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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::cmp::{max, min};
use std::collections::{HashMap, HashSet};
use std::marker::PhantomData;
use std::mem::size_of;
use std::rc::Rc;
use std::result::Result::Ok;
use std::sync::Arc;
use std::vec::Vec;
use arrow::array::{
Array, ArrayData, ArrayDataBuilder, ArrayDataRef, ArrayRef, BinaryArray,
BinaryBuilder, BooleanBufferBuilder, BufferBuilderTrait, FixedSizeBinaryArray,
FixedSizeBinaryBuilder, GenericListArray, Int16BufferBuilder, ListBuilder,
OffsetSizeTrait, PrimitiveArray, PrimitiveArrayOps, PrimitiveBuilder, StringArray,
StringBuilder, StructArray,
};
use arrow::buffer::{Buffer, MutableBuffer};
use arrow::datatypes::{
BooleanType as ArrowBooleanType, DataType as ArrowType,
Date32Type as ArrowDate32Type, Date64Type as ArrowDate64Type, DateUnit,
DurationMicrosecondType as ArrowDurationMicrosecondType,
DurationMillisecondType as ArrowDurationMillisecondType,
DurationNanosecondType as ArrowDurationNanosecondType,
DurationSecondType as ArrowDurationSecondType, Field,
Float32Type as ArrowFloat32Type, Float64Type as ArrowFloat64Type,
Int16Type as ArrowInt16Type, Int32Type as ArrowInt32Type,
Int64Type as ArrowInt64Type, Int8Type as ArrowInt8Type, IntervalUnit, Schema,
Time32MillisecondType as ArrowTime32MillisecondType,
Time32SecondType as ArrowTime32SecondType,
Time64MicrosecondType as ArrowTime64MicrosecondType,
Time64NanosecondType as ArrowTime64NanosecondType, TimeUnit,
TimeUnit as ArrowTimeUnit, TimestampMicrosecondType as ArrowTimestampMicrosecondType,
TimestampMillisecondType as ArrowTimestampMillisecondType,
TimestampNanosecondType as ArrowTimestampNanosecondType,
TimestampSecondType as ArrowTimestampSecondType, ToByteSlice,
UInt16Type as ArrowUInt16Type, UInt32Type as ArrowUInt32Type,
UInt64Type as ArrowUInt64Type, UInt8Type as ArrowUInt8Type,
};
use arrow::util::bit_util;
use crate::arrow::converter::{
BinaryArrayConverter, BinaryConverter, BoolConverter, BooleanArrayConverter,
Converter, Date32Converter, DictionaryArrayConverter, DictionaryConverter,
FixedLenBinaryConverter, FixedSizeArrayConverter, Float32Converter, Float64Converter,
Int16Converter, Int32Converter, Int64Converter, Int8Converter, Int96ArrayConverter,
Int96Converter, LargeBinaryArrayConverter, LargeBinaryConverter,
LargeUtf8ArrayConverter, LargeUtf8Converter, Time32MillisecondConverter,
Time32SecondConverter, Time64MicrosecondConverter, Time64NanosecondConverter,
TimestampMicrosecondConverter, TimestampMillisecondConverter, UInt16Converter,
UInt32Converter, UInt64Converter, UInt8Converter, Utf8ArrayConverter, Utf8Converter,
};
use crate::arrow::record_reader::RecordReader;
use crate::arrow::schema::parquet_to_arrow_field;
use crate::basic::{LogicalType, Repetition, Type as PhysicalType};
use crate::column::page::PageIterator;
use crate::column::reader::ColumnReaderImpl;
use crate::data_type::{
BoolType, ByteArrayType, DataType, DoubleType, FixedLenByteArrayType, FloatType,
Int32Type, Int64Type, Int96Type,
};
use crate::errors::{ParquetError, ParquetError::ArrowError, Result};
use crate::file::reader::{FilePageIterator, FileReader};
use crate::schema::types::{
ColumnDescPtr, ColumnDescriptor, ColumnPath, SchemaDescPtr, Type, TypePtr,
};
use crate::schema::visitor::TypeVisitor;
use std::any::Any;
/// Array reader reads parquet data into arrow array.
pub trait ArrayReader {
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>;
/// Returns the definition levels of data from last call of `next_batch`.
