arrow_array/array/mod.rs
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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
//! The concrete array definitions
mod binary_array;
use crate::types::*;
use arrow_buffer::{ArrowNativeType, NullBuffer, OffsetBuffer, ScalarBuffer};
use arrow_data::ArrayData;
use arrow_schema::{DataType, IntervalUnit, TimeUnit};
use std::any::Any;
use std::sync::Arc;
pub use binary_array::*;
mod boolean_array;
pub use boolean_array::*;
mod byte_array;
pub use byte_array::*;
mod dictionary_array;
pub use dictionary_array::*;
mod fixed_size_binary_array;
pub use fixed_size_binary_array::*;
mod fixed_size_list_array;
pub use fixed_size_list_array::*;
mod list_array;
pub use list_array::*;
mod map_array;
pub use map_array::*;
mod null_array;
pub use null_array::*;
mod primitive_array;
pub use primitive_array::*;
mod string_array;
pub use string_array::*;
mod struct_array;
pub use struct_array::*;
mod union_array;
pub use union_array::*;
mod run_array;
pub use run_array::*;
mod byte_view_array;
pub use byte_view_array::*;
mod list_view_array;
pub use list_view_array::*;
use crate::iterator::ArrayIter;
/// An array in the [arrow columnar format](https://arrow.apache.org/docs/format/Columnar.html)
pub trait Array: std::fmt::Debug + Send + Sync {
/// Returns the array as [`Any`] so that it can be
/// downcasted to a specific implementation.
///
/// # Example:
///
/// ```
/// # use std::sync::Arc;
/// # use arrow_array::{Int32Array, RecordBatch};
/// # use arrow_schema::{Schema, Field, DataType, ArrowError};
///
/// let id = Int32Array::from(vec![1, 2, 3, 4, 5]);
/// let batch = RecordBatch::try_new(
/// Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)])),
/// vec![Arc::new(id)]
/// ).unwrap();
///
/// let int32array = batch
/// .column(0)
/// .as_any()
/// .downcast_ref::<Int32Array>()
/// .expect("Failed to downcast");
/// ```
fn as_any(&self) -> &dyn Any;
/// Returns the underlying data of this array
fn to_data(&self) -> ArrayData;
/// Returns the underlying data of this array
///
/// Unlike [`Array::to_data`] this consumes self, allowing it avoid unnecessary clones
fn into_data(self) -> ArrayData;
/// Returns a reference to the [`DataType`] of this array.
///
/// # Example:
///
/// ```
/// use arrow_schema::DataType;
/// use arrow_array::{Array, Int32Array};
///
/// let array = Int32Array::from(vec![1, 2, 3, 4, 5]);
///
/// assert_eq!(*array.data_type(), DataType::Int32);
/// ```
fn data_type(&self) -> &DataType;
/// Returns a zero-copy slice of this array with the indicated offset and length.
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array};
///
/// let array = Int32Array::from(vec![1, 2, 3, 4, 5]);
/// // Make slice over the values [2, 3, 4]
/// let array_slice = array.slice(1, 3);
///
/// assert_eq!(&array_slice, &Int32Array::from(vec![2, 3, 4]));
/// ```
fn slice(&self, offset: usize, length: usize) -> ArrayRef;
/// Returns the length (i.e., number of elements) of this array.
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array};
///
/// let array = Int32Array::from(vec![1, 2, 3, 4, 5]);
///
/// assert_eq!(array.len(), 5);
/// ```
fn len(&self) -> usize;
/// Returns whether this array is empty.
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array};
///
/// let array = Int32Array::from(vec![1, 2, 3, 4, 5]);
///
/// assert_eq!(array.is_empty(), false);
/// ```
fn is_empty(&self) -> bool;
/// Shrinks the capacity of any exclusively owned buffer as much as possible
///
/// Shared or externally allocated buffers will be ignored, and
/// any buffer offsets will be preserved.
fn shrink_to_fit(&mut self) {}
/// Returns the offset into the underlying data used by this array(-slice).
/// Note that the underlying data can be shared by many arrays.
/// This defaults to `0`.
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, BooleanArray};
///
/// let array = BooleanArray::from(vec![false, false, true, true]);
/// let array_slice = array.slice(1, 3);
///
/// assert_eq!(array.offset(), 0);
/// assert_eq!(array_slice.offset(), 1);
/// ```
fn offset(&self) -> usize;
/// Returns the null buffer of this array if any.
///
/// The null buffer contains the "physical" nulls of an array, that is how
/// the nulls are represented in the underlying arrow format.
///
/// The physical representation is efficient, but is sometimes non intuitive
/// for certain array types such as those with nullable child arrays like
/// [`DictionaryArray::values`], [`RunArray::values`] or [`UnionArray`], or without a
/// null buffer, such as [`NullArray`].
///
/// To determine if each element of such an array is "logically" null,
/// use the slower [`Array::logical_nulls`] to obtain a computed mask.
fn nulls(&self) -> Option<&NullBuffer>;
/// Returns a potentially computed [`NullBuffer`] that represents the logical
/// null values of this array, if any.
