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array_reader.rs
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array_reader.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.
use std::any::Any;
use std::cmp::{max, min};
use std::marker::PhantomData;
use std::mem::size_of;
use std::result::Result::Ok;
use std::sync::Arc;
use std::vec::Vec;
use arrow::array::{
new_empty_array, Array, ArrayData, ArrayDataBuilder, ArrayRef, BooleanArray,
BooleanBufferBuilder, DecimalArray, GenericListArray, Int16BufferBuilder, Int32Array,
Int64Array, MapArray, OffsetSizeTrait, PrimitiveArray, StructArray, UInt32Array,
};
use arrow::buffer::{Buffer, MutableBuffer};
use arrow::compute::take;
use arrow::datatypes::{
ArrowPrimitiveType, BooleanType as ArrowBooleanType, DataType as ArrowType,
Float32Type as ArrowFloat32Type, Float64Type as ArrowFloat64Type,
Int32Type as ArrowInt32Type, Int64Type as ArrowInt64Type, ToByteSlice,
UInt32Type as ArrowUInt32Type, UInt64Type as ArrowUInt64Type,
};
use arrow::util::bit_util;
use crate::arrow::converter::Converter;
use crate::arrow::record_reader::buffer::{ScalarValue, ValuesBuffer};
use crate::arrow::record_reader::{GenericRecordReader, RecordReader};
use crate::arrow::schema::parquet_to_arrow_field;
use crate::basic::Type as PhysicalType;
use crate::column::page::PageIterator;
use crate::column::reader::decoder::ColumnValueDecoder;
use crate::column::reader::ColumnReaderImpl;
use crate::data_type::DataType;
use crate::errors::{ParquetError, ParquetError::ArrowError, Result};
use crate::file::reader::{FilePageIterator, FileReader};
use crate::schema::types::{ColumnDescPtr, SchemaDescPtr};
mod builder;
mod byte_array;
mod byte_array_dictionary;
mod dictionary_buffer;
mod empty_array;
mod offset_buffer;
#[cfg(test)]
mod test_util;
pub use builder::build_array_reader;
pub use byte_array::make_byte_array_reader;
pub use byte_array_dictionary::make_byte_array_dictionary_reader;
/// Array reader reads parquet data into arrow array.
pub trait ArrayReader: Send {
fn as_any(&self) -> &dyn Any;
/// Returns the arrow type of this array reader.
fn get_data_type(&self) -> &ArrowType;
/// Reads at most `batch_size` records into an arrow array and return it.
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef>;
/// If this array has a non-zero definition level, i.e. has a nullable parent
/// array, returns the definition levels of data from the last call of `next_batch`
///
/// Otherwise returns None
///
/// This is used by parent [`ArrayReader`] to compute their null bitmaps
fn get_def_levels(&self) -> Option<&[i16]>;
/// If this array has a non-zero repetition level, i.e. has a repeated parent
/// array, returns the repetition levels of data from the last call of `next_batch`
///
/// Otherwise returns None
///
/// This is used by parent [`ArrayReader`] to compute their array offsets
fn get_rep_levels(&self) -> Option<&[i16]>;
}
/// A collection of row groups
pub trait RowGroupCollection {
/// Get schema of parquet file.
fn schema(&self) -> Result<SchemaDescPtr>;
/// Get the numer of rows in this collection
fn num_rows(&self) -> usize;
/// Returns an iterator over the column chunks for particular column
fn column_chunks(&self, i: usize) -> Result<Box<dyn PageIterator>>;
}
impl RowGroupCollection for Arc<dyn FileReader> {
fn schema(&self) -> Result<SchemaDescPtr> {
Ok(self.metadata().file_metadata().schema_descr_ptr())
}
fn num_rows(&self) -> usize {
self.metadata().file_metadata().num_rows() as usize
}
fn column_chunks(&self, column_index: usize) -> Result<Box<dyn PageIterator>> {
let iterator = FilePageIterator::new(column_index, Arc::clone(self))?;
Ok(Box::new(iterator))
}
}
/// Uses `record_reader` to read up to `batch_size` records from `pages`
///
/// Returns the number of records read, which can be less than batch_size if
/// pages is exhausted.