/// The result is used by parent array reader to calculate its own definition
/// levels and repetition levels, so that its parent can calculate null bitmap.
fn get_def_levels(&self) -> Option<&[i16]>;
/// Return the repetition levels of data from last call of `next_batch`.
/// The result is used by parent array reader to calculate its own definition
/// levels and repetition levels, so that its parent can calculate null bitmap.
fn get_rep_levels(&self) -> Option<&[i16]>;
}
/// A NullArrayReader reads Parquet columns stored as null int32s with an Arrow
/// NullArray type.
pub struct NullArrayReader<T: DataType> {
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: DataType> NullArrayReader<T> {
/// Construct null array reader.
pub fn new(
mut pages: Box<dyn PageIterator>,
column_desc: ColumnDescPtr,
) -> Result<Self> {
let mut record_reader = RecordReader::<T>::new(column_desc.clone());
if let Some(page_reader) = pages.next() {
record_reader.set_page_reader(page_reader?)?;
}
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: DataType> ArrayReader for NullArrayReader<T> {
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> {
let mut records_read = 0usize;
while records_read < batch_size {
let records_to_read = batch_size - records_read;
// NB can be 0 if at end of page
let records_read_once = self.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) = self.pages.next() {
// Read from new page reader
self.record_reader.set_page_reader(page_reader?)?;
} else {
// Page reader also exhausted
break;
}
}
}
// convert to arrays
let array = arrow::array::NullArray::new(records_read);
// 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(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: DataType> {
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: DataType> PrimitiveArrayReader<T> {
/// Construct primitive array reader.
pub fn new(
mut pages: Box<dyn PageIterator>,
column_desc: ColumnDescPtr,
) -> Result<Self> {
let data_type = parquet_to_arrow_field(column_desc.as_ref())?
.data_type()
.clone();
let mut record_reader = RecordReader::<T>::new(column_desc.clone());
if let Some(page_reader) = pages.next() {
record_reader.set_page_reader(page_reader?)?;
}
Ok(Self {
data_type,
pages,
def_levels_buffer: None,
rep_levels_buffer: None,
column_desc,
record_reader,
_type_marker: PhantomData,
})
}
}
/// Implementation of primitive array reader.
impl<T: DataType> ArrayReader for PrimitiveArrayReader<T> {
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> {
let mut records_read = 0usize;
while records_read < batch_size {
let records_to_read = batch_size - records_read;
// NB can be 0 if at end of page
let records_read_once = self.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) = self.pages.next() {
// Read from new page reader
self.record_reader.set_page_reader(page_reader?)?;
} else {
// Page reader also exhausted
break;
}
}
}
// convert to arrays
let array =
match (&self.data_type, T::get_physical_type()) {
(ArrowType::Boolean, PhysicalType::BOOLEAN) => {
BoolConverter::new(BooleanArrayConverter {})
.convert(self.record_reader.cast::<BoolType>())
}
(ArrowType::Int8, PhysicalType::INT32) => {
Int8Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::Int16, PhysicalType::INT32) => {
Int16Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::Int32, PhysicalType::INT32) => {
Int32Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::UInt8, PhysicalType::INT32) => {
UInt8Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::UInt16, PhysicalType::INT32) => {