///
/// Logical nulls represent the values that are null in the array,
/// regardless of the underlying physical arrow representation.
///
/// For most array types, this is equivalent to the "physical" nulls
/// returned by [`Array::nulls`]. It is different for the following cases, because which
/// elements are null is not encoded in a single null buffer:
///
/// * [`DictionaryArray`] where [`DictionaryArray::values`] contains nulls
/// * [`RunArray`] where [`RunArray::values`] contains nulls
/// * [`NullArray`] where all indices are nulls
/// * [`UnionArray`] where the selected values contains nulls
///
/// In these cases a logical [`NullBuffer`] will be computed, encoding the
/// logical nullability of these arrays, beyond what is encoded in
/// [`Array::nulls`]
fn logical_nulls(&self) -> Option<NullBuffer> {
self.nulls().cloned()
}
/// Returns whether the element at `index` is null according to [`Array::nulls`]
///
/// Note: For performance reasons, this method returns nullability solely as determined by the
/// null buffer. This difference can lead to surprising results, for example, [`NullArray::is_null`] always
/// returns `false` as the array lacks a null buffer. Similarly [`DictionaryArray`], [`RunArray`] and [`UnionArray`] may
/// encode nullability in their children. See [`Self::logical_nulls`] for more information.
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array, NullArray};
///
/// let array = Int32Array::from(vec![Some(1), None]);
/// assert_eq!(array.is_null(0), false);
/// assert_eq!(array.is_null(1), true);
///
/// // NullArrays do not have a null buffer, and therefore always
/// // return false for is_null.
/// let array = NullArray::new(1);
/// assert_eq!(array.is_null(0), false);
/// ```
fn is_null(&self, index: usize) -> bool {
self.nulls().map(|n| n.is_null(index)).unwrap_or_default()
}
/// Returns whether the element at `index` is *not* null, the
/// opposite of [`Self::is_null`].
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array};
///
/// let array = Int32Array::from(vec![Some(1), None]);
///
/// assert_eq!(array.is_valid(0), true);
/// assert_eq!(array.is_valid(1), false);
/// ```
fn is_valid(&self, index: usize) -> bool {
!self.is_null(index)
}
/// Returns the total number of physical null values in this array.
///
/// Note: this method returns the physical null count, i.e. that encoded in [`Array::nulls`],
/// see [`Array::logical_nulls`] for logical nullability
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array};
///
/// // Construct an array with values [1, NULL, NULL]
/// let array = Int32Array::from(vec![Some(1), None, None]);
///
/// assert_eq!(array.null_count(), 2);
/// ```
fn null_count(&self) -> usize {
self.nulls().map(|n| n.null_count()).unwrap_or_default()
}
/// Returns the total number of logical null values in this array.
///
/// Note: this method returns the logical null count, i.e. that encoded in
/// [`Array::logical_nulls`]. In general this is equivalent to [`Array::null_count`] but may differ in the
/// presence of logical nullability, see [`Array::nulls`] and [`Array::logical_nulls`].
///
/// # Example:
///
/// ```
/// use arrow_array::{Array, Int32Array};
///
/// // Construct an array with values [1, NULL, NULL]
/// let array = Int32Array::from(vec![Some(1), None, None]);
///
/// assert_eq!(array.logical_null_count(), 2);
/// ```
fn logical_null_count(&self) -> usize {
self.logical_nulls()
.map(|n| n.null_count())
.unwrap_or_default()
}
/// Returns `false` if the array is guaranteed to not contain any logical nulls
///
/// This is generally equivalent to `Array::logical_null_count() != 0` unless determining
/// the logical nulls is expensive, in which case this method can return true even for an
/// array without nulls.
///
/// This is also generally equivalent to `Array::null_count() != 0` but may differ in the
/// presence of logical nullability, see [`Array::logical_null_count`] and [`Array::null_count`].
///
/// Implementations will return `true` unless they can cheaply prove no logical nulls
/// are present. For example a [`DictionaryArray`] with nullable values will still return true,
/// even if the nulls present in [`DictionaryArray::values`] are not referenced by any key,
/// and therefore would not appear in [`Array::logical_nulls`].
fn is_nullable(&self) -> bool {
self.logical_null_count() != 0
}
/// Returns the total number of bytes of memory pointed to by this array.
/// The buffers store bytes in the Arrow memory format, and include the data as well as the validity map.
/// Note that this does not always correspond to the exact memory usage of an array,
/// since multiple arrays can share the same buffers or slices thereof.
fn get_buffer_memory_size(&self) -> usize;
/// Returns the total number of bytes of memory occupied physically by this array.