fn read_records<V, CV>(
record_reader: &mut GenericRecordReader<V, CV>,
pages: &mut dyn PageIterator,
batch_size: usize,
) -> Result<usize>
where
V: ValuesBuffer + Default,
CV: ColumnValueDecoder<Slice = V::Slice>,
{
let mut records_read = 0usize;
while records_read < batch_size {
let records_to_read = batch_size - records_read;
let records_read_once = record_reader.read_records(records_to_read)?;
records_read += records_read_once;
// Record reader exhausted
if records_read_once < records_to_read {
if let Some(page_reader) = pages.next() {
// Read from new page reader (i.e. column chunk)
record_reader.set_page_reader(page_reader?)?;
} else {
// Page reader also exhausted
break;
}
}
}
Ok(records_read)
}
/// A NullArrayReader reads Parquet columns stored as null int32s with an Arrow
/// NullArray type.
pub struct NullArrayReader<T>
where
T: DataType,
T::T: ScalarValue,
{
data_type: ArrowType,
pages: Box<dyn PageIterator>,
def_levels_buffer: Option<Buffer>,
rep_levels_buffer: Option<Buffer>,
column_desc: ColumnDescPtr,
record_reader: RecordReader<T>,
_type_marker: PhantomData<T>,
}
impl<T> NullArrayReader<T>
where
T: DataType,
T::T: ScalarValue,
{
/// Construct null array reader.
pub fn new(pages: Box<dyn PageIterator>, column_desc: ColumnDescPtr) -> Result<Self> {
let record_reader = RecordReader::<T>::new(column_desc.clone());
Ok(Self {
data_type: ArrowType::Null,
pages,
def_levels_buffer: None,
rep_levels_buffer: None,
column_desc,
record_reader,
_type_marker: PhantomData,
})
}
}
/// Implementation of primitive array reader.
impl<T> ArrayReader for NullArrayReader<T>
where
T: DataType,
T::T: ScalarValue,
{
fn as_any(&self) -> &dyn Any {
self
}
/// Returns data type of primitive array.
fn get_data_type(&self) -> &ArrowType {
&self.data_type
}
/// Reads at most `batch_size` records into array.
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef> {
read_records(&mut self.record_reader, self.pages.as_mut(), batch_size)?;
// convert to arrays
let array = arrow::array::NullArray::new(self.record_reader.num_values());
// save definition and repetition buffers
self.def_levels_buffer = self.record_reader.consume_def_levels()?;
self.rep_levels_buffer = self.record_reader.consume_rep_levels()?;
// Must consume bitmap buffer
self.record_reader.consume_bitmap_buffer()?;
self.record_reader.reset();
Ok(Arc::new(array))
}
fn get_def_levels(&self) -> Option<&[i16]> {
self.def_levels_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
fn get_rep_levels(&self) -> Option<&[i16]> {
self.rep_levels_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
}
/// Primitive array readers are leaves of array reader tree. They accept page iterator
/// and read them into primitive arrays.
pub struct PrimitiveArrayReader<T>
where
T: DataType,
T::T: ScalarValue,
{
data_type: ArrowType,
pages: Box<dyn PageIterator>,
def_levels_buffer: Option<Buffer>,
rep_levels_buffer: Option<Buffer>,
column_desc: ColumnDescPtr,
record_reader: RecordReader<T>,
}
impl<T> PrimitiveArrayReader<T>
where
T: DataType,
T::T: ScalarValue,
{
/// Construct primitive array reader.
pub fn new(
pages: Box<dyn PageIterator>,
column_desc: ColumnDescPtr,
arrow_type: Option<ArrowType>,
) -> Result<Self> {
Self::new_with_options(pages, column_desc, arrow_type, false)
}
/// Construct primitive array reader with ability to only compute null mask and not
/// buffer level data
pub fn new_with_options(
pages: Box<dyn PageIterator>,
column_desc: ColumnDescPtr,
arrow_type: Option<ArrowType>,
null_mask_only: bool,
) -> Result<Self> {
// Check if Arrow type is specified, else create it from Parquet type
let data_type = match arrow_type {
Some(t) => t,
None => parquet_to_arrow_field(column_desc.as_ref())?