UInt16Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::UInt32, PhysicalType::INT32) => {
UInt32Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::Int64, PhysicalType::INT64) => {
Int64Converter::new().convert(self.record_reader.cast::<Int64Type>())
}
(ArrowType::UInt64, PhysicalType::INT64) => {
UInt64Converter::new().convert(self.record_reader.cast::<Int64Type>())
}
(ArrowType::Float32, PhysicalType::FLOAT) => Float32Converter::new()
.convert(self.record_reader.cast::<FloatType>()),
(ArrowType::Float64, PhysicalType::DOUBLE) => Float64Converter::new()
.convert(self.record_reader.cast::<DoubleType>()),
(ArrowType::Timestamp(unit, _), PhysicalType::INT64) => match unit {
TimeUnit::Millisecond => TimestampMillisecondConverter::new()
.convert(self.record_reader.cast::<Int64Type>()),
TimeUnit::Microsecond => TimestampMicrosecondConverter::new()
.convert(self.record_reader.cast::<Int64Type>()),
_ => Err(general_err!("No conversion from parquet type to arrow type for timestamp with unit {:?}", unit)),
},
(ArrowType::Date32(unit), PhysicalType::INT32) => match unit {
DateUnit::Day => Date32Converter::new()
.convert(self.record_reader.cast::<Int32Type>()),
_ => Err(general_err!("No conversion from parquet type to arrow type for date with unit {:?}", unit)),
}
(ArrowType::Time32(unit), PhysicalType::INT32) => {
match unit {
TimeUnit::Second => {
Time32SecondConverter::new().convert(self.record_reader.cast::<Int32Type>())
}
TimeUnit::Millisecond => {
Time32MillisecondConverter::new().convert(self.record_reader.cast::<Int32Type>())
}
_ => Err(general_err!("Invalid or unsupported arrow array with datatype {:?}", self.get_data_type()))
}
}
(ArrowType::Time64(unit), PhysicalType::INT64) => {
match unit {
TimeUnit::Microsecond => {
Time64MicrosecondConverter::new().convert(self.record_reader.cast::<Int64Type>())
}
TimeUnit::Nanosecond => {
Time64NanosecondConverter::new().convert(self.record_reader.cast::<Int64Type>())
}
_ => Err(general_err!("Invalid or unsupported arrow array with datatype {:?}", self.get_data_type()))
}
}
(ArrowType::Interval(IntervalUnit::YearMonth), PhysicalType::INT32) => {
UInt32Converter::new().convert(self.record_reader.cast::<Int32Type>())
}
(ArrowType::Interval(IntervalUnit::DayTime), PhysicalType::INT64) => {
UInt64Converter::new().convert(self.record_reader.cast::<Int64Type>())
}
(ArrowType::Duration(_), PhysicalType::INT64) => {
UInt64Converter::new().convert(self.record_reader.cast::<Int64Type>())
}
(arrow_type, physical_type) => Err(general_err!(
"Reading {:?} type from parquet {:?} is not supported yet.",
arrow_type,
physical_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> + '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 initialized column reader
if self.column_reader.is_none() {
let init_result = self.next_column_reader()?;
if !init_result {
return Err(general_err!("No page left!"));
}
}
assert!(self.column_reader.is_some());
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 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()
};
self.converter.convert(data)
}
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,
{
fn new(
pages: Box<dyn PageIterator>,
column_desc: ColumnDescPtr,
converter: C,
) -> Result<Self> {
let data_type = 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,
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,
) -> Self {
Self {
item_reader,
data_type,
item_type,
list_def_level: def_level,
list_rep_level: rep_level,
def_level_buffer: None,
rep_level_buffer: None,
_marker: PhantomData,
}
}
}
macro_rules! build_empty_list_array_with_primitive_items {