/// This value will always be greater than returned by `get_buffer_memory_size()` and
/// includes the overhead of the data structures that contain the pointers to the various buffers.
fn get_array_memory_size(&self) -> usize;
}
/// A reference-counted reference to a generic `Array`
pub type ArrayRef = Arc<dyn Array>;
/// Ergonomics: Allow use of an ArrayRef as an `&dyn Array`
impl Array for ArrayRef {
fn as_any(&self) -> &dyn Any {
self.as_ref().as_any()
}
fn to_data(&self) -> ArrayData {
self.as_ref().to_data()
}
fn into_data(self) -> ArrayData {
self.to_data()
}
fn data_type(&self) -> &DataType {
self.as_ref().data_type()
}
fn slice(&self, offset: usize, length: usize) -> ArrayRef {
self.as_ref().slice(offset, length)
}
fn len(&self) -> usize {
self.as_ref().len()
}
fn is_empty(&self) -> bool {
self.as_ref().is_empty()
}
/// For shared buffers, this is a no-op.
fn shrink_to_fit(&mut self) {
if let Some(slf) = Arc::get_mut(self) {
slf.shrink_to_fit();
} else {
// We ignore shared buffers.
}
}
fn offset(&self) -> usize {
self.as_ref().offset()
}
fn nulls(&self) -> Option<&NullBuffer> {
self.as_ref().nulls()
}
fn logical_nulls(&self) -> Option<NullBuffer> {
self.as_ref().logical_nulls()
}
fn is_null(&self, index: usize) -> bool {
self.as_ref().is_null(index)
}
fn is_valid(&self, index: usize) -> bool {
self.as_ref().is_valid(index)
}
fn null_count(&self) -> usize {
self.as_ref().null_count()
}
fn logical_null_count(&self) -> usize {
self.as_ref().logical_null_count()
}
fn is_nullable(&self) -> bool {
self.as_ref().is_nullable()
}
fn get_buffer_memory_size(&self) -> usize {
self.as_ref().get_buffer_memory_size()
}
fn get_array_memory_size(&self) -> usize {
self.as_ref().get_array_memory_size()
}
}
impl<T: Array> Array for &T {
fn as_any(&self) -> &dyn Any {
T::as_any(self)
}
fn to_data(&self) -> ArrayData {
T::to_data(self)
}
fn into_data(self) -> ArrayData {
self.to_data()
}
fn data_type(&self) -> &DataType {
T::data_type(self)
}
fn slice(&self, offset: usize, length: usize) -> ArrayRef {
T::slice(self, offset, length)
}
fn len(&self) -> usize {
T::len(self)
}
fn is_empty(&self) -> bool {
T::is_empty(self)
}
fn offset(&self) -> usize {
T::offset(self)
}
fn nulls(&self) -> Option<&NullBuffer> {
T::nulls(self)
}
fn logical_nulls(&self) -> Option<NullBuffer> {
T::logical_nulls(self)
}
fn is_null(&self, index: usize) -> bool {
T::is_null(self, index)
}
fn is_valid(&self, index: usize) -> bool {
T::is_valid(self, index)
}
fn null_count(&self) -> usize {
T::null_count(self)
}
fn logical_null_count(&self) -> usize {
T::logical_null_count(self)
}
fn is_nullable(&self) -> bool {
T::is_nullable(self)
}
fn get_buffer_memory_size(&self) -> usize {
T::get_buffer_memory_size(self)
}
fn get_array_memory_size(&self) -> usize {
T::get_array_memory_size(self)
}
}
/// A generic trait for accessing the values of an [`Array`]
///
/// This trait helps write specialized implementations of algorithms for
/// different array types. Specialized implementations allow the compiler
/// to optimize the code for the specific array type, which can lead to
/// significant performance improvements.
///
/// # Example
/// For example, to write three different implementations of a string length function
/// for [`StringArray`], [`LargeStringArray`], and [`StringViewArray`], you can write
///
/// ```
/// # use std::sync::Arc;
/// # use arrow_array::{ArrayAccessor, ArrayRef, ArrowPrimitiveType, OffsetSizeTrait, PrimitiveArray};
/// # use arrow_buffer::ArrowNativeType;
/// # use arrow_array::cast::AsArray;
/// # use arrow_array::iterator::ArrayIter;
/// # use arrow_array::types::{Int32Type, Int64Type};
/// # use arrow_schema::{ArrowError, DataType};
/// /// This function takes a dynamically typed `ArrayRef` and calls
/// /// calls one of three specialized implementations
/// fn character_length(arg: ArrayRef) -> Result<ArrayRef, ArrowError> {
/// match arg.data_type() {
/// DataType::Utf8 => {
/// // downcast the ArrayRef to a StringArray and call the specialized implementation
/// let string_array = arg.as_string::<i32>();
/// character_length_general::<Int32Type, _>(string_array)
/// }
/// DataType::LargeUtf8 => {
/// character_length_general::<Int64Type, _>(arg.as_string::<i64>())
/// }
/// DataType::Utf8View => {
/// character_length_general::<Int32Type, _>(arg.as_string_view())
/// }
/// _ => Err(ArrowError::InvalidArgumentError("Unsupported data type".to_string())),
/// }
/// }
///
/// /// A generic implementation of the character_length function
/// /// This function uses the `ArrayAccessor` trait to access the values of the array
/// /// so the compiler can generated specialized implementations for different array types
/// ///
/// /// Returns a new array with the length of each string in the input array
/// /// * Int32Array for Utf8 and Utf8View arrays (lengths are 32-bit integers)
/// /// * Int64Array for LargeUtf8 arrays (lengths are 64-bit integers)
/// ///
/// /// This is generic on the type of the primitive array (different string arrays have
/// /// different lengths) and the type of the array accessor (different string arrays
/// /// have different ways to access the values)
/// fn character_length_general<'a, T: ArrowPrimitiveType, V: ArrayAccessor<Item = &'a str>>(
/// array: V,
/// ) -> Result<ArrayRef, ArrowError>
/// where
/// T::Native: OffsetSizeTrait,
/// {
/// let iter = ArrayIter::new(array);
/// // Create a Int32Array / Int64Array with the length of each string
/// let result = iter
/// .map(|string| {
/// string.map(|string: &str| {
/// T::Native::from_usize(string.chars().count())
/// .expect("should not fail as string.chars will always return integer")
/// })
/// })
/// .collect::<PrimitiveArray<T>>();
///
/// /// Return the result as a new ArrayRef (dynamically typed)
/// Ok(Arc::new(result) as ArrayRef)
/// }
/// ```
///
/// # Validity
///
/// An [`ArrayAccessor`] must always return a well-defined value for an index
/// that is within the bounds `0..Array::len`, including for null indexes where
/// [`Array::is_null`] is true.
