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https://github.com/neondatabase/neon.git
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pageserver: integrate k-merge with bottom-most compaction (#8415)
Use the k-merge iterator in the compaction process to reduce memory footprint. part of https://github.com/neondatabase/neon/issues/8002 ## Summary of changes * refactor the bottom-most compaction code to use k-merge iterator * add Send bound on some structs as it is used across the await points --------- Signed-off-by: Alex Chi Z <chi@neon.tech> Co-authored-by: Arpad Müller <arpad-m@users.noreply.github.com>
This commit is contained in:
@@ -6810,7 +6810,7 @@ mod tests {
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vec![
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// Image layer at GC horizon
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PersistentLayerKey {
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key_range: Key::MIN..get_key(10),
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key_range: Key::MIN..Key::MAX,
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lsn_range: Lsn(0x30)..Lsn(0x31),
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is_delta: false
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},
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@@ -262,7 +262,7 @@ where
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pub fn iter<'a>(self, start_key: &'a [u8; L], ctx: &'a RequestContext) -> DiskBtreeIterator<'a>
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where
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R: 'a,
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R: 'a + Send,
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{
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DiskBtreeIterator {
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stream: Box::pin(self.into_stream(start_key, ctx)),
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@@ -521,7 +521,7 @@ where
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pub struct DiskBtreeIterator<'a> {
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#[allow(clippy::type_complexity)]
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stream: std::pin::Pin<
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Box<dyn Stream<Item = std::result::Result<(Vec<u8>, u64), DiskBtreeError>> + 'a>,
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Box<dyn Stream<Item = std::result::Result<(Vec<u8>, u64), DiskBtreeError>> + 'a + Send>,
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>,
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}
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@@ -6,8 +6,6 @@ pub(crate) mod inmemory_layer;
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pub(crate) mod layer;
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mod layer_desc;
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mod layer_name;
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#[cfg(test)]
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pub mod merge_iterator;
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use crate::context::{AccessStatsBehavior, RequestContext};
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@@ -33,11 +33,14 @@ use crate::page_cache::{self, FileId, PAGE_SZ};
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use crate::repository::{Key, Value, KEY_SIZE};
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use crate::tenant::blob_io::BlobWriter;
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use crate::tenant::block_io::{BlockBuf, BlockCursor, BlockLease, BlockReader, FileBlockReader};
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use crate::tenant::disk_btree::{DiskBtreeBuilder, DiskBtreeReader, VisitDirection};
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use crate::tenant::disk_btree::{
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DiskBtreeBuilder, DiskBtreeIterator, DiskBtreeReader, VisitDirection,
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};
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use crate::tenant::storage_layer::{Layer, ValueReconstructResult, ValueReconstructState};
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use crate::tenant::timeline::GetVectoredError;
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use crate::tenant::vectored_blob_io::{
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BlobFlag, MaxVectoredReadBytes, VectoredBlobReader, VectoredRead, VectoredReadPlanner,
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BlobFlag, MaxVectoredReadBytes, StreamingVectoredReadPlanner, VectoredBlobReader, VectoredRead,
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VectoredReadPlanner,
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};
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use crate::tenant::{PageReconstructError, Timeline};
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use crate::virtual_file::{self, VirtualFile};
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@@ -53,6 +56,7 @@ use pageserver_api::models::{ImageCompressionAlgorithm, LayerAccessKind};
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use pageserver_api::shard::TenantShardId;
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use rand::{distributions::Alphanumeric, Rng};
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use serde::{Deserialize, Serialize};
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use std::collections::VecDeque;
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use std::fs::File;
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use std::io::SeekFrom;
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use std::ops::Range;
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@@ -747,12 +751,10 @@ impl DeltaLayer {
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}
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impl DeltaLayerInner {
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#[cfg(test)]
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pub(crate) fn key_range(&self) -> &Range<Key> {
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&self.layer_key_range
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}
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#[cfg(test)]
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pub(crate) fn lsn_range(&self) -> &Range<Lsn> {
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&self.layer_lsn_range
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}
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@@ -1512,7 +1514,6 @@ impl DeltaLayerInner {
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offset
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}
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#[cfg(test)]
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pub(crate) fn iter<'a>(&'a self, ctx: &'a RequestContext) -> DeltaLayerIterator<'a> {
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let block_reader = FileBlockReader::new(&self.file, self.file_id);
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let tree_reader =
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@@ -1523,7 +1524,7 @@ impl DeltaLayerInner {
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index_iter: tree_reader.iter(&[0; DELTA_KEY_SIZE], ctx),
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key_values_batch: std::collections::VecDeque::new(),
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is_end: false,
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planner: crate::tenant::vectored_blob_io::StreamingVectoredReadPlanner::new(
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planner: StreamingVectoredReadPlanner::new(
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1024 * 8192, // The default value. Unit tests might use a different value. 1024 * 8K = 8MB buffer.