($item_type:ident) => {{
let values_builder = PrimitiveBuilder::<$item_type>::new(0);
let mut builder = ListBuilder::new(values_builder);
let empty_list_array = builder.finish();
Ok(Arc::new(empty_list_array))
}};
}
macro_rules! build_empty_list_array_with_non_primitive_items {
($builder:ident) => {{
let values_builder = $builder::new(0);
let mut builder = ListBuilder::new(values_builder);
let empty_list_array = builder.finish();
Ok(Arc::new(empty_list_array))
}};
}
fn build_empty_list_array(item_type: ArrowType) -> Result<ArrayRef> {
match item_type {
ArrowType::UInt8 => build_empty_list_array_with_primitive_items!(ArrowUInt8Type),
ArrowType::UInt16 => {
build_empty_list_array_with_primitive_items!(ArrowUInt16Type)
}
ArrowType::UInt32 => {
build_empty_list_array_with_primitive_items!(ArrowUInt32Type)
}
ArrowType::UInt64 => {
build_empty_list_array_with_primitive_items!(ArrowUInt64Type)
}
ArrowType::Int8 => build_empty_list_array_with_primitive_items!(ArrowInt8Type),
ArrowType::Int16 => build_empty_list_array_with_primitive_items!(ArrowInt16Type),
ArrowType::Int32 => build_empty_list_array_with_primitive_items!(ArrowInt32Type),
ArrowType::Int64 => build_empty_list_array_with_primitive_items!(ArrowInt64Type),
ArrowType::Float32 => {
build_empty_list_array_with_primitive_items!(ArrowFloat32Type)
}
ArrowType::Float64 => {
build_empty_list_array_with_primitive_items!(ArrowFloat64Type)
}
ArrowType::Boolean => {
build_empty_list_array_with_primitive_items!(ArrowBooleanType)
}
ArrowType::Date32(_) => {
build_empty_list_array_with_primitive_items!(ArrowDate32Type)
}
ArrowType::Date64(_) => {
build_empty_list_array_with_primitive_items!(ArrowDate64Type)
}
ArrowType::Time32(ArrowTimeUnit::Second) => {
build_empty_list_array_with_primitive_items!(ArrowTime32SecondType)
}
ArrowType::Time32(ArrowTimeUnit::Millisecond) => {
build_empty_list_array_with_primitive_items!(ArrowTime32MillisecondType)
}
ArrowType::Time64(ArrowTimeUnit::Microsecond) => {
build_empty_list_array_with_primitive_items!(ArrowTime64MicrosecondType)
}
ArrowType::Time64(ArrowTimeUnit::Nanosecond) => {
build_empty_list_array_with_primitive_items!(ArrowTime64NanosecondType)
}
ArrowType::Duration(ArrowTimeUnit::Second) => {
build_empty_list_array_with_primitive_items!(ArrowDurationSecondType)
}
ArrowType::Duration(ArrowTimeUnit::Millisecond) => {
build_empty_list_array_with_primitive_items!(ArrowDurationMillisecondType)
}
ArrowType::Duration(ArrowTimeUnit::Microsecond) => {
build_empty_list_array_with_primitive_items!(ArrowDurationMicrosecondType)
}
ArrowType::Duration(ArrowTimeUnit::Nanosecond) => {
build_empty_list_array_with_primitive_items!(ArrowDurationNanosecondType)
}
ArrowType::Timestamp(ArrowTimeUnit::Second, _) => {
build_empty_list_array_with_primitive_items!(ArrowTimestampSecondType)
}
ArrowType::Timestamp(ArrowTimeUnit::Millisecond, _) => {
build_empty_list_array_with_primitive_items!(ArrowTimestampMillisecondType)
}
ArrowType::Timestamp(ArrowTimeUnit::Microsecond, _) => {
build_empty_list_array_with_primitive_items!(ArrowTimestampMicrosecondType)
}
ArrowType::Timestamp(ArrowTimeUnit::Nanosecond, _) => {
build_empty_list_array_with_primitive_items!(ArrowTimestampNanosecondType)
}
ArrowType::Utf8 => {
build_empty_list_array_with_non_primitive_items!(StringBuilder)
}
ArrowType::Binary => {
build_empty_list_array_with_non_primitive_items!(BinaryBuilder)
}
_ => Err(ParquetError::General(format!(
"ListArray of type List({:?}) is not supported by array_reader",
item_type
))),
}
}
macro_rules! remove_primitive_array_indices {