///
/// The value at null indexes is unspecified, and implementations must not rely
/// on a specific value such as [`Default::default`] being returned, however, it
/// must not be undefined
pub trait ArrayAccessor: Array {
/// The Arrow type of the element being accessed.
type Item: Send + Sync;
/// Returns the element at index `i`
/// # Panics
/// Panics if the value is outside the bounds of the array
fn value(&self, index: usize) -> Self::Item;
/// Returns the element at index `i`
/// # Safety
/// Caller is responsible for ensuring that the index is within the bounds of the array
unsafe fn value_unchecked(&self, index: usize) -> Self::Item;
}
/// A trait for Arrow String Arrays, currently three types are supported:
/// - `StringArray`
/// - `LargeStringArray`
/// - `StringViewArray`
///
/// This trait helps to abstract over the different types of string arrays
/// so that we don't need to duplicate the implementation for each type.
pub trait StringArrayType<'a>: ArrayAccessor<Item = &'a str> + Sized {
/// Returns true if all data within this string array is ASCII
fn is_ascii(&self) -> bool;
/// Constructs a new iterator
fn iter(&self) -> ArrayIter<Self>;
}
impl<'a, O: OffsetSizeTrait> StringArrayType<'a> for &'a GenericStringArray<O> {
fn is_ascii(&self) -> bool {
GenericStringArray::<O>::is_ascii(self)
}
fn iter(&self) -> ArrayIter<Self> {
GenericStringArray::<O>::iter(self)
}
}
impl<'a> StringArrayType<'a> for &'a StringViewArray {
fn is_ascii(&self) -> bool {
StringViewArray::is_ascii(self)
}
fn iter(&self) -> ArrayIter<Self> {
StringViewArray::iter(self)
}
}
impl PartialEq for dyn Array + '_ {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<T: Array> PartialEq<T> for dyn Array + '_ {
fn eq(&self, other: &T) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl PartialEq for NullArray {
fn eq(&self, other: &NullArray) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<T: ArrowPrimitiveType> PartialEq for PrimitiveArray<T> {
fn eq(&self, other: &PrimitiveArray<T>) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<K: ArrowDictionaryKeyType> PartialEq for DictionaryArray<K> {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl PartialEq for BooleanArray {
fn eq(&self, other: &BooleanArray) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<OffsetSize: OffsetSizeTrait> PartialEq for GenericStringArray<OffsetSize> {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<OffsetSize: OffsetSizeTrait> PartialEq for GenericBinaryArray<OffsetSize> {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl PartialEq for FixedSizeBinaryArray {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<OffsetSize: OffsetSizeTrait> PartialEq for GenericListArray<OffsetSize> {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<OffsetSize: OffsetSizeTrait> PartialEq for GenericListViewArray<OffsetSize> {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl PartialEq for MapArray {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl PartialEq for FixedSizeListArray {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl PartialEq for StructArray {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
impl<T: ByteViewType + ?Sized> PartialEq for GenericByteViewArray<T> {
fn eq(&self, other: &Self) -> bool {
self.to_data().eq(&other.to_data())
}
}
/// Constructs an array using the input `data`.
