parquet/arrow/async_writer/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.
//! Contains async writer which writes arrow data into parquet data.
//!
//! Provides `async` API for writing [`RecordBatch`]es as parquet files. The API is
//! similar to the [`sync` API](crate::arrow::arrow_writer::ArrowWriter), so please
//! read the documentation there before using this API.
//!
//! Here is an example for using [`AsyncArrowWriter`]:
//!
//! ```
//! # #[tokio::main(flavor="current_thread")]
//! # async fn main() {
//! #
//! # use std::sync::Arc;
//! # use arrow_array::{ArrayRef, Int64Array, RecordBatch, RecordBatchReader};
//! # use bytes::Bytes;
//! # use parquet::arrow::{AsyncArrowWriter, arrow_reader::ParquetRecordBatchReaderBuilder};
//! #
//! let col = Arc::new(Int64Array::from_iter_values([1, 2, 3])) as ArrayRef;
//! let to_write = RecordBatch::try_from_iter([("col", col)]).unwrap();
//!
//! let mut buffer = Vec::new();
//! let mut writer = AsyncArrowWriter::try_new(&mut buffer, to_write.schema(), None).unwrap();
//! writer.write(&to_write).await.unwrap();
//! writer.close().await.unwrap();
//!
//! let buffer = Bytes::from(buffer);
//! let mut reader = ParquetRecordBatchReaderBuilder::try_new(buffer.clone())
//! .unwrap()
//! .build()
//! .unwrap();
//! let read = reader.next().unwrap().unwrap();
//!
//! assert_eq!(to_write, read);
//! # }
//! ```
//!
//! [`object_store`] provides it's native implementation of [`AsyncFileWriter`] by [`ParquetObjectWriter`].
#[cfg(feature = "object_store")]
mod store;
#[cfg(feature = "object_store")]
pub use store::*;
use crate::{
arrow::arrow_writer::ArrowWriterOptions,
arrow::ArrowWriter,
errors::{ParquetError, Result},
file::{metadata::RowGroupMetaData, properties::WriterProperties},
format::{FileMetaData, KeyValue},
};
use arrow_array::RecordBatch;
use arrow_schema::SchemaRef;
use bytes::Bytes;
use futures::future::BoxFuture;
use futures::FutureExt;
use std::mem;
use tokio::io::{AsyncWrite, AsyncWriteExt};
/// The asynchronous interface used by [`AsyncArrowWriter`] to write parquet files.
pub trait AsyncFileWriter: Send {
/// Write the provided bytes to the underlying writer
///
/// The underlying writer CAN decide to buffer the data or write it immediately.
/// This design allows the writer implementer to control the buffering and I/O scheduling.
///
/// The underlying writer MAY implement retry logic to prevent breaking users write process.
fn write(&mut self, bs: Bytes) -> BoxFuture<'_, Result<()>>;
/// Flush any buffered data to the underlying writer and finish writing process.
///
/// After `complete` returns `Ok(())`, caller SHOULD not call write again.
fn complete(&mut self) -> BoxFuture<'_, Result<()>>;
}
impl AsyncFileWriter for Box<dyn AsyncFileWriter + '_> {
fn write(&mut self, bs: Bytes) -> BoxFuture<'_, Result<()>> {
self.as_mut().write(bs)
}
fn complete(&mut self) -> BoxFuture<'_, Result<()>> {
self.as_mut().complete()
}
}
impl<T: AsyncWrite + Unpin + Send> AsyncFileWriter for T {
fn write(&mut self, bs: Bytes) -> BoxFuture<'_, Result<()>> {
async move {
self.write_all(&bs).await?;
Ok(())
}
.boxed()
}
fn complete(&mut self) -> BoxFuture<'_, Result<()>> {
async move {
self.flush().await?;
self.shutdown().await?;
Ok(())
}
.boxed()
}
}
/// Encodes [`RecordBatch`] to parquet, outputting to an [`AsyncFileWriter`]
///
/// ## Memory Usage
///
/// This writer eagerly writes data as soon as possible to the underlying [`AsyncFileWriter`],
/// permitting fine-grained control over buffering and I/O scheduling. However, the columnar
/// nature of parquet forces data for an entire row group to be buffered in memory, before
/// it can be flushed. Depending on the data and the configured row group size, this buffering
/// may be substantial.