($arr: expr, $item_type:ty, $indices:expr) => {{
let array_data = match $arr.as_any().downcast_ref::<PrimitiveArray<$item_type>>() {
Some(a) => a,
_ => return Err(ParquetError::General(format!("Error generating next batch for ListArray: {:?} cannot be downcast to PrimitiveArray", $arr))),
};
let mut builder = PrimitiveBuilder::<$item_type>::new($arr.len());
for i in 0..array_data.len() {
if !$indices.contains(&i) {
if array_data.is_null(i) {
builder.append_null()?;
} else {
builder.append_value(array_data.value(i))?;
}
}
}
Ok(Arc::new(builder.finish()))
}};
}
macro_rules! remove_array_indices_custom_builder {
($arr: expr, $array_type:ty, $item_builder:ident, $indices:expr) => {{
let array_data = match $arr.as_any().downcast_ref::<$array_type>() {
Some(a) => a,
_ => return Err(ParquetError::General(format!("Error generating next batch for ListArray: {:?} cannot be downcast to PrimitiveArray", $arr))),
};
let mut builder = $item_builder::new(array_data.len());
for i in 0..array_data.len() {
if !$indices.contains(&i) {
if array_data.is_null(i) {
builder.append_null()?;
} else {
builder.append_value(array_data.value(i))?;
}
}
}
Ok(Arc::new(builder.finish()))
}};
}
macro_rules! remove_fixed_size_binary_array_indices {
($arr: expr, $array_type:ty, $item_builder:ident, $indices:expr, $len:expr) => {{
let array_data = match $arr.as_any().downcast_ref::<$array_type>() {
Some(a) => a,
_ => return Err(ParquetError::General(format!("Error generating next batch for ListArray: {:?} cannot be downcast to PrimitiveArray", $arr))),
};
let mut builder = FixedSizeBinaryBuilder::new(array_data.len(), $len);
for i in 0..array_data.len() {
if !$indices.contains(&i) {
if array_data.is_null(i) {
builder.append_null()?;
} else {
builder.append_value(array_data.value(i))?;
}
}
}
Ok(Arc::new(builder.finish()))
}};
}
fn remove_indices(
arr: ArrayRef,
item_type: ArrowType,
indices: Vec<usize>,
) -> Result<ArrayRef> {
match item_type {
ArrowType::UInt8 => remove_primitive_array_indices!(arr, ArrowUInt8Type, indices),
ArrowType::UInt16 => {
remove_primitive_array_indices!(arr, ArrowUInt16Type, indices)
}
ArrowType::UInt32 => {
remove_primitive_array_indices!(arr, ArrowUInt32Type, indices)
}
ArrowType::UInt64 => {
remove_primitive_array_indices!(arr, ArrowUInt64Type, indices)
}
ArrowType::Int8 => remove_primitive_array_indices!(arr, ArrowInt8Type, indices),
ArrowType::Int16 => remove_primitive_array_indices!(arr, ArrowInt16Type, indices),
ArrowType::Int32 => remove_primitive_array_indices!(arr, ArrowInt32Type, indices),
ArrowType::Int64 => remove_primitive_array_indices!(arr, ArrowInt64Type, indices),
ArrowType::Float32 => {
remove_primitive_array_indices!(arr, ArrowFloat32Type, indices)
}
ArrowType::Float64 => {
remove_primitive_array_indices!(arr, ArrowFloat64Type, indices)
}
ArrowType::Boolean => {
remove_primitive_array_indices!(arr, ArrowBooleanType, indices)
}
ArrowType::Date32(_) => {
remove_primitive_array_indices!(arr, ArrowDate32Type, indices)
}
ArrowType::Date64(_) => {
remove_primitive_array_indices!(arr, ArrowDate64Type, indices)
}
ArrowType::Time32(ArrowTimeUnit::Second) => {
remove_primitive_array_indices!(arr, ArrowTime32SecondType, indices)
}
ArrowType::Time32(ArrowTimeUnit::Millisecond) => {
remove_primitive_array_indices!(arr, ArrowTime32MillisecondType, indices)
}
ArrowType::Time64(ArrowTimeUnit::Microsecond) => {
remove_primitive_array_indices!(arr, ArrowTime64MicrosecondType, indices)
}
ArrowType::Time64(ArrowTimeUnit::Nanosecond) => {
remove_primitive_array_indices!(arr, ArrowTime64NanosecondType, indices)
