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//! Contains [`RecordBatch`].
use std::sync::Arc;
use crate::array::*;
use crate::datatypes::*;
use crate::error::{ArrowError, Result};
/// A two-dimensional dataset with a number of
/// columns ([`Array`]) and rows and defined [`Schema`](crate::datatypes::Schema).
/// # Implementation
/// Cloning is `O(C)` where `C` is the number of columns.
#[derive(Clone, Debug, PartialEq)]
pub struct RecordBatch {
schema: Arc<Schema>,
columns: Vec<Arc<dyn Array>>,
}
impl RecordBatch {
/// Creates a [`RecordBatch`] from a schema and columns.
/// # Errors
/// This function errors iff
/// * `columns` is empty
/// * the schema and column data types do not match
/// * `columns` have a different length
/// # Example
///
/// ```
/// # use std::sync::Arc;
/// # use arrow2::array::PrimitiveArray;
/// # use arrow2::datatypes::{Schema, Field, DataType};
/// # use arrow2::record_batch::RecordBatch;
/// # fn main() -> arrow2::error::Result<()> {
/// let id_array = PrimitiveArray::from_slice([1i32, 2, 3, 4, 5]);
/// let schema = Arc::new(Schema::new(vec![
/// Field::new("id", DataType::Int32, false)
/// ]));
///
/// let batch = RecordBatch::try_new(
/// schema,
/// vec![Arc::new(id_array)]
/// )?;
/// # Ok(())
/// # }
/// ```
pub fn try_new(schema: Arc<Schema>, columns: Vec<Arc<dyn Array>>) -> Result<Self> {
let options = RecordBatchOptions::default();
Self::validate_new_batch(&schema, columns.as_slice(), &options)?;
Ok(RecordBatch { schema, columns })
}
/// Creates a [`RecordBatch`] from a schema and columns, with additional options,
/// such as whether to strictly validate field names.
///
/// See [`Self::try_new()`] for the expected conditions.
pub fn try_new_with_options(
schema: Arc<Schema>,
columns: Vec<Arc<dyn Array>>,
options: &RecordBatchOptions,
) -> Result<Self> {
Self::validate_new_batch(&schema, &columns, options)?;
Ok(RecordBatch { schema, columns })
}
/// Creates a new empty [`RecordBatch`].
pub fn new_empty(schema: Arc<Schema>) -> Self {
let columns = schema
.fields()
.iter()
.map(|field| new_empty_array(field.data_type().clone()).into())
.collect();
RecordBatch { schema, columns }
}
/// Validate the schema and columns using [`RecordBatchOptions`]. Returns an error
/// if any validation check fails.
fn validate_new_batch(
schema: &Schema,
columns: &[Arc<dyn Array>],
options: &RecordBatchOptions,
) -> Result<()> {
// check that there are some columns
if columns.is_empty() {
return Err(ArrowError::InvalidArgumentError(
"at least one column must be defined to create a record batch".to_string(),
));
}
// check that number of fields in schema match column length
if schema.fields().len() != columns.len() {
return Err(ArrowError::InvalidArgumentError(format!(
"number of columns({}) must match number of fields({}) in schema",
columns.len(),
schema.fields().len(),
)));
}
// check that all columns have the same row count, and match the schema
let len = columns[0].len();
// This is a bit repetitive, but it is better to check the condition outside the loop
if options.match_field_names {
for (i, column) in columns.iter().enumerate() {
if column.len() != len {
return Err(ArrowError::InvalidArgumentError(
"all columns in a record batch must have the same length".to_string(),
));
}
if column.data_type() != schema.field(i).data_type() {
return Err(ArrowError::InvalidArgumentError(format!(
"column types must match schema types, expected {:?} but found {:?} at column index {}",
schema.field(i).data_type(),
column.data_type(),
i)));
}
}
} else {
for (i, column) in columns.iter().enumerate() {
if column.len() != len {
return Err(ArrowError::InvalidArgumentError(
"all columns in a record batch must have the same length".to_string(),
));
}
if !column
.data_type()
.equals_datatype(schema.field(i).data_type())
{
return Err(ArrowError::InvalidArgumentError(format!(
"column types must match schema types, expected {:?} but found {:?} at column index {}",
schema.field(i).data_type(),
column.data_type(),
i)));
}
}
}
Ok(())
}
/// Returns the [`Schema`](crate::datatypes::Schema) of the record batch.
pub fn schema(&self) -> &Arc<Schema> {
&self.schema
}
/// Returns the number of columns in the record batch.
///
/// # Example
///
/// ```
/// # use std::sync::Arc;
/// # use arrow2::array::PrimitiveArray;
/// # use arrow2::datatypes::{Schema, Field, DataType};
/// # use arrow2::record_batch::RecordBatch;
/// # fn main() -> arrow2::error::Result<()> {
/// let id_array = PrimitiveArray::from_slice([1i32, 2, 3, 4, 5]);
/// let schema = Arc::new(Schema::new(vec![
/// Field::new("id", DataType::Int32, false)
/// ]));
///
/// let batch = RecordBatch::try_new(schema, vec![Arc::new(id_array)])?;
///
/// assert_eq!(batch.num_columns(), 1);
/// # Ok(())
/// # }
/// ```
pub fn num_columns(&self) -> usize {
self.columns.len()
}
/// Returns the number of rows in each column.
///
/// # Panics
///
/// Panics if the `RecordBatch` contains no columns.