/// Returns a reference-counted `Array` instance.
pub fn make_array(data: ArrayData) -> ArrayRef {
match data.data_type() {
DataType::Boolean => Arc::new(BooleanArray::from(data)) as ArrayRef,
DataType::Int8 => Arc::new(Int8Array::from(data)) as ArrayRef,
DataType::Int16 => Arc::new(Int16Array::from(data)) as ArrayRef,
DataType::Int32 => Arc::new(Int32Array::from(data)) as ArrayRef,
DataType::Int64 => Arc::new(Int64Array::from(data)) as ArrayRef,
DataType::UInt8 => Arc::new(UInt8Array::from(data)) as ArrayRef,
DataType::UInt16 => Arc::new(UInt16Array::from(data)) as ArrayRef,
DataType::UInt32 => Arc::new(UInt32Array::from(data)) as ArrayRef,
DataType::UInt64 => Arc::new(UInt64Array::from(data)) as ArrayRef,
DataType::Float16 => Arc::new(Float16Array::from(data)) as ArrayRef,
DataType::Float32 => Arc::new(Float32Array::from(data)) as ArrayRef,
DataType::Float64 => Arc::new(Float64Array::from(data)) as ArrayRef,
DataType::Date32 => Arc::new(Date32Array::from(data)) as ArrayRef,
DataType::Date64 => Arc::new(Date64Array::from(data)) as ArrayRef,
DataType::Time32(TimeUnit::Second) => Arc::new(Time32SecondArray::from(data)) as ArrayRef,
DataType::Time32(TimeUnit::Millisecond) => {
Arc::new(Time32MillisecondArray::from(data)) as ArrayRef
}
DataType::Time64(TimeUnit::Microsecond) => {
Arc::new(Time64MicrosecondArray::from(data)) as ArrayRef
}
DataType::Time64(TimeUnit::Nanosecond) => {
Arc::new(Time64NanosecondArray::from(data)) as ArrayRef
}
DataType::Timestamp(TimeUnit::Second, _) => {
Arc::new(TimestampSecondArray::from(data)) as ArrayRef
}
DataType::Timestamp(TimeUnit::Millisecond, _) => {
Arc::new(TimestampMillisecondArray::from(data)) as ArrayRef
}
DataType::Timestamp(TimeUnit::Microsecond, _) => {
Arc::new(TimestampMicrosecondArray::from(data)) as ArrayRef
}
DataType::Timestamp(TimeUnit::Nanosecond, _) => {
Arc::new(TimestampNanosecondArray::from(data)) as ArrayRef
}
DataType::Interval(IntervalUnit::YearMonth) => {
Arc::new(IntervalYearMonthArray::from(data)) as ArrayRef
}
DataType::Interval(IntervalUnit::DayTime) => {
Arc::new(IntervalDayTimeArray::from(data)) as ArrayRef
}
DataType::Interval(IntervalUnit::MonthDayNano) => {
Arc::new(IntervalMonthDayNanoArray::from(data)) as ArrayRef
}
DataType::Duration(TimeUnit::Second) => {
Arc::new(DurationSecondArray::from(data)) as ArrayRef
}
DataType::Duration(TimeUnit::Millisecond) => {
Arc::new(DurationMillisecondArray::from(data)) as ArrayRef
}
DataType::Duration(TimeUnit::Microsecond) => {
Arc::new(DurationMicrosecondArray::from(data)) as ArrayRef
}
DataType::Duration(TimeUnit::Nanosecond) => {
Arc::new(DurationNanosecondArray::from(data)) as ArrayRef
}
DataType::Binary => Arc::new(BinaryArray::from(data)) as ArrayRef,
DataType::LargeBinary => Arc::new(LargeBinaryArray::from(data)) as ArrayRef,
DataType::FixedSizeBinary(_) => Arc::new(FixedSizeBinaryArray::from(data)) as ArrayRef,
DataType::BinaryView => Arc::new(BinaryViewArray::from(data)) as ArrayRef,
DataType::Utf8 => Arc::new(StringArray::from(data)) as ArrayRef,
DataType::LargeUtf8 => Arc::new(LargeStringArray::from(data)) as ArrayRef,
DataType::Utf8View => Arc::new(StringViewArray::from(data)) as ArrayRef,
DataType::List(_) => Arc::new(ListArray::from(data)) as ArrayRef,
DataType::LargeList(_) => Arc::new(LargeListArray::from(data)) as ArrayRef,
DataType::ListView(_) => Arc::new(ListViewArray::from(data)) as ArrayRef,
DataType::LargeListView(_) => Arc::new(LargeListViewArray::from(data)) as ArrayRef,
DataType::Struct(_) => Arc::new(StructArray::from(data)) as ArrayRef,
DataType::Map(_, _) => Arc::new(MapArray::from(data)) as ArrayRef,
DataType::Union(_, _) => Arc::new(UnionArray::from(data)) as ArrayRef,
DataType::FixedSizeList(_, _) => Arc::new(FixedSizeListArray::from(data)) as ArrayRef,
DataType::Dictionary(ref key_type, _) => match key_type.as_ref() {
DataType::Int8 => Arc::new(DictionaryArray::<Int8Type>::from(data)) as ArrayRef,
DataType::Int16 => Arc::new(DictionaryArray::<Int16Type>::from(data)) as ArrayRef,
DataType::Int32 => Arc::new(DictionaryArray::<Int32Type>::from(data)) as ArrayRef,
DataType::Int64 => Arc::new(DictionaryArray::<Int64Type>::from(data)) as ArrayRef,
DataType::UInt8 => Arc::new(DictionaryArray::<UInt8Type>::from(data)) as ArrayRef,
DataType::UInt16 => Arc::new(DictionaryArray::<UInt16Type>::from(data)) as ArrayRef,
DataType::UInt32 => Arc::new(DictionaryArray::<UInt32Type>::from(data)) as ArrayRef,
DataType::UInt64 => Arc::new(DictionaryArray::<UInt64Type>::from(data)) as ArrayRef,
dt => panic!("Unexpected dictionary key type {dt:?}"),
},
DataType::RunEndEncoded(ref run_ends_type, _) => match run_ends_type.data_type() {
DataType::Int16 => Arc::new(RunArray::<Int16Type>::from(data)) as ArrayRef,