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1024, // The default value. Unit tests might use a different value
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),
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@@ -1595,17 +1596,15 @@ impl<'a> pageserver_compaction::interface::CompactionDeltaEntry<'a, Key> for Del
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}
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}
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#[cfg(test)]
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pub struct DeltaLayerIterator<'a> {
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delta_layer: &'a DeltaLayerInner,
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ctx: &'a RequestContext,
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planner: crate::tenant::vectored_blob_io::StreamingVectoredReadPlanner,
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index_iter: crate::tenant::disk_btree::DiskBtreeIterator<'a>,
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key_values_batch: std::collections::VecDeque<(Key, Lsn, Value)>,
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planner: StreamingVectoredReadPlanner,
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index_iter: DiskBtreeIterator<'a>,
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key_values_batch: VecDeque<(Key, Lsn, Value)>,
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is_end: bool,
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}
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#[cfg(test)]
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impl<'a> DeltaLayerIterator<'a> {
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/// Retrieve a batch of key-value pairs into the iterator buffer.
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async fn next_batch(&mut self) -> anyhow::Result<()> {
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@@ -29,13 +29,16 @@ use crate::page_cache::{self, FileId, PAGE_SZ};
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use crate::repository::{Key, Value, KEY_SIZE};
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use crate::tenant::blob_io::BlobWriter;
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use crate::tenant::block_io::{BlockBuf, BlockReader, FileBlockReader};
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use crate::tenant::disk_btree::{DiskBtreeBuilder, DiskBtreeReader, VisitDirection};
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use crate::tenant::disk_btree::{
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DiskBtreeBuilder, DiskBtreeIterator, DiskBtreeReader, VisitDirection,
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};
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use crate::tenant::storage_layer::{
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LayerAccessStats, ValueReconstructResult, ValueReconstructState,
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};
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use crate::tenant::timeline::GetVectoredError;
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use crate::tenant::vectored_blob_io::{
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BlobFlag, MaxVectoredReadBytes, VectoredBlobReader, VectoredRead, VectoredReadPlanner,
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BlobFlag, MaxVectoredReadBytes, StreamingVectoredReadPlanner, VectoredBlobReader, VectoredRead,
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VectoredReadPlanner,
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};
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use crate::tenant::{PageReconstructError, Timeline};
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use crate::virtual_file::{self, VirtualFile};
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@@ -50,6 +53,7 @@ use pageserver_api::models::LayerAccessKind;
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use pageserver_api::shard::{ShardIdentity, TenantShardId};
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use rand::{distributions::Alphanumeric, Rng};
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use serde::{Deserialize, Serialize};
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use std::collections::VecDeque;
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use std::fs::File;
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use std::io::SeekFrom;
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use std::ops::Range;
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@@ -369,12 +373,10 @@ impl ImageLayer {
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}
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impl ImageLayerInner {
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#[cfg(test)]
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pub(crate) fn key_range(&self) -> &Range<Key> {
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&self.key_range
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}
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#[cfg(test)]
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pub(crate) fn lsn(&self) -> Lsn {
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self.lsn
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}
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@@ -699,7 +701,6 @@ impl ImageLayerInner {
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}
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}
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#[cfg(test)]
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pub(crate) fn iter<'a>(&'a self, ctx: &'a RequestContext) -> ImageLayerIterator<'a> {
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let block_reader = FileBlockReader::new(&self.file, self.file_id);
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let tree_reader =
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@@ -708,9 +709,9 @@ impl ImageLayerInner {
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image_layer: self,
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ctx,
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index_iter: tree_reader.iter(&[0; KEY_SIZE], ctx),
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key_values_batch: std::collections::VecDeque::new(),
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key_values_batch: VecDeque::new(),
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is_end: false,
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planner: crate::tenant::vectored_blob_io::StreamingVectoredReadPlanner::new(
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planner: StreamingVectoredReadPlanner::new(
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1024 * 8192, // The default value. Unit tests might use a different value. 1024 * 8K = 8MB buffer.