.data_type()
.clone(),
};
let record_reader =
RecordReader::<T>::new_with_options(column_desc.clone(), null_mask_only);
Ok(Self {
data_type,
pages,
def_levels_buffer: None,
rep_levels_buffer: None,
column_desc,
record_reader,
})
}
}
/// Implementation of primitive array reader.
impl<T> ArrayReader for PrimitiveArrayReader<T>
where
T: DataType,
T::T: ScalarValue,
{
fn as_any(&self) -> &dyn Any {
self
}
/// Returns data type of primitive array.
fn get_data_type(&self) -> &ArrowType {
&self.data_type
}
/// Reads at most `batch_size` records into array.
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef> {
read_records(&mut self.record_reader, self.pages.as_mut(), batch_size)?;
let target_type = self.get_data_type().clone();
let arrow_data_type = match T::get_physical_type() {
PhysicalType::BOOLEAN => ArrowBooleanType::DATA_TYPE,
PhysicalType::INT32 => {
match target_type {
ArrowType::UInt32 => {
// follow C++ implementation and use overflow/reinterpret cast from i32 to u32 which will map
// `i32::MIN..0` to `(i32::MAX as u32)..u32::MAX`
ArrowUInt32Type::DATA_TYPE
}
_ => ArrowInt32Type::DATA_TYPE,
}
}
PhysicalType::INT64 => {
match target_type {
ArrowType::UInt64 => {
// follow C++ implementation and use overflow/reinterpret cast from i64 to u64 which will map
// `i64::MIN..0` to `(i64::MAX as u64)..u64::MAX`
ArrowUInt64Type::DATA_TYPE
}
_ => ArrowInt64Type::DATA_TYPE,
}
}
PhysicalType::FLOAT => ArrowFloat32Type::DATA_TYPE,
PhysicalType::DOUBLE => ArrowFloat64Type::DATA_TYPE,
PhysicalType::INT96
| PhysicalType::BYTE_ARRAY
| PhysicalType::FIXED_LEN_BYTE_ARRAY => {
unreachable!(
"PrimitiveArrayReaders don't support complex physical types"
);
}
};
// Convert to arrays by using the Parquet physical type.
// The physical types are then cast to Arrow types if necessary
let mut record_data = self.record_reader.consume_record_data()?;
if T::get_physical_type() == PhysicalType::BOOLEAN {
let mut boolean_buffer = BooleanBufferBuilder::new(record_data.len());
for e in record_data.as_slice() {
boolean_buffer.append(*e > 0);
}
record_data = boolean_buffer.finish();
}
let mut array_data = ArrayDataBuilder::new(arrow_data_type)
.len(self.record_reader.num_values())
.add_buffer(record_data);
if let Some(b) = self.record_reader.consume_bitmap_buffer()? {
array_data = array_data.null_bit_buffer(b);
}
let array_data = unsafe { array_data.build_unchecked() };
let array = match T::get_physical_type() {
PhysicalType::BOOLEAN => Arc::new(BooleanArray::from(array_data)) as ArrayRef,
PhysicalType::INT32 => {
Arc::new(PrimitiveArray::<ArrowInt32Type>::from(array_data)) as ArrayRef
}
PhysicalType::INT64 => {
Arc::new(PrimitiveArray::<ArrowInt64Type>::from(array_data)) as ArrayRef
}
PhysicalType::FLOAT => {
Arc::new(PrimitiveArray::<ArrowFloat32Type>::from(array_data)) as ArrayRef
}
PhysicalType::DOUBLE => {
Arc::new(PrimitiveArray::<ArrowFloat64Type>::from(array_data)) as ArrayRef
}
PhysicalType::INT96
| PhysicalType::BYTE_ARRAY
| PhysicalType::FIXED_LEN_BYTE_ARRAY => {
unreachable!(
"PrimitiveArrayReaders don't support complex physical types"
);
}
};
// cast to Arrow type
// We make a strong assumption here that the casts should be infallible.
// If the cast fails because of incompatible datatypes, then there might
// be a bigger problem with how Arrow schemas are converted to Parquet.
//
// As there is not always a 1:1 mapping between Arrow and Parquet, there
// are datatypes which we must convert explicitly.
// These are:
// - date64: we should cast int32 to date32, then date32 to date64.
let array = match target_type {
ArrowType::Date64 => {
// this is cheap as it internally reinterprets the data
let a = arrow::compute::cast(&array, &ArrowType::Date32)?;
arrow::compute::cast(&a, &target_type)?