}
ArrowType::Duration(ArrowTimeUnit::Second) => {
remove_primitive_array_indices!(arr, ArrowDurationSecondType, indices)
}
ArrowType::Duration(ArrowTimeUnit::Millisecond) => {
remove_primitive_array_indices!(arr, ArrowDurationMillisecondType, indices)
}
ArrowType::Duration(ArrowTimeUnit::Microsecond) => {
remove_primitive_array_indices!(arr, ArrowDurationMicrosecondType, indices)
}
ArrowType::Duration(ArrowTimeUnit::Nanosecond) => {
remove_primitive_array_indices!(arr, ArrowDurationNanosecondType, indices)
}
ArrowType::Timestamp(ArrowTimeUnit::Second, _) => {
remove_primitive_array_indices!(arr, ArrowTimestampSecondType, indices)
}
ArrowType::Timestamp(ArrowTimeUnit::Millisecond, _) => {
remove_primitive_array_indices!(arr, ArrowTimestampMillisecondType, indices)
}
ArrowType::Timestamp(ArrowTimeUnit::Microsecond, _) => {
remove_primitive_array_indices!(arr, ArrowTimestampMicrosecondType, indices)
}
ArrowType::Timestamp(ArrowTimeUnit::Nanosecond, _) => {
remove_primitive_array_indices!(arr, ArrowTimestampNanosecondType, indices)
}
ArrowType::Utf8 => {
remove_array_indices_custom_builder!(arr, StringArray, StringBuilder, indices)
}
ArrowType::Binary => {
remove_array_indices_custom_builder!(arr, BinaryArray, BinaryBuilder, indices)
}
ArrowType::FixedSizeBinary(size) => remove_fixed_size_binary_array_indices!(
arr,
FixedSizeBinaryArray,
FixedSizeBinaryBuilder,
indices,
size
),
_ => Err(ParquetError::General(format!(
"ListArray of type List({:?}) is not supported by array_reader",
item_type
))),
}
}
/// 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)?;
let item_type = self.item_reader.get_data_type().clone();
if next_batch_array.len() == 0 {
return build_empty_list_array(item_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(
"Expected item_reader def_levels and rep_levels to be same length as batch".to_string(),
));
}
// Need to remove from the values array the nulls that represent null lists rather than null items
// null lists have def_level = 0
let mut null_list_indices: Vec<usize> = Vec::new();
for i in 0..def_levels.len() {
if def_levels[i] == 0 {
null_list_indices.push(i);
}
}
let batch_values = match null_list_indices.len() {
0 => next_batch_array.clone(),
_ => remove_indices(next_batch_array.clone(), item_type, null_list_indices)?,
};
// null list has def_level = 0
// empty list has def_level = 1
// null item in a list has def_level = 2
// non-null item has def_level = 3
// 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();
for i in 0..rep_levels.len() {
if rep_levels[i] == 0 {
offsets.push(cur_offset)
}
if def_levels[i] > 0 {
cur_offset = cur_offset + OffsetSize::one();
}
}
offsets.push(cur_offset);
let num_bytes = bit_util::ceil(offsets.len(), 8);
let mut null_buf = MutableBuffer::new(num_bytes).with_bitset(num_bytes, false);
let null_slice = null_buf.data_mut();
let mut list_index = 0;
for i in 0..rep_levels.len() {
if rep_levels[i] == 0 && def_levels[i] != 0 {
bit_util::set_bit(null_slice, list_index);
}
if rep_levels[i] == 0 {
list_index += 1;
}
}
let value_offsets = Buffer::from(&offsets.to_byte_slice());
// null list has def_level = 0
let null_count = def_levels.iter().filter(|x| x == &&0).count();
let list_data = ArrayData::builder(self.get_data_type().clone())
.len(offsets.len() - 1)
.add_buffer(value_offsets)
.add_child_data(batch_values.data())
.null_bit_buffer(null_buf.freeze())
.null_count(null_count)
.offset(next_batch_array.offset())
.build();
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 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