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Posted to github@arrow.apache.org by GitBox <gi...@apache.org> on 2022/11/21 08:21:30 UTC
[GitHub] [arrow-datafusion] richox opened a new pull request, #4301: Use tournament loser tree for k-way sort-merging
richox opened a new pull request, #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301
# Which issue does this PR close?
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Closes #4300.
# Rationale for this change
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Explaining clearly why changes are proposed helps reviewers understand your changes and offer better suggestions for fixes.
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# What changes are included in this PR?
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# Are these changes tested?
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2. Serve as another way to document the expected behavior of the code
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running benchmarks with `cargo bench --bench merge`:
```
merge i64 time: [8.0959 ms 8.2001 ms 8.3260 ms]
change: [-58.629% -57.906% -57.138%] (p = 0.00 < 0.05)
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
4 (4.00%) high mild
7 (7.00%) high severe
merge f64 time: [8.2829 ms 8.3378 ms 8.4028 ms]
change: [-56.127% -55.475% -54.829%] (p = 0.00 < 0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
5 (5.00%) high mild
5 (5.00%) high severe
merge utf8 low cardinality
time: [7.5418 ms 7.6425 ms 7.7538 ms]
change: [-65.897% -65.335% -64.703%] (p = 0.00 < 0.05)
Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
7 (7.00%) high mild
6 (6.00%) high severe
merge utf8 high cardinality
time: [9.9438 ms 10.094 ms 10.257 ms]
change: [-52.043% -51.155% -50.249%] (p = 0.00 < 0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
4 (4.00%) high mild
4 (4.00%) high severe
merge utf8 tuple time: [20.197 ms 20.493 ms 20.826 ms]
change: [-40.663% -39.505% -38.279%] (p = 0.00 < 0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
6 (6.00%) high mild
4 (4.00%) high severe
merge utf8 dictionary time: [5.1537 ms 5.2135 ms 5.2788 ms]
change: [-72.062% -71.616% -71.137%] (p = 0.00 < 0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
7 (7.00%) high mild
1 (1.00%) high severe
merge utf8 dictionary tuple
time: [7.9585 ms 8.0592 ms 8.1797 ms]
change: [-63.981% -63.324% -62.678%] (p = 0.00 < 0.05)
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
6 (6.00%) high mild
5 (5.00%) high severe
merge mixed utf8 dictionary tuple
time: [14.528 ms 14.669 ms 14.829 ms]
change: [-43.886% -43.201% -42.489%] (p = 0.00 < 0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
5 (5.00%) high mild
5 (5.00%) high severe
merge mixed tuple time: [17.824 ms 18.068 ms 18.333 ms]
change: [-39.957% -38.888% -37.748%] (p = 0.00 < 0.05)
Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
4 (4.00%) high mild
1 (1.00%) high severe
```
# Are there any user-facing changes?
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[GitHub] [arrow-datafusion] alamb merged pull request #4301: Use tournament loser tree for k-way sort-merging, increase merge speed by 50%
Posted by GitBox <gi...@apache.org>.
alamb merged PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301
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[GitHub] [arrow-datafusion] alamb commented on pull request #4301: Use tournament loser tree for k-way sort-merging, increase merge speed by 50%
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1329744186
Follow on PR: https://github.com/apache/arrow-datafusion/pull/4407
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[GitHub] [arrow-datafusion] alamb commented on pull request #4301: Use tournament loser tree for k-way sort-merging
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1322210468
cc @tustvold
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[GitHub] [arrow-datafusion] viirya commented on a diff in pull request #4301: Use tournament loser tree for k-way sort-merging
Posted by GitBox <gi...@apache.org>.
viirya commented on code in PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#discussion_r1028605200
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -551,17 +558,46 @@ impl SortPreservingMergeStream {
if self.aborted {
return Poll::Ready(None);
}
+ let num_streams = self.streams.num_streams();
+
+ // Init all cursors and the loser tree in the first poll
+ if self.loser_tree.is_empty() {
+ // Ensure all non-exhausted streams have a cursor from which
+ // rows can be pulled
+ for i in 0..num_streams {
+ match futures::ready!(self.maybe_poll_stream(cx, i)) {
+ Ok(_) => {}
+ Err(e) => {
+ self.aborted = true;
+ return Poll::Ready(Some(Err(e)));
+ }
+ }
+ }
- // Ensure all non-exhausted streams have a cursor from which
- // rows can be pulled
- for i in 0..self.streams.num_streams() {
- match futures::ready!(self.maybe_poll_stream(cx, i)) {
- Ok(_) => {}
- Err(e) => {
- self.aborted = true;
- return Poll::Ready(Some(Err(e)));
+ // Init loser tree
+ self.loser_tree.resize(num_streams, usize::MAX);
+ for i in 0..num_streams {
+ let mut winner = i;
+ let mut cmp_node = (num_streams + i) / 2;
+ while cmp_node != 0 && self.loser_tree[cmp_node] != usize::MAX {
+ let challenger = self.loser_tree[cmp_node];
+ let challenger_win =
+ match (&self.cursors[winner], &self.cursors[challenger]) {
+ (None, _) => true,
+ (_, None) => false,
+ (Some(winner), Some(challenger)) => challenger < winner,
+ };
+ if challenger_win {
+ self.loser_tree[cmp_node] = winner;
+ winner = challenger;
+ } else {
+ self.loser_tree[cmp_node] = challenger;
+ }
Review Comment:
```suggestion
if challenger_win {
self.loser_tree[cmp_node] = winner;
winner = challenger;
}
```
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[GitHub] [arrow-datafusion] ursabot commented on pull request #4301: Use tournament loser tree for k-way sort-merging, increase merge speed by 50%
Posted by GitBox <gi...@apache.org>.