DataType::Int32 => Arc::new(RunArray::<Int32Type>::from(data)) as ArrayRef,
DataType::Int64 => Arc::new(RunArray::<Int64Type>::from(data)) as ArrayRef,
dt => panic!("Unexpected data type for run_ends array {dt:?}"),
},
DataType::Null => Arc::new(NullArray::from(data)) as ArrayRef,
DataType::Decimal128(_, _) => Arc::new(Decimal128Array::from(data)) as ArrayRef,
DataType::Decimal256(_, _) => Arc::new(Decimal256Array::from(data)) as ArrayRef,
dt => panic!("Unexpected data type {dt:?}"),
}
}
/// Creates a new empty array
///
/// ```
/// use std::sync::Arc;
/// use arrow_schema::DataType;
/// use arrow_array::{ArrayRef, Int32Array, new_empty_array};
///
/// let empty_array = new_empty_array(&DataType::Int32);
/// let array: ArrayRef = Arc::new(Int32Array::from(vec![] as Vec<i32>));
///
/// assert_eq!(&array, &empty_array);
/// ```
pub fn new_empty_array(data_type: &DataType) -> ArrayRef {
let data = ArrayData::new_empty(data_type);
make_array(data)
}
/// Creates a new array of `data_type` of length `length` filled
/// entirely of `NULL` values
///
/// ```
/// use std::sync::Arc;
/// use arrow_schema::DataType;
/// use arrow_array::{ArrayRef, Int32Array, new_null_array};
///
/// let null_array = new_null_array(&DataType::Int32, 3);
/// let array: ArrayRef = Arc::new(Int32Array::from(vec![None, None, None]));
///
/// assert_eq!(&array, &null_array);
/// ```
pub fn new_null_array(data_type: &DataType, length: usize) -> ArrayRef {
make_array(ArrayData::new_null(data_type, length))
}
/// Helper function that gets offset from an [`ArrayData`]
///
/// # Safety
///
/// - ArrayData must contain a valid [`OffsetBuffer`] as its first buffer
unsafe fn get_offsets<O: ArrowNativeType>(data: &ArrayData) -> OffsetBuffer<O> {
match data.is_empty() && data.buffers()[0].is_empty() {
true => OffsetBuffer::new_empty(),
false => {
let buffer =
ScalarBuffer::new(data.buffers()[0].clone(), data.offset(), data.len() + 1);
// Safety:
// ArrayData is valid
unsafe { OffsetBuffer::new_unchecked(buffer) }
}
}
}
/// Helper function for printing potentially long arrays.
fn print_long_array<A, F>(array: &A, f: &mut std::fmt::Formatter, print_item: F) -> std::fmt::Result
where
A: Array,
F: Fn(&A, usize, &mut std::fmt::Formatter) -> std::fmt::Result,
{
let head = std::cmp::min(10, array.len());
for i in 0..head {
if array.is_null(i) {
writeln!(f, " null,")?;
} else {
write!(f, " ")?;
print_item(array, i, f)?;
writeln!(f, ",")?;
}
}
if array.len() > 10 {
if array.len() > 20 {
writeln!(f, " ...{} elements...,", array.len() - 20)?;
}
let tail = std::cmp::max(head, array.len() - 10);
for i in tail..array.len() {
if array.is_null(i) {
writeln!(f, " null,")?;
} else {
write!(f, " ")?;
print_item(array, i, f)?;
writeln!(f, ",")?;
}
}
}
Ok(())
}
#[cfg(test)]
mod tests {
use super::*;
use crate::cast::{as_union_array, downcast_array};
use crate::downcast_run_array;
use arrow_buffer::MutableBuffer;
use arrow_schema::{Field, Fields, UnionFields, UnionMode};
#[test]
fn test_empty_primitive() {
let array = new_empty_array(&DataType::Int32);
let a = array.as_any().downcast_ref::<Int32Array>().unwrap();
assert_eq!(a.len(), 0);
let expected: &[i32] = &[];
assert_eq!(a.values(), expected);
}
#[test]
fn test_empty_variable_sized() {
let array = new_empty_array(&DataType::Utf8);
let a = array.as_any().downcast_ref::<StringArray>().unwrap();
assert_eq!(a.len(), 0);
assert_eq!(a.value_offsets()[0], 0i32);
}
#[test]
fn test_empty_list_primitive() {
let data_type = DataType::List(Arc::new(Field::new_list_field(DataType::Int32, false)));
let array = new_empty_array(&data_type);
let a = array.as_any().downcast_ref::<ListArray>().unwrap();
assert_eq!(a.len(), 0);
assert_eq!(a.value_offsets()[0], 0i32);
}
#[test]
fn test_null_boolean() {
let array = new_null_array(&DataType::Boolean, 9);
let a = array.as_any().downcast_ref::<BooleanArray>().unwrap();
assert_eq!(a.len(), 9);
for i in 0..9 {
assert!(a.is_null(i));
}
}
#[test]
fn test_null_primitive() {
let array = new_null_array(&DataType::Int32, 9);
let a = array.as_any().downcast_ref::<Int32Array>().unwrap();
assert_eq!(a.len(), 9);
for i in 0..9 {
assert!(a.is_null(i));
}
}
#[test]
fn test_null_struct() {
// It is possible to create a null struct containing a non-nullable child
// see https://github.com/apache/arrow-rs/pull/3244 for details
let struct_type = DataType::Struct(vec![Field::new("data", DataType::Int64, false)].into());
let array = new_null_array(&struct_type, 9);
let a = array.as_any().downcast_ref::<StructArray>().unwrap();
assert_eq!(a.len(), 9);
assert_eq!(a.column(0).len(), 9);
for i in 0..9 {
assert!(a.is_null(i));
}
// Make sure we can slice the resulting array.