}
ArrowType::Decimal(p, s) => {
let array = match array.data_type() {
ArrowType::Int32 => array
.as_any()
.downcast_ref::<Int32Array>()
.unwrap()
.iter()
.map(|v| v.map(|v| v.into()))
.collect::<DecimalArray>(),
ArrowType::Int64 => array
.as_any()
.downcast_ref::<Int64Array>()
.unwrap()
.iter()
.map(|v| v.map(|v| v.into()))
.collect::<DecimalArray>(),
_ => {
return Err(ArrowError(format!(
"Cannot convert {:?} to decimal",
array.data_type()
)))
}
}
.with_precision_and_scale(p, s)?;
Arc::new(array) as ArrayRef
}
_ => arrow::compute::cast(&array, &target_type)?,
};
// save definition and repetition buffers
self.def_levels_buffer = self.record_reader.consume_def_levels()?;
self.rep_levels_buffer = self.record_reader.consume_rep_levels()?;
self.record_reader.reset();
Ok(array)
}
fn get_def_levels(&self) -> Option<&[i16]> {
self.def_levels_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
fn get_rep_levels(&self) -> Option<&[i16]> {
self.rep_levels_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
}
/// Primitive array readers are leaves of array reader tree. They accept page iterator
/// and read them into primitive arrays.
pub struct ComplexObjectArrayReader<T, C>
where
T: DataType,
C: Converter<Vec<Option<T::T>>, ArrayRef> + 'static,
{
data_type: ArrowType,
pages: Box<dyn PageIterator>,
def_levels_buffer: Option<Vec<i16>>,
rep_levels_buffer: Option<Vec<i16>>,
column_desc: ColumnDescPtr,
column_reader: Option<ColumnReaderImpl<T>>,
converter: C,
_parquet_type_marker: PhantomData<T>,
_converter_marker: PhantomData<C>,
}
impl<T, C> ArrayReader for ComplexObjectArrayReader<T, C>
where
T: DataType,
C: Converter<Vec<Option<T::T>>, ArrayRef> + Send + 'static,
{
fn as_any(&self) -> &dyn Any {
self
}
fn get_data_type(&self) -> &ArrowType {
&self.data_type
}
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef> {
// Try to initialize column reader
if self.column_reader.is_none() {
self.next_column_reader()?;
}
let mut data_buffer: Vec<T::T> = Vec::with_capacity(batch_size);
data_buffer.resize_with(batch_size, T::T::default);
let mut def_levels_buffer = if self.column_desc.max_def_level() > 0 {
let mut buf: Vec<i16> = Vec::with_capacity(batch_size);
buf.resize_with(batch_size, || 0);
Some(buf)
} else {
None
};
let mut rep_levels_buffer = if self.column_desc.max_rep_level() > 0 {
let mut buf: Vec<i16> = Vec::with_capacity(batch_size);
buf.resize_with(batch_size, || 0);
Some(buf)
} else {
None
};
let mut num_read = 0;
while self.column_reader.is_some() && num_read < batch_size {
let num_to_read = batch_size - num_read;
let cur_data_buf = &mut data_buffer[num_read..];
let cur_def_levels_buf =
def_levels_buffer.as_mut().map(|b| &mut b[num_read..]);
let cur_rep_levels_buf =
rep_levels_buffer.as_mut().map(|b| &mut b[num_read..]);
let (data_read, levels_read) =
self.column_reader.as_mut().unwrap().read_batch(
num_to_read,
cur_def_levels_buf,
cur_rep_levels_buf,
cur_data_buf,
)?;
// Fill space
if levels_read > data_read {
def_levels_buffer.iter().for_each(|def_levels_buffer| {
let (mut level_pos, mut data_pos) = (levels_read, data_read);
while level_pos > 0 && data_pos > 0 {
if def_levels_buffer[num_read + level_pos - 1]
== self.column_desc.max_def_level()
{
cur_data_buf.swap(level_pos - 1, data_pos - 1);
level_pos -= 1;
data_pos -= 1;
} else {
level_pos -= 1;
}
}
});
}
let values_read = max(levels_read, data_read);
num_read += values_read;
// current page exhausted && page iterator exhausted
if values_read < num_to_read && !self.next_column_reader()? {
break;
}
}
data_buffer.truncate(num_read);
def_levels_buffer
.iter_mut()
.for_each(|buf| buf.truncate(num_read));
rep_levels_buffer
.iter_mut()
.for_each(|buf| buf.truncate(num_read));
self.def_levels_buffer = def_levels_buffer;