ursabot commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1329708051
Benchmark runs are scheduled for baseline = 52e198ea456c588cd57d44e9d98b082d0d2bd163 and contender = 0d334cf7d67ecdf2bd095987242085e0d59484f3. 0d334cf7d67ecdf2bd095987242085e0d59484f3 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.
Conbench compare runs links:
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on ec2-t3-xlarge-us-east-2] [ec2-t3-xlarge-us-east-2](https://conbench.ursa.dev/compare/runs/8a1d6a9e8144471ea160fbf595429b98...e87c2696f67f401ca5b2010f755161db/)
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on test-mac-arm] [test-mac-arm](https://conbench.ursa.dev/compare/runs/1f452b0b9e094beeaf7cb42adf4764b1...1682458985cc45edafdc8130921044e5/)
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on ursa-i9-9960x] [ursa-i9-9960x](https://conbench.ursa.dev/compare/runs/e1dcc9c6029849b0804021114e9c24e3...f6fee4f8665843639b7a63f2317ccd6b/)
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on ursa-thinkcentre-m75q] [ursa-thinkcentre-m75q](https://conbench.ursa.dev/compare/runs/694098fac7f7436ebe9f500c72b861aa...6724d4d02f8645ad88909256d6eaaa0d/)
Buildkite builds:
Supported benchmarks:
ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python, R. Runs only benchmarks with cloud = True
test-mac-arm: Supported benchmark langs: C++, Python, R
ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript
ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
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[GitHub] [arrow-datafusion] alamb commented on pull request #4301: Use tournament loser tree for k-way sort-merging
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1328040325
If we don't hear back from @richox by Monday I plan to merge this PR and then create a follow on PR with the proposed changes from @tustvold and @viirya
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[GitHub] [arrow-datafusion] tustvold commented on a diff in pull request #4301: Use tournament loser tree for k-way sort-merging
Posted by GitBox <gi...@apache.org>.
tustvold commented on code in PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#discussion_r1028358218
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -570,45 +606,57 @@ impl SortPreservingMergeStream {
let _timer = elapsed_compute.timer();
loop {
- match self.heap.pop() {
- Some(Reverse(mut cursor)) => {
- let stream_idx = cursor.stream_idx();
- let batch_idx = self.batches[stream_idx].len() - 1;
- let row_idx = cursor.advance();
-
- let mut cursor_finished = false;
- // insert the cursor back to heap if the record batch is not exhausted
- if !cursor.is_finished() {
- self.heap.push(Reverse(cursor));
- } else {
- cursor_finished = true;
- self.cursor_finished[stream_idx] = true;
+ // Adjust the loser tree if necessary
+ if !self.loser_tree_adjusted {
+ let mut winner = self.loser_tree[0];
Review Comment:
It might be easier to follow if this was moved into a method called `replace_loser_tree_winner`, perhaps with a link to this GIF - https://en.wikipedia.org/wiki/K-way_merge_algorithm#/media/File:Loser_tree_replacement_selection.gif
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[GitHub] [arrow-datafusion] alamb commented on pull request #4301: Use tournament loser tree for k-way sort-merging, increase merge speed by 50%
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1329703852
I will have a follow on PR up shortly
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[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #4301: Use tournament loser tree for k-way sort-merging, increase merge speed by 50%
Posted by GitBox <gi...@apache.org>.