a.slice(0, 5);
}
#[test]
fn test_null_variable_sized() {
let array = new_null_array(&DataType::Utf8, 9);
let a = array.as_any().downcast_ref::<StringArray>().unwrap();
assert_eq!(a.len(), 9);
assert_eq!(a.value_offsets()[9], 0i32);
for i in 0..9 {
assert!(a.is_null(i));
}
}
#[test]
fn test_null_list_primitive() {
let data_type = DataType::List(Arc::new(Field::new_list_field(DataType::Int32, true)));
let array = new_null_array(&data_type, 9);
let a = array.as_any().downcast_ref::<ListArray>().unwrap();
assert_eq!(a.len(), 9);
assert_eq!(a.value_offsets()[9], 0i32);
for i in 0..9 {
assert!(a.is_null(i));
}
}
#[test]
fn test_null_map() {
let data_type = DataType::Map(
Arc::new(Field::new(
"entry",
DataType::Struct(Fields::from(vec![
Field::new("key", DataType::Utf8, false),
Field::new("value", DataType::Int32, true),
])),
false,
)),
false,
);
let array = new_null_array(&data_type, 9);
let a = array.as_any().downcast_ref::<MapArray>().unwrap();
assert_eq!(a.len(), 9);
assert_eq!(a.value_offsets()[9], 0i32);
for i in 0..9 {
assert!(a.is_null(i));
}
}
#[test]
fn test_null_dictionary() {
let values =
vec![None, None, None, None, None, None, None, None, None] as Vec<Option<&str>>;
let array: DictionaryArray<Int8Type> = values.into_iter().collect();
let array = Arc::new(array) as ArrayRef;
let null_array = new_null_array(array.data_type(), 9);
assert_eq!(&array, &null_array);
assert_eq!(
array.to_data().buffers()[0].len(),
null_array.to_data().buffers()[0].len()
);
}
#[test]
fn test_null_union() {
for mode in [UnionMode::Sparse, UnionMode::Dense] {
let data_type = DataType::Union(
UnionFields::new(
vec![2, 1],
vec![
Field::new("foo", DataType::Int32, true),
Field::new("bar", DataType::Int64, true),
],
),
mode,
);
let array = new_null_array(&data_type, 4);
let array = as_union_array(array.as_ref());
assert_eq!(array.len(), 4);
assert_eq!(array.null_count(), 0);
assert_eq!(array.logical_null_count(), 4);
for i in 0..4 {
let a = array.value(i);
assert_eq!(a.len(), 1);
assert_eq!(a.null_count(), 1);
assert_eq!(a.logical_null_count(), 1);
assert!(a.is_null(0))
}
array.to_data().validate_full().unwrap();
}
}
#[test]
#[allow(unused_parens)]
fn test_null_runs() {
for r in [DataType::Int16, DataType::Int32, DataType::Int64] {
let data_type = DataType::RunEndEncoded(
Arc::new(Field::new("run_ends", r, false)),
Arc::new(Field::new("values", DataType::Utf8, true)),
);
let array = new_null_array(&data_type, 4);
let array = array.as_ref();
downcast_run_array! {
array => {
assert_eq!(array.len(), 4);
assert_eq!(array.null_count(), 0);
assert_eq!(array.logical_null_count(), 4);
assert_eq!(array.values().len(), 1);
assert_eq!(array.values().null_count(), 1);
assert_eq!(array.run_ends().len(), 4);
assert_eq!(array.run_ends().values(), &[4]);
let idx = array.get_physical_indices(&[0, 1, 2, 3]).unwrap();
assert_eq!(idx, &[0,0,0,0]);
}
d => unreachable!("{d}")
}
}
}
#[test]
fn test_null_fixed_size_binary() {
for size in [1, 2, 7] {
let array = new_null_array(&DataType::FixedSizeBinary(size), 6);
let array = array
.as_ref()
.as_any()
.downcast_ref::<FixedSizeBinaryArray>()
.unwrap();
assert_eq!(array.len(), 6);
assert_eq!(array.null_count(), 6);
assert_eq!(array.logical_null_count(), 6);
array.iter().for_each(|x| assert!(x.is_none()));
}
}
#[test]
fn test_memory_size_null() {
let null_arr = NullArray::new(32);
assert_eq!(0, null_arr.get_buffer_memory_size());
assert_eq!(
std::mem::size_of::<usize>(),
null_arr.get_array_memory_size()
);
}
#[test]
fn test_memory_size_primitive() {
let arr = PrimitiveArray::<Int64Type>::from_iter_values(0..128);