self.rep_levels_buffer = rep_levels_buffer;
let data: Vec<Option<T::T>> = if self.def_levels_buffer.is_some() {
data_buffer
.into_iter()
.zip(self.def_levels_buffer.as_ref().unwrap().iter())
.map(|(t, def_level)| {
if *def_level == self.column_desc.max_def_level() {
Some(t)
} else {
None
}
})
.collect()
} else {
data_buffer.into_iter().map(Some).collect()
};
let mut array = self.converter.convert(data)?;
if let ArrowType::Dictionary(_, _) = self.data_type {
array = arrow::compute::cast(&array, &self.data_type)?;
}
Ok(array)
}
fn get_def_levels(&self) -> Option<&[i16]> {
self.def_levels_buffer.as_deref()
}
fn get_rep_levels(&self) -> Option<&[i16]> {
self.rep_levels_buffer.as_deref()
}
}
impl<T, C> ComplexObjectArrayReader<T, C>
where
T: DataType,
C: Converter<Vec<Option<T::T>>, ArrayRef> + 'static,
{
pub fn new(
pages: Box<dyn PageIterator>,
column_desc: ColumnDescPtr,
converter: C,
arrow_type: Option<ArrowType>,
) -> Result<Self> {
let data_type = match arrow_type {
Some(t) => t,
None => parquet_to_arrow_field(column_desc.as_ref())?
.data_type()
.clone(),
};
Ok(Self {
data_type,
pages,
def_levels_buffer: None,
rep_levels_buffer: None,
column_desc,
column_reader: None,
converter,
_parquet_type_marker: PhantomData,
_converter_marker: PhantomData,
})
}
fn next_column_reader(&mut self) -> Result<bool> {
Ok(match self.pages.next() {
Some(page) => {
self.column_reader =
Some(ColumnReaderImpl::<T>::new(self.column_desc.clone(), page?));
true
}
None => false,
})
}
}
/// Implementation of list array reader.
pub struct ListArrayReader<OffsetSize: OffsetSizeTrait> {
item_reader: Box<dyn ArrayReader>,
data_type: ArrowType,
item_type: ArrowType,
list_def_level: i16,
list_rep_level: i16,
list_empty_def_level: i16,
list_null_def_level: i16,
def_level_buffer: Option<Buffer>,
rep_level_buffer: Option<Buffer>,
_marker: PhantomData<OffsetSize>,
}
impl<OffsetSize: OffsetSizeTrait> ListArrayReader<OffsetSize> {
/// Construct list array reader.
pub fn new(
item_reader: Box<dyn ArrayReader>,
data_type: ArrowType,
item_type: ArrowType,
def_level: i16,
rep_level: i16,
list_null_def_level: i16,
list_empty_def_level: i16,
) -> Self {
Self {
item_reader,
data_type,
item_type,
list_def_level: def_level,
list_rep_level: rep_level,
list_null_def_level,
list_empty_def_level,
def_level_buffer: None,
rep_level_buffer: None,
_marker: PhantomData,
}
}
}
/// Implementation of ListArrayReader. Nested lists and lists of structs are not yet supported.
impl<OffsetSize: OffsetSizeTrait> ArrayReader for ListArrayReader<OffsetSize> {
fn as_any(&self) -> &dyn Any {
self
}
/// Returns data type.
/// This must be a List.
fn get_data_type(&self) -> &ArrowType {
&self.data_type
}
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef> {
let next_batch_array = self.item_reader.next_batch(batch_size)?;
if next_batch_array.len() == 0 {
return Ok(new_empty_array(&self.data_type));
}
let def_levels = self
.item_reader
.get_def_levels()
.ok_or_else(|| ArrowError("item_reader def levels are None.".to_string()))?;
let rep_levels = self
.item_reader
.get_rep_levels()
.ok_or_else(|| ArrowError("item_reader rep levels are None.".to_string()))?;
if !((def_levels.len() == rep_levels.len())
&& (rep_levels.len() == next_batch_array.len()))
{
return Err(ArrowError(
format!("Expected item_reader def_levels {} and rep_levels {} to be same length as batch {}", def_levels.len(), rep_levels.len(), next_batch_array.len()),
));
}
// List definitions can be encoded as 4 values:
// - n + 0: the list slot is null
// - n + 1: the list slot is not null, but is empty (i.e. [])
// - n + 2: the list slot is not null, but its child is empty (i.e. [ null ])
// - n + 3: the list slot is not null, and its child is not empty
// Where n is the max definition level of the list's parent.