///
/// # Example
///
/// ```
/// # use std::sync::Arc;
/// # use arrow2::array::PrimitiveArray;
/// # use arrow2::datatypes::{Schema, Field, DataType};
/// # use arrow2::record_batch::RecordBatch;
/// # fn main() -> arrow2::error::Result<()> {
/// let id_array = PrimitiveArray::from_slice([1i32, 2, 3, 4, 5]);
/// let schema = Arc::new(Schema::new(vec![
/// Field::new("id", DataType::Int32, false)
/// ]));
///
/// let batch = RecordBatch::try_new(schema, vec![Arc::new(id_array)])?;
///
/// assert_eq!(batch.num_rows(), 5);
/// # Ok(())
/// # }
/// ```
pub fn num_rows(&self) -> usize {
self.columns[0].len()
}
/// Get a reference to a column's array by index.
///
/// # Panics
///
/// Panics if `index` is outside of `0..num_columns`.
pub fn column(&self, index: usize) -> &Arc<dyn Array> {
&self.columns[index]
}
/// Get a reference to all columns in the record batch.
pub fn columns(&self) -> &[Arc<dyn Array>] {
&self.columns[..]
}
/// Create a `RecordBatch` from an iterable list of pairs of the
/// form `(field_name, array)`, with the same requirements on
/// fields and arrays as [`RecordBatch::try_new`]. This method is
/// often used to create a single `RecordBatch` from arrays,
/// e.g. for testing.
///
/// The resulting schema is marked as nullable for each column if
/// the array for that column is has any nulls. To explicitly
/// specify nullibility, use [`RecordBatch::try_from_iter_with_nullable`]
///
/// Example:
/// ```
/// use std::sync::Arc;
/// use arrow2::array::*;
/// use arrow2::datatypes::DataType;
/// use arrow2::record_batch::RecordBatch;
///
/// let a: Arc<dyn Array> = Arc::new(Int32Array::from_slice(&[1, 2]));
/// let b: Arc<dyn Array> = Arc::new(Utf8Array::<i32>::from_slice(&["a", "b"]));
///
/// let record_batch = RecordBatch::try_from_iter(vec![
/// ("a", a),
/// ("b", b),
/// ]);
/// ```
pub fn try_from_iter<I, F>(value: I) -> Result<Self>
where
I: IntoIterator<Item = (F, Arc<dyn Array>)>,
F: AsRef<str>,
{
// TODO: implement `TryFrom` trait, once
// https://github.com/rust-lang/rust/issues/50133 is no longer an
// issue
let iter = value.into_iter().map(|(field_name, array)| {
let nullable = array.null_count() > 0;
(field_name, array, nullable)
});
Self::try_from_iter_with_nullable(iter)
}
/// Create a `RecordBatch` from an iterable list of tuples of the
/// form `(field_name, array, nullable)`, with the same requirements on
/// fields and arrays as [`RecordBatch::try_new`]. This method is often
/// used to create a single `RecordBatch` from arrays, e.g. for
/// testing.
///
/// Example:
/// ```
/// use std::sync::Arc;
/// use arrow2::array::*;
/// use arrow2::datatypes::DataType;
/// use arrow2::record_batch::RecordBatch;
///
/// let a: Arc<dyn Array> = Arc::new(Int32Array::from_slice(&[1, 2]));
/// let b: Arc<dyn Array> = Arc::new(Utf8Array::<i32>::from_slice(&["a", "b"]));
///
/// // Note neither `a` nor `b` has any actual nulls, but we mark
/// // b an nullable
/// let record_batch = RecordBatch::try_from_iter_with_nullable(vec![
/// ("a", a, false),
/// ("b", b, true),
/// ]);
/// ```
pub fn try_from_iter_with_nullable<I, F>(value: I) -> Result<Self>
where
I: IntoIterator<Item = (F, Arc<dyn Array>, bool)>,
F: AsRef<str>,
{
// TODO: implement `TryFrom` trait, once
// https://github.com/rust-lang/rust/issues/50133 is no longer an
// issue
let (fields, columns) = value
.into_iter()
.map(|(field_name, array, nullable)| {
let field_name = field_name.as_ref();
let field = Field::new(field_name, array.data_type().clone(), nullable);
(field, array)
})
.unzip();
let schema = Arc::new(Schema::new(fields));
RecordBatch::try_new(schema, columns)
}
}
/// Options that control the behaviour used when creating a [`RecordBatch`].
#[derive(Debug)]
pub struct RecordBatchOptions {
/// Match field names of structs and lists. If set to `true`, the names must match.
pub match_field_names: bool,
}
impl Default for RecordBatchOptions {
fn default() -> Self {
Self {
match_field_names: true,
}
}
}
impl From<StructArray> for RecordBatch {
/// # Panics iff the null count of the array is not null.
fn from(array: StructArray) -> Self {
assert!(array.null_count() == 0);
let (fields, values, _) = array.into_data();
RecordBatch {
schema: Arc::new(Schema::new(fields)),
columns: values,
}
}
}
impl From<RecordBatch> for StructArray {
fn from(batch: RecordBatch) -> Self {
let (fields, values) = batch
.schema
.fields
.iter()
.zip(batch.columns.iter())
.map(|t| (t.0.clone(), t.1.clone()))
.unzip();
StructArray::from_data(DataType::Struct(fields), values, None)
}
}
/// Trait for types that can read `RecordBatch`'s.
pub trait RecordBatchReader: Iterator<Item = Result<RecordBatch>> {
/// Returns the schema of this `RecordBatchReader`.
///
/// Implementation of this trait should guarantee that all `RecordBatch`'s returned by this
/// reader should have the same schema as returned from this method.
fn schema(&self) -> &Schema;
/// Reads the next `RecordBatch`.
#[deprecated(
since = "2.0.0",
note = "This method is deprecated in favour of `next` from the trait Iterator."
)]
fn next_batch(&mut self) -> Result<Option<RecordBatch>> {
self.next().transpose()
}
}