let empty = PrimitiveArray::<Int64Type>::from(ArrayData::new_empty(arr.data_type()));
// subtract empty array to avoid magic numbers for the size of additional fields
assert_eq!(
arr.get_array_memory_size() - empty.get_array_memory_size(),
128 * std::mem::size_of::<i64>()
);
}
#[test]
fn test_memory_size_primitive_sliced() {
let arr = PrimitiveArray::<Int64Type>::from_iter_values(0..128);
let slice1 = arr.slice(0, 64);
let slice2 = arr.slice(64, 64);
// both slices report the full buffer memory usage, even though the buffers are shared
assert_eq!(slice1.get_array_memory_size(), arr.get_array_memory_size());
assert_eq!(slice2.get_array_memory_size(), arr.get_array_memory_size());
}
#[test]
fn test_memory_size_primitive_nullable() {
let arr: PrimitiveArray<Int64Type> = (0..128)
.map(|i| if i % 20 == 0 { Some(i) } else { None })
.collect();
let empty_with_bitmap = PrimitiveArray::<Int64Type>::from(
ArrayData::builder(arr.data_type().clone())
.add_buffer(MutableBuffer::new(0).into())
.null_bit_buffer(Some(MutableBuffer::new_null(0).into()))
.build()
.unwrap(),
);
// expected size is the size of the PrimitiveArray struct,
// which includes the optional validity buffer
// plus one buffer on the heap
assert_eq!(
std::mem::size_of::<PrimitiveArray<Int64Type>>(),
empty_with_bitmap.get_array_memory_size()
);
// subtract empty array to avoid magic numbers for the size of additional fields
// the size of the validity bitmap is rounded up to 64 bytes
assert_eq!(
arr.get_array_memory_size() - empty_with_bitmap.get_array_memory_size(),
128 * std::mem::size_of::<i64>() + 64
);
}
#[test]
fn test_memory_size_dictionary() {
let values = PrimitiveArray::<Int64Type>::from_iter_values(0..16);
let keys = PrimitiveArray::<Int16Type>::from_iter_values(
(0..256).map(|i| (i % values.len()) as i16),
);
let dict_data_type = DataType::Dictionary(
Box::new(keys.data_type().clone()),
Box::new(values.data_type().clone()),
);
let dict_data = keys
.into_data()
.into_builder()
.data_type(dict_data_type)
.child_data(vec![values.into_data()])
.build()
.unwrap();
let empty_data = ArrayData::new_empty(&DataType::Dictionary(
Box::new(DataType::Int16),
Box::new(DataType::Int64),
));
let arr = DictionaryArray::<Int16Type>::from(dict_data);
let empty = DictionaryArray::<Int16Type>::from(empty_data);
let expected_keys_size = 256 * std::mem::size_of::<i16>();
assert_eq!(
arr.keys().get_array_memory_size() - empty.keys().get_array_memory_size(),
expected_keys_size
);
let expected_values_size = 16 * std::mem::size_of::<i64>();
assert_eq!(
arr.values().get_array_memory_size() - empty.values().get_array_memory_size(),
expected_values_size
);
let expected_size = expected_keys_size + expected_values_size;
assert_eq!(
arr.get_array_memory_size() - empty.get_array_memory_size(),
expected_size
);
}
/// Test function that takes an &dyn Array
fn compute_my_thing(arr: &dyn Array) -> bool {
!arr.is_empty()
}
#[test]
fn test_array_ref_as_array() {
let arr: Int32Array = vec![1, 2, 3].into_iter().map(Some).collect();
// works well!
assert!(compute_my_thing(&arr));
// Should also work when wrapped as an ArrayRef
let arr: ArrayRef = Arc::new(arr);
assert!(compute_my_thing(&arr));
assert!(compute_my_thing(arr.as_ref()));
}
#[test]
fn test_downcast_array() {
let array: Int32Array = vec![1, 2, 3].into_iter().map(Some).collect();
let boxed: ArrayRef = Arc::new(array);
let array: Int32Array = downcast_array(&boxed);
let expected: Int32Array = vec![1, 2, 3].into_iter().map(Some).collect();
assert_eq!(array, expected);
}
}