///
/// Memory usage can be limited by calling [`Self::flush`] to flush the in progress row group,
/// although this will likely increase overall file size and reduce query performance.
/// See [ArrowWriter] for more information.
///
/// ```no_run
/// # use tokio::fs::File;
/// # use arrow_array::RecordBatch;
/// # use parquet::arrow::AsyncArrowWriter;
/// # async fn test() {
/// let mut writer: AsyncArrowWriter<File> = todo!();
/// let batch: RecordBatch = todo!();
/// writer.write(&batch).await.unwrap();
/// // Trigger an early flush if buffered size exceeds 1_000_000
/// if writer.in_progress_size() > 1_000_000 {
/// writer.flush().await.unwrap()
/// }
/// # }
/// ```
pub struct AsyncArrowWriter<W> {
/// Underlying sync writer
sync_writer: ArrowWriter<Vec<u8>>,
/// Async writer provided by caller
async_writer: W,
}
impl<W: AsyncFileWriter> AsyncArrowWriter<W> {
/// Try to create a new Async Arrow Writer
pub fn try_new(
writer: W,
arrow_schema: SchemaRef,
props: Option<WriterProperties>,
) -> Result<Self> {
let options = ArrowWriterOptions::new().with_properties(props.unwrap_or_default());
Self::try_new_with_options(writer, arrow_schema, options)
}
/// Try to create a new Async Arrow Writer with [`ArrowWriterOptions`]
pub fn try_new_with_options(
writer: W,
arrow_schema: SchemaRef,
options: ArrowWriterOptions,
) -> Result<Self> {
let sync_writer = ArrowWriter::try_new_with_options(Vec::new(), arrow_schema, options)?;
Ok(Self {
sync_writer,
async_writer: writer,
})
}
/// Returns metadata for any flushed row groups
pub fn flushed_row_groups(&self) -> &[RowGroupMetaData] {
self.sync_writer.flushed_row_groups()
}
/// Estimated memory usage, in bytes, of this `ArrowWriter`
///
/// See [ArrowWriter::memory_size] for more information.
pub fn memory_size(&self) -> usize {
self.sync_writer.memory_size()
}
/// Anticipated encoded size of the in progress row group.
///
/// See [ArrowWriter::memory_size] for more information.
pub fn in_progress_size(&self) -> usize {
self.sync_writer.in_progress_size()
}
/// Returns the number of rows buffered in the in progress row group
pub fn in_progress_rows(&self) -> usize {
self.sync_writer.in_progress_rows()
}
/// Returns the number of bytes written by this instance
pub fn bytes_written(&self) -> usize {
self.sync_writer.bytes_written()
}
/// Enqueues the provided `RecordBatch` to be written
///
/// After every sync write by the inner [ArrowWriter], the inner buffer will be
/// checked and flush if at least half full
pub async fn write(&mut self, batch: &RecordBatch) -> Result<()> {
let before = self.sync_writer.flushed_row_groups().len();
self.sync_writer.write(batch)?;
if before != self.sync_writer.flushed_row_groups().len() {
self.do_write().await?;
}
Ok(())
}
/// Flushes all buffered rows into a new row group
pub async fn flush(&mut self) -> Result<()> {
self.sync_writer.flush()?;
self.do_write().await?;
Ok(())
}
/// Append [`KeyValue`] metadata in addition to those in [`WriterProperties`]
///
/// This method allows to append metadata after [`RecordBatch`]es are written.
pub fn append_key_value_metadata(&mut self, kv_metadata: KeyValue) {
self.sync_writer.append_key_value_metadata(kv_metadata);
}
/// Close and finalize the writer.
///
/// All the data in the inner buffer will be force flushed.
///
/// Unlike [`Self::close`] this does not consume self
///
/// Attempting to write after calling finish will result in an error
pub async fn finish(&mut self) -> Result<FileMetaData> {
let metadata = self.sync_writer.finish()?;
// Force to flush the remaining data.
self.do_write().await?;
self.async_writer.complete().await?;
Ok(metadata)
}
/// Close and finalize the writer.