alamb commented on code in PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#discussion_r1034040105
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -570,45 +606,57 @@ impl SortPreservingMergeStream {
let _timer = elapsed_compute.timer();
loop {
- match self.heap.pop() {
- Some(Reverse(mut cursor)) => {
- let stream_idx = cursor.stream_idx();
- let batch_idx = self.batches[stream_idx].len() - 1;
- let row_idx = cursor.advance();
-
- let mut cursor_finished = false;
- // insert the cursor back to heap if the record batch is not exhausted
- if !cursor.is_finished() {
- self.heap.push(Reverse(cursor));
- } else {
- cursor_finished = true;
- self.cursor_finished[stream_idx] = true;
+ // Adjust the loser tree if necessary
+ if !self.loser_tree_adjusted {
+ let mut winner = self.loser_tree[0];
+ match futures::ready!(self.maybe_poll_stream(cx, winner)) {
+ Ok(_) => {}
+ Err(e) => {
+ self.aborted = true;
+ return Poll::Ready(Some(Err(e)));
}
+ }
- self.in_progress.push(RowIndex {
- stream_idx,
- batch_idx,
- row_idx,
- });
-
- if self.in_progress.len() == self.batch_size {
- return Poll::Ready(Some(self.build_record_batch()));
+ let mut cmp_node = (num_streams + winner) / 2;
+ while cmp_node != 0 {
+ let challenger = self.loser_tree[cmp_node];
+ let challenger_win =
+ match (&self.cursors[winner], &self.cursors[challenger]) {
+ (None, _) => true,
+ (_, None) => false,
+ (Some(winner), Some(challenger)) => challenger < winner,
+ };
+ if challenger_win {
+ self.loser_tree[cmp_node] = winner;
+ winner = challenger;
}
+ cmp_node /= 2;
+ }
+ self.loser_tree[0] = winner;
+ self.loser_tree_adjusted = true;
+ }
- // If removed the last row from the cursor, need to fetch a new record
- // batch if possible, before looping round again
- if cursor_finished {
- match futures::ready!(self.maybe_poll_stream(cx, stream_idx)) {
- Ok(_) => {}
- Err(e) => {
- self.aborted = true;
- return Poll::Ready(Some(Err(e)));
- }
- }
- }
+ let min_cursor_idx = self.loser_tree[0];
Review Comment:
I couldn't make this work in https://github.com/apache/arrow-datafusion/pull/4407
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[GitHub] [arrow-datafusion] alamb commented on pull request #4301: Use tournament loser tree for k-way sort-merging, increase merge speed by 50%
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1329704231
Thanks again @richox @tustvold and @viirya
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[GitHub] [arrow-datafusion] tustvold commented on a diff in pull request #4301: Use tournament loser tree for k-way sort-merging
Posted by GitBox <gi...@apache.org>.
tustvold commented on code in PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#discussion_r1028338480
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -570,45 +606,57 @@ impl SortPreservingMergeStream {
let _timer = elapsed_compute.timer();
loop {
- match self.heap.pop() {
- Some(Reverse(mut cursor)) => {
- let stream_idx = cursor.stream_idx();
- let batch_idx = self.batches[stream_idx].len() - 1;
- let row_idx = cursor.advance();
-
- let mut cursor_finished = false;
- // insert the cursor back to heap if the record batch is not exhausted
- if !cursor.is_finished() {
- self.heap.push(Reverse(cursor));
- } else {
- cursor_finished = true;
- self.cursor_finished[stream_idx] = true;
+ // Adjust the loser tree if necessary
+ if !self.loser_tree_adjusted {
+ let mut winner = self.loser_tree[0];
+ match futures::ready!(self.maybe_poll_stream(cx, winner)) {
+ Ok(_) => {}
+ Err(e) => {
+ self.aborted = true;
+ return Poll::Ready(Some(Err(e)));
}
+ }
- self.in_progress.push(RowIndex {
- stream_idx,
- batch_idx,
- row_idx,
- });
-
- if self.in_progress.len() == self.batch_size {
- return Poll::Ready(Some(self.build_record_batch()));
+ let mut cmp_node = (num_streams + winner) / 2;
Review Comment:
```suggestion
// Replace overall winner by walking tree of losers
let mut cmp_node = (num_streams + winner) / 2;
```
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -323,8 +318,17 @@ pub(crate) struct SortPreservingMergeStream {
/// An id to uniquely identify the input stream batch
next_batch_id: usize,
- /// Heap that yields [`SortKeyCursor`] in increasing order
- heap: BinaryHeap<Reverse<SortKeyCursor>>,
+ /// Vector that holds all [`SortKeyCursor`]s
+ cursors: Vec<Option<SortKeyCursor>>,
+
+ /// The loser tree that always produces the minimum cursor
+ ///
+ /// Node 0 stores the top winner, Nodes 1..num_streams store
+ /// the loser nodes
+ loser_tree: Vec<usize>,
+
+ /// Identify whether the loser tree is adjusted
Review Comment:
```suggestion
/// Identify whether the most recently yielded overall winner has been replaced
/// within the loser tree, a value of `false` indicates that they overall winner
/// has been yielded but the loser tree has not been updated
```
Or something to make it clearer what adjusted actually means.