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1024, // The default value. Unit tests might use a different value
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),
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@@ -974,17 +975,15 @@ impl Drop for ImageLayerWriter {
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}
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}
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#[cfg(test)]
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pub struct ImageLayerIterator<'a> {
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image_layer: &'a ImageLayerInner,
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ctx: &'a RequestContext,
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planner: crate::tenant::vectored_blob_io::StreamingVectoredReadPlanner,
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index_iter: crate::tenant::disk_btree::DiskBtreeIterator<'a>,
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key_values_batch: std::collections::VecDeque<(Key, Lsn, Value)>,
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planner: StreamingVectoredReadPlanner,
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index_iter: DiskBtreeIterator<'a>,
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key_values_batch: VecDeque<(Key, Lsn, Value)>,
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is_end: bool,
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}
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#[cfg(test)]
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impl<'a> ImageLayerIterator<'a> {
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/// Retrieve a batch of key-value pairs into the iterator buffer.
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async fn next_batch(&mut self) -> anyhow::Result<()> {
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@@ -385,6 +385,7 @@ impl Layer {
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}
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/// Get all key/values in the layer. Should be replaced with an iterator-based API in the future.
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#[allow(dead_code)]
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pub(crate) async fn load_key_values(
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&self,
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ctx: &RequestContext,
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@@ -1918,7 +1919,7 @@ impl ResidentLayer {
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self.owner.metadata()
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}
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#[cfg(test)]
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/// Cast the layer to a delta, return an error if it is an image layer.
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pub(crate) async fn get_as_delta(
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&self,
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ctx: &RequestContext,
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@@ -1930,7 +1931,7 @@ impl ResidentLayer {
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}
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}
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#[cfg(test)]
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/// Cast the layer to an image, return an error if it is a delta layer.
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pub(crate) async fn get_as_image(
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&self,
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ctx: &RequestContext,
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@@ -547,5 +547,9 @@ mod tests {
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&ctx,
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);
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assert_merge_iter_equal(&mut merge_iter, &expect).await;
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is_send(merge_iter);
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}
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fn is_send(_: impl Send) {}
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}
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@@ -27,6 +27,7 @@ use utils::id::TimelineId;
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use crate::context::{AccessStatsBehavior, RequestContext, RequestContextBuilder};
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use crate::page_cache;
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use crate::tenant::config::defaults::{DEFAULT_CHECKPOINT_DISTANCE, DEFAULT_COMPACTION_THRESHOLD};
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use crate::tenant::storage_layer::merge_iterator::MergeIterator;
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use crate::tenant::storage_layer::{AsLayerDesc, PersistentLayerDesc};
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use crate::tenant::timeline::{drop_rlock, DeltaLayerWriter, ImageLayerWriter};
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use crate::tenant::timeline::{Hole, ImageLayerCreationOutcome};
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@@ -1039,10 +1040,12 @@ impl Timeline {
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);
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// Step 1: (In the future) construct a k-merge iterator over all layers. For now, simply collect all keys + LSNs.
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// Also, collect the layer information to decide when to split the new delta layers.
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let mut all_key_values = Vec::new();
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let mut downloaded_layers = Vec::new();
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let mut delta_split_points = BTreeSet::new();
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for layer in &layer_selection {
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all_key_values.extend(layer.load_key_values(ctx).await?);
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let resident_layer = layer.download_and_keep_resident().await?;
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downloaded_layers.push(resident_layer);
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let desc = layer.layer_desc();
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if desc.is_delta() {
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// TODO: is it correct to only record split points for deltas intersecting with the GC horizon? (exclude those below/above the horizon)
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@@ -1052,44 +1055,28 @@ impl Timeline {
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delta_split_points.insert(key_range.end);
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}
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}
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// Key small to large, LSN low to high, if the same LSN has both image and delta due to the merge of delta layers and
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// image layers, make image appear before than delta.
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struct ValueWrapper<'a>(&'a crate::repository::Value);
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impl Ord for ValueWrapper<'_> {
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fn cmp(&self, other: &Self) -> std::cmp::Ordering {
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use crate::repository::Value;
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use std::cmp::Ordering;
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match (self.0, other.0) {
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(Value::Image(_), Value::WalRecord(_)) => Ordering::Less,
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(Value::WalRecord(_), Value::Image(_)) => Ordering::Greater,
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_ => Ordering::Equal,
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}
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let mut delta_layers = Vec::new();
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let mut image_layers = Vec::new();
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for resident_layer in &downloaded_layers {
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if resident_layer.layer_desc().is_delta() {
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let layer = resident_layer.get_as_delta(ctx).await?;
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delta_layers.push(layer);
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} else {
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let layer = resident_layer.get_as_image(ctx).await?;
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image_layers.push(layer);
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}
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}
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impl PartialOrd for ValueWrapper<'_> {
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fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
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Some(self.cmp(other))
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}
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}
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impl PartialEq for ValueWrapper<'_> {
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fn eq(&self, other: &Self) -> bool {
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self.cmp(other) == std::cmp::Ordering::Equal
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}
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}
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impl Eq for ValueWrapper<'_> {}
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all_key_values.sort_by(|(k1, l1, v1), (k2, l2, v2)| {
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(k1, l1, ValueWrapper(v1)).cmp(&(k2, l2, ValueWrapper(v2)))
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});
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let mut merge_iter = MergeIterator::create(&delta_layers, &image_layers, ctx);
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// Step 2: Produce images+deltas. TODO: ensure newly-produced delta does not overlap with other deltas.