///
/// All the data in the inner buffer will be force flushed.
pub async fn close(mut self) -> Result<FileMetaData> {
self.finish().await
}
/// Flush the data written by `sync_writer` into the `async_writer`
///
/// # Notes
///
/// This method will take the inner buffer from the `sync_writer` and write it into the
/// async writer. After the write, the inner buffer will be empty.
async fn do_write(&mut self) -> Result<()> {
let buffer = mem::take(self.sync_writer.inner_mut());
self.async_writer
.write(Bytes::from(buffer))
.await
.map_err(|e| ParquetError::External(Box::new(e)))?;
Ok(())
}
}
#[cfg(test)]
mod tests {
use arrow::datatypes::{DataType, Field, Schema};
use arrow_array::{ArrayRef, BinaryArray, Int32Array, Int64Array, RecordBatchReader};
use bytes::Bytes;
use std::sync::Arc;
use tokio::pin;
use crate::arrow::arrow_reader::{ParquetRecordBatchReader, ParquetRecordBatchReaderBuilder};
use super::*;
fn get_test_reader() -> ParquetRecordBatchReader {
let testdata = arrow::util::test_util::parquet_test_data();
// This test file is large enough to generate multiple row groups.
let path = format!("{}/alltypes_tiny_pages_plain.parquet", testdata);
let original_data = Bytes::from(std::fs::read(path).unwrap());
ParquetRecordBatchReaderBuilder::try_new(original_data)
.unwrap()
.build()
.unwrap()
}
#[tokio::test]
async fn test_async_writer() {
let col = Arc::new(Int64Array::from_iter_values([1, 2, 3])) as ArrayRef;
let to_write = RecordBatch::try_from_iter([("col", col)]).unwrap();
let mut buffer = Vec::new();
let mut writer = AsyncArrowWriter::try_new(&mut buffer, to_write.schema(), None).unwrap();
writer.write(&to_write).await.unwrap();
writer.close().await.unwrap();
let buffer = Bytes::from(buffer);
let mut reader = ParquetRecordBatchReaderBuilder::try_new(buffer)
.unwrap()
.build()
.unwrap();
let read = reader.next().unwrap().unwrap();
assert_eq!(to_write, read);
}
// Read the data from the test file and write it by the async writer and sync writer.
// And then compares the results of the two writers.
#[tokio::test]
async fn test_async_writer_with_sync_writer() {
let reader = get_test_reader();
let write_props = WriterProperties::builder()
.set_max_row_group_size(64)
.build();
let mut async_buffer = Vec::new();
let mut async_writer = AsyncArrowWriter::try_new(
&mut async_buffer,
reader.schema(),
Some(write_props.clone()),
)
.unwrap();
let mut sync_buffer = Vec::new();
let mut sync_writer =
ArrowWriter::try_new(&mut sync_buffer, reader.schema(), Some(write_props)).unwrap();
for record_batch in reader {
let record_batch = record_batch.unwrap();
async_writer.write(&record_batch).await.unwrap();
sync_writer.write(&record_batch).unwrap();
}
sync_writer.close().unwrap();
async_writer.close().await.unwrap();
assert_eq!(sync_buffer, async_buffer);
}
struct TestAsyncSink {
sink: Vec<u8>,
min_accept_bytes: usize,
expect_total_bytes: usize,
}
impl AsyncWrite for TestAsyncSink {
fn poll_write(
self: std::pin::Pin<&mut Self>,
cx: &mut std::task::Context<'_>,
buf: &[u8],
) -> std::task::Poll<std::result::Result<usize, std::io::Error>> {
let written_bytes = self.sink.len();
if written_bytes + buf.len() < self.expect_total_bytes {
assert!(buf.len() >= self.min_accept_bytes);
} else {
assert_eq!(written_bytes + buf.len(), self.expect_total_bytes);
}
let sink = &mut self.get_mut().sink;
pin!(sink);
sink.poll_write(cx, buf)
}
fn poll_flush(
self: std::pin::Pin<&mut Self>,
cx: &mut std::task::Context<'_>,
) -> std::task::Poll<std::result::Result<(), std::io::Error>> {
let sink = &mut self.get_mut().sink;