// If a Parquet schema's only leaf is the list, then n = 0.
// If the list index is at empty definition, the child slot is null
let non_null_list_indices =
def_levels.iter().enumerate().filter_map(|(index, def)| {
(*def > self.list_empty_def_level).then(|| index as u32)
});
let indices = UInt32Array::from_iter_values(non_null_list_indices);
let batch_values = take(&*next_batch_array.clone(), &indices, None)?;
// first item in each list has rep_level = 0, subsequent items have rep_level = 1
let mut offsets: Vec<OffsetSize> = Vec::new();
let mut cur_offset = OffsetSize::zero();
def_levels.iter().zip(rep_levels).for_each(|(d, r)| {
if *r == 0 || d == &self.list_empty_def_level {
offsets.push(cur_offset);
}
if d > &self.list_empty_def_level {
cur_offset += OffsetSize::one();
}
});
offsets.push(cur_offset);
let num_bytes = bit_util::ceil(offsets.len(), 8);
// TODO: A useful optimization is to use the null count to fill with
// 0 or null, to reduce individual bits set in a loop.
// To favour dense data, set every slot to true, then unset
let mut null_buf = MutableBuffer::new(num_bytes).with_bitset(num_bytes, true);
let null_slice = null_buf.as_slice_mut();
let mut list_index = 0;
for i in 0..rep_levels.len() {
// If the level is lower than empty, then the slot is null.
// When a list is non-nullable, its empty level = null level,
// so this automatically factors that in.
if rep_levels[i] == 0 && def_levels[i] < self.list_empty_def_level {
bit_util::unset_bit(null_slice, list_index);
}
if rep_levels[i] == 0 {
list_index += 1;
}
}
let value_offsets = Buffer::from(&offsets.to_byte_slice());
let list_data = ArrayData::builder(self.get_data_type().clone())
.len(offsets.len() - 1)
.add_buffer(value_offsets)
.add_child_data(batch_values.data().clone())
.null_bit_buffer(null_buf.into())
.offset(next_batch_array.offset());
let list_data = unsafe { list_data.build_unchecked() };
let result_array = GenericListArray::<OffsetSize>::from(list_data);
Ok(Arc::new(result_array))
}
fn get_def_levels(&self) -> Option<&[i16]> {
self.def_level_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
fn get_rep_levels(&self) -> Option<&[i16]> {
self.rep_level_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
}
/// Implementation of a map array reader.
pub struct MapArrayReader {
key_reader: Box<dyn ArrayReader>,
value_reader: Box<dyn ArrayReader>,
data_type: ArrowType,
map_def_level: i16,
map_rep_level: i16,
def_level_buffer: Option<Buffer>,
rep_level_buffer: Option<Buffer>,
}
impl MapArrayReader {
pub fn new(
key_reader: Box<dyn ArrayReader>,
value_reader: Box<dyn ArrayReader>,
data_type: ArrowType,
def_level: i16,
rep_level: i16,
) -> Self {
Self {
key_reader,
value_reader,
data_type,
map_def_level: rep_level,
map_rep_level: def_level,
def_level_buffer: None,
rep_level_buffer: None,
}
}
}
impl ArrayReader for MapArrayReader {
fn as_any(&self) -> &dyn Any {
self
}
fn get_data_type(&self) -> &ArrowType {
&self.data_type
}
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef> {
let key_array = self.key_reader.next_batch(batch_size)?;
let value_array = self.value_reader.next_batch(batch_size)?;
// Check that key and value have the same lengths
let key_length = key_array.len();
if key_length != value_array.len() {
return Err(general_err!(
"Map key and value should have the same lengths."
