow’s usage - Serializer
- Wrap an
ArrayBuilderas a serializer
Enums§
- Error
Kind - Classifies an error for pattern matching
Functions§
- from_
arrow - Deserialize items from arrow arrays (requires one of the
arrow-*features) - from_
marrow - Deserialize items from marrow views
- from_
record_ batch - Deserialize items from a record batch (requires one of the
arrow-*features) - to_
arrow - Build arrow arrays from the given items (requires one of the
arrow-*features) - to_
marrow - Build marrow arrays from the given items
- to_
record_ batch - Build a record batch from the given items (requires one of the
arrow-*features)