pin!(sink);
sink.poll_flush(cx)
}
fn poll_shutdown(
self: std::pin::Pin<&mut Self>,
cx: &mut std::task::Context<'_>,
) -> std::task::Poll<std::result::Result<(), std::io::Error>> {
let sink = &mut self.get_mut().sink;
pin!(sink);
sink.poll_shutdown(cx)
}
}
#[tokio::test]
async fn test_async_writer_bytes_written() {
let col = Arc::new(Int64Array::from_iter_values([1, 2, 3])) as ArrayRef;
let to_write = RecordBatch::try_from_iter([("col", col)]).unwrap();
let temp = tempfile::tempfile().unwrap();
let file = tokio::fs::File::from_std(temp.try_clone().unwrap());
let mut writer =
AsyncArrowWriter::try_new(file.try_clone().await.unwrap(), to_write.schema(), None)
.unwrap();
writer.write(&to_write).await.unwrap();
let _metadata = writer.finish().await.unwrap();
// After `finish` this should include the metadata and footer
let reported = writer.bytes_written();
// Get actual size from file metadata
let actual = file.metadata().await.unwrap().len() as usize;
assert_eq!(reported, actual);
}
#[tokio::test]
async fn test_async_writer_file() {
let col = Arc::new(Int64Array::from_iter_values([1, 2, 3])) as ArrayRef;
let col2 = Arc::new(BinaryArray::from_iter_values(vec![
vec![0; 500000],
vec![0; 500000],
vec![0; 500000],
])) as ArrayRef;
let to_write = RecordBatch::try_from_iter([("col", col), ("col2", col2)]).unwrap();
let temp = tempfile::tempfile().unwrap();
let file = tokio::fs::File::from_std(temp.try_clone().unwrap());
let mut writer = AsyncArrowWriter::try_new(file, to_write.schema(), None).unwrap();
writer.write(&to_write).await.unwrap();
writer.close().await.unwrap();
let mut reader = ParquetRecordBatchReaderBuilder::try_new(temp)
.unwrap()
.build()
.unwrap();
let read = reader.next().unwrap().unwrap();
assert_eq!(to_write, read);
}
#[tokio::test]
async fn in_progress_accounting() {
// define schema
let schema = Schema::new(vec![Field::new("a", DataType::Int32, false)]);
// create some data
let a = Int32Array::from_value(0_i32, 512);
// build a record batch
let batch = RecordBatch::try_new(Arc::new(schema), vec![Arc::new(a)]).unwrap();
let temp = tempfile::tempfile().unwrap();
let file = tokio::fs::File::from_std(temp.try_clone().unwrap());
let mut writer = AsyncArrowWriter::try_new(file, batch.schema(), None).unwrap();
// starts empty
assert_eq!(writer.in_progress_size(), 0);
assert_eq!(writer.in_progress_rows(), 0);
assert_eq!(writer.bytes_written(), 4); // Initial Parquet header
writer.write(&batch).await.unwrap();
// updated on write
let initial_size = writer.in_progress_size();
assert!(initial_size > 0);
assert_eq!(writer.in_progress_rows(), batch.num_rows());
let initial_memory = writer.memory_size();
// memory estimate is larger than estimated encoded size
assert!(
initial_size <= initial_memory,
"{initial_size} <= {initial_memory}"
);
// updated on second write
writer.write(&batch).await.unwrap();
assert!(writer.in_progress_size() > initial_size);
assert_eq!(writer.in_progress_rows(), batch.num_rows() * 2);
assert!(writer.memory_size() > initial_memory);
assert!(
writer.in_progress_size() <= writer.memory_size(),
"in_progress_size {} <= memory_size {}",
writer.in_progress_size(),
writer.memory_size()
);
// in progress tracking is cleared, but the overall data written is updated
let pre_flush_bytes_written = writer.bytes_written();
writer.flush().await.unwrap();
assert_eq!(writer.in_progress_size(), 0);
assert_eq!(writer.memory_size(), 0);
assert_eq!(writer.in_progress_rows(), 0);
assert!(writer.bytes_written() > pre_flush_bytes_written);
writer.close().await.unwrap();
}
}