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// Data of the same key.
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let mut accumulated_values = Vec::new();
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let mut last_key = all_key_values.first().unwrap().0; // TODO: assert all_key_values not empty
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let mut last_key: Option<Key> = None;
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/// Take a list of images and deltas, produce an image at the GC horizon, and a list of deltas above the GC horizon.
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async fn flush_accumulated_states(
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tline: &Arc<Timeline>,
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key: Key,
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accumulated_values: &[&(Key, Lsn, crate::repository::Value)],
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accumulated_values: &[(Key, Lsn, crate::repository::Value)],
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horizon: Lsn,
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) -> anyhow::Result<(Vec<(Key, Lsn, crate::repository::Value)>, bytes::Bytes)> {
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let mut base_image = None;
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@@ -1190,7 +1177,7 @@ impl Timeline {
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self.conf,
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self.timeline_id,
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self.tenant_shard_id,
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&(all_key_values.first().unwrap().0..all_key_values.last().unwrap().0.next()),
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&(Key::MIN..Key::MAX), // covers the full key range
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gc_cutoff,
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ctx,
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)
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@@ -1200,20 +1187,24 @@ impl Timeline {
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let delta_split_points = delta_split_points.into_iter().collect_vec();
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let mut current_delta_split_point = 0;
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let mut delta_layers = Vec::new();
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for item @ (key, _, _) in &all_key_values {
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if &last_key == key {
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accumulated_values.push(item);
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while let Some((key, lsn, val)) = merge_iter.next().await? {
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if last_key.is_none() || last_key.as_ref() == Some(&key) {
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if last_key.is_none() {
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last_key = Some(key);
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}
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accumulated_values.push((key, lsn, val));
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} else {
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let last_key = last_key.as_mut().unwrap();
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let (deltas, image) =
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flush_accumulated_states(self, last_key, &accumulated_values, gc_cutoff)
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flush_accumulated_states(self, *last_key, &accumulated_values, gc_cutoff)
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.await?;
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// Put the image into the image layer. Currently we have a single big layer for the compaction.
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image_layer_writer.put_image(last_key, image, ctx).await?;
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image_layer_writer.put_image(*last_key, image, ctx).await?;
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delta_values.extend(deltas);
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delta_layers.extend(
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flush_deltas(
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&mut delta_values,
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last_key,
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*last_key,
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&delta_split_points,
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&mut current_delta_split_point,
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self,
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@@ -1223,11 +1214,12 @@ impl Timeline {
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.await?,
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);
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accumulated_values.clear();
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accumulated_values.push(item);
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last_key = *key;
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*last_key = key;
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accumulated_values.push((key, lsn, val));
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}
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}
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let last_key = last_key.expect("no keys produced during compaction");
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// TODO: move this part to the loop body
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let (deltas, image) =
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flush_accumulated_states(self, last_key, &accumulated_values, gc_cutoff).await?;
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@@ -396,7 +396,6 @@ impl<'a> VectoredBlobReader<'a> {
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/// Read planner used in [`crate::tenant::storage_layer::image_layer::ImageLayerIterator`]. It provides a streaming API for
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/// getting read blobs. It returns a batch when `handle` gets called and when the current key would just exceed the read_size and
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/// max_cnt constraints.
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#[cfg(test)]
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pub struct StreamingVectoredReadPlanner {
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read_builder: Option<VectoredReadBuilder>,
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// Arguments for previous blob passed into [`StreamingVectoredReadPlanner::handle`]
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@@ -410,7 +409,6 @@ pub struct StreamingVectoredReadPlanner {
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cnt: usize,
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}
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#[cfg(test)]
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impl StreamingVectoredReadPlanner {
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pub fn new(max_read_size: u64, max_cnt: usize) -> Self {
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assert!(max_cnt > 0);
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