));
}
let def_levels = self
.key_reader
.get_def_levels()
.ok_or_else(|| ArrowError("item_reader def levels are None.".to_string()))?;
let rep_levels = self
.key_reader
.get_rep_levels()
.ok_or_else(|| ArrowError("item_reader rep levels are None.".to_string()))?;
if !((def_levels.len() == rep_levels.len()) && (rep_levels.len() == key_length)) {
return Err(ArrowError(
"Expected item_reader def_levels and rep_levels to be same length as batch".to_string(),
));
}
let entry_data_type = if let ArrowType::Map(field, _) = &self.data_type {
field.data_type().clone()
} else {
return Err(ArrowError("Expected a map arrow type".to_string()));
};
let entry_data = ArrayDataBuilder::new(entry_data_type)
.len(key_length)
.add_child_data(key_array.data().clone())
.add_child_data(value_array.data().clone());
let entry_data = unsafe { entry_data.build_unchecked() };
let entry_len = rep_levels.iter().filter(|level| **level == 0).count();
// first item in each list has rep_level = 0, subsequent items have rep_level = 1
let mut offsets: Vec<i32> = Vec::new();
let mut cur_offset = 0;
def_levels.iter().zip(rep_levels).for_each(|(d, r)| {
if *r == 0 || d == &self.map_def_level {
offsets.push(cur_offset);
}
if d > &self.map_def_level {
cur_offset += 1;
}
});
offsets.push(cur_offset);
let num_bytes = bit_util::ceil(offsets.len(), 8);
// TODO: A useful optimization is to use the null count to fill with
// 0 or null, to reduce individual bits set in a loop.
// To favour dense data, set every slot to true, then unset
let mut null_buf = MutableBuffer::new(num_bytes).with_bitset(num_bytes, true);
let null_slice = null_buf.as_slice_mut();
let mut list_index = 0;
for i in 0..rep_levels.len() {
// If the level is lower than empty, then the slot is null.
// When a list is non-nullable, its empty level = null level,
// so this automatically factors that in.
if rep_levels[i] == 0 && def_levels[i] < self.map_def_level {
// should be empty list
bit_util::unset_bit(null_slice, list_index);
}
if rep_levels[i] == 0 {
list_index += 1;
}
}
let value_offsets = Buffer::from(&offsets.to_byte_slice());
// Now we can build array data
let array_data = ArrayDataBuilder::new(self.data_type.clone())
.len(entry_len)
.add_buffer(value_offsets)
.null_bit_buffer(null_buf.into())
.add_child_data(entry_data);
let array_data = unsafe { array_data.build_unchecked() };
Ok(Arc::new(MapArray::from(array_data)))
}
fn get_def_levels(&self) -> Option<&[i16]> {
self.def_level_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
fn get_rep_levels(&self) -> Option<&[i16]> {
self.rep_level_buffer
.as_ref()
.map(|buf| unsafe { buf.typed_data() })
}
}
/// Implementation of struct array reader.
pub struct StructArrayReader {
children: Vec<Box<dyn ArrayReader>>,
data_type: ArrowType,
struct_def_level: i16,
struct_rep_level: i16,
def_level_buffer: Option<Buffer>,
rep_level_buffer: Option<Buffer>,
}
impl StructArrayReader {
/// Construct struct array reader.
pub fn new(
data_type: ArrowType,
children: Vec<Box<dyn ArrayReader>>,
def_level: i16,
rep_level: i16,
) -> Self {
Self {
data_type,
children,
struct_def_level: def_level,
struct_rep_level: rep_level,
def_level_buffer: None,
rep_level_buffer: None,
}
}
}
impl ArrayReader for StructArrayReader {
fn as_any(&self) -> &dyn Any {
self
}
/// Returns data type.
/// This must be a struct.
fn get_data_type(&self) -> &ArrowType {
&self.data_type
}
/// Read `batch_size` struct records.
///
/// Definition levels of struct array is calculated as following:
/// ```ignore
/// def_levels[i] = min(child1_def_levels[i], child2_def_levels[i], ...,
/// childn_def_levels[i]);
/// ```
///
/// Repetition levels of struct array is calculated as following:
/// ```ignore
/// rep_levels[i] = child1_rep_levels[i];
/// ```
///
/// The null bitmap of struct array is calculated from def_levels:
/// ```ignore
/// null_bitmap[i] = (def_levels[i] >= self.def_level);
/// ```
fn next_batch(&mut self, batch_size: usize) -> Result<ArrayRef> {
if self.children.is_empty() {