Expand description
The central type in Apache Arrow are arrays, which are a known-length sequence of values
all having the same type. This module provides concrete implementations of each type, as
well as an Array
trait that can be used for type-erasure.
Downcasting an Array
Arrays are often passed around as a dynamically typed &dyn Array
or ArrayRef
.
For example, RecordBatch
stores columns as ArrayRef
.
Whilst these arrays can be passed directly to the
compute
, csv
,
json
, etc… APIs, it is often the case that you
wish to interact with the data directly. This requires downcasting
to the concrete type of the array:
fn sum_int32(array: &dyn Array) -> i32 {
let integers: &Int32Array = array.as_any().downcast_ref().unwrap();
integers.iter().map(|val| val.unwrap_or_default()).sum()
}
// Note: the values for positions corresponding to nulls will be arbitrary
fn as_f32_slice(array: &dyn Array) -> &[f32] {
array.as_any().downcast_ref::<Float32Array>().unwrap().values()
}
Additionally, there are convenient functions to do this casting
such as as_primitive_array<T>
and as_string_array
:
fn as_f32_slice(array: &dyn Array) -> &[f32] {
// use as_primtive_array
as_primitive_array::<Float32Type>(array).values()
}
Building an Array
Most Array
implementations can be constructed directly from iterators or Vec
Int32Array::from(vec![1, 2]);
Int32Array::from(vec![Some(1), None]);
Int32Array::from_iter([1, 2, 3, 4]);
Int32Array::from_iter([Some(1), Some(2), None, Some(4)]);
StringArray::from(vec!["foo", "bar"]);
StringArray::from(vec![Some("foo"), None]);
StringArray::from_iter([Some("foo"), None]);
StringArray::from_iter_values(["foo", "bar"]);
ListArray::from_iter_primitive::<Int32Type, _, _>([
Some(vec![Some(1), None, Some(3)]),
None,
Some(vec![])
]);
Additionally ArrayBuilder
implementations can be
used to construct arrays with a push-based interface
// Create a new builder with a capacity of 100
let mut builder = Int16Array::builder(100);
// Append a single primitive value
builder.append_value(1);
// Append a null value
builder.append_null();
// Append a slice of primitive values
builder.append_slice(&[2, 3, 4]);
// Build the array
let array = builder.finish();
assert_eq!(
5,
array.len(),
"The array has 5 values, counting the null value"
);
assert_eq!(2, array.value(2), "Get the value with index 2");
assert_eq!(
&array.values()[3..5],
&[3, 4],
"Get slice of len 2 starting at idx 3"
)
Zero-Copy Slicing
Given an Array
of arbitrary length, it is possible to create an owned slice of this
data. Internally this just increments some ref-counts, and so is incredibly cheap
let array = Arc::new(Int32Array::from_iter([1, 2, 3])) as ArrayRef;
// Slice with offset 1 and length 2
let sliced = array.slice(1, 2);
let ints = sliced.as_any().downcast_ref::<Int32Array>().unwrap();
assert_eq!(ints.values(), &[2, 3]);
Internal Representation
Internally, arrays are represented by one or several Buffer
, the number and meaning of
which depend on the array’s data type, as documented in the Arrow specification.
For example, the type Int16Array
represents an array of 16-bit integers and consists of:
Similarly, the type StringArray
represents an array of UTF-8 strings and consists of:
Structs
Array
.ArrayData
typeArrayAccessor
Buffer
object.Decimal128Array
Decimal256Array
Array
for fixed width decimal numbersFixedSizeListArray
BinaryArray
and LargeBinaryArray
for storing
binary data.GenericListArray
GenericStringArray
DictionaryArray
. For example to map a set of byte indices
to f32 values. Note that the use of a HashMap
here will not scale to very large
arrays or result in an ordered dictionary.DictionaryArray
that stores Strings. For example to map a set of byte indices
to String values. Note that the use of a HashMap
here will not scale to very large
arrays or result in an ordered dictionary.DictionaryArray
that implements ArrayAccessor
allowing fast access to its elementsUnionArray
.Enums
Traits
Array
Functions
data
.
Returns a reference-counted Array
instance.capacity
that corresponds to the datatype DataType
This function is useful to construct arrays from an arbitrary vectors with known/expected
schema.data_type
of length length
filled
entirely of NULL
valuesType Definitions
Array
.Decimal128Array
stores fixed width decimal numbers,
with a fixed precision and scale.Decimal256Array
stores fixed width decimal numbers,
with a fixed precision and scalecollect
collect
collect
collect
collect
collect
collect
TimestampMicrosecondType.
See examples for TimestampSecondArray.
TimestampMillisecondType.
See examples for TimestampSecondArray.
TimestampNanosecondType.
See examples for TimestampSecondArray.
Timestamp
.collect
collect
collect
collect