FWIW a boolean of `should_replace_winner` or something might be clearer
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -551,17 +558,46 @@ impl SortPreservingMergeStream {
if self.aborted {
return Poll::Ready(None);
}
+ let num_streams = self.streams.num_streams();
+
+ // Init all cursors and the loser tree in the first poll
+ if self.loser_tree.is_empty() {
+ // Ensure all non-exhausted streams have a cursor from which
Review Comment:
It might be easier to follow if this method were split into a method called `init_loser_tree` with a doc comment explaining what it does
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -570,45 +606,57 @@ impl SortPreservingMergeStream {
let _timer = elapsed_compute.timer();
loop {
- match self.heap.pop() {
- Some(Reverse(mut cursor)) => {
- let stream_idx = cursor.stream_idx();
- let batch_idx = self.batches[stream_idx].len() - 1;
- let row_idx = cursor.advance();
-
- let mut cursor_finished = false;
- // insert the cursor back to heap if the record batch is not exhausted
- if !cursor.is_finished() {
- self.heap.push(Reverse(cursor));
- } else {
- cursor_finished = true;
- self.cursor_finished[stream_idx] = true;
+ // Adjust the loser tree if necessary
+ if !self.loser_tree_adjusted {
+ let mut winner = self.loser_tree[0];
Review Comment:
It might be easier to follow if this was moved into a method called `replace_loser_tree_winner`
##########
datafusion/core/src/physical_plan/sorts/cursor.rs:
##########
@@ -109,8 +109,14 @@ impl PartialOrd for SortKeyCursor {
impl Ord for SortKeyCursor {
fn cmp(&self, other: &Self) -> Ordering {
- self.current()
- .cmp(&other.current())
- .then_with(|| self.stream_idx.cmp(&other.stream_idx))
+ match (self.is_finished(), other.is_finished()) {
Review Comment:
```suggestion
// Order finished cursors last
match (self.is_finished(), other.is_finished()) {
```
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -570,45 +606,57 @@ impl SortPreservingMergeStream {
let _timer = elapsed_compute.timer();
loop {
- match self.heap.pop() {
- Some(Reverse(mut cursor)) => {
- let stream_idx = cursor.stream_idx();
- let batch_idx = self.batches[stream_idx].len() - 1;
- let row_idx = cursor.advance();
-
- let mut cursor_finished = false;
- // insert the cursor back to heap if the record batch is not exhausted
- if !cursor.is_finished() {
- self.heap.push(Reverse(cursor));
- } else {
- cursor_finished = true;
- self.cursor_finished[stream_idx] = true;
+ // Adjust the loser tree if necessary
+ if !self.loser_tree_adjusted {
+ let mut winner = self.loser_tree[0];
+ match futures::ready!(self.maybe_poll_stream(cx, winner)) {
+ Ok(_) => {}
+ Err(e) => {
+ self.aborted = true;
+ return Poll::Ready(Some(Err(e)));
}
+ }
- self.in_progress.push(RowIndex {
- stream_idx,
- batch_idx,
- row_idx,
- });
-
- if self.in_progress.len() == self.batch_size {
- return Poll::Ready(Some(self.build_record_batch()));
+ let mut cmp_node = (num_streams + winner) / 2;
+ while cmp_node != 0 {
+ let challenger = self.loser_tree[cmp_node];
+ let challenger_win =
+ match (&self.cursors[winner], &self.cursors[challenger]) {
+ (None, _) => true,
+ (_, None) => false,
+ (Some(winner), Some(challenger)) => challenger < winner,
+ };
+ if challenger_win {
+ self.loser_tree[cmp_node] = winner;
+ winner = challenger;
}
+ cmp_node /= 2;
+ }
+ self.loser_tree[0] = winner;
+ self.loser_tree_adjusted = true;
+ }
- // If removed the last row from the cursor, need to fetch a new record
- // batch if possible, before looping round again
- if cursor_finished {
- match futures::ready!(self.maybe_poll_stream(cx, stream_idx)) {
- Ok(_) => {}
- Err(e) => {
- self.aborted = true;
- return Poll::Ready(Some(Err(e)));
- }
- }
- }
+ let min_cursor_idx = self.loser_tree[0];
Review Comment:
I think this could be made easier to follow if it were written along the lines of
```
let min_cursor = self.cursors[min_cursor_idx];
if min_cursor.is_finished() {
// All streams are exhausted
return Poll::Ready((!self.in_progress.is_empty()).then(|| self.build_record_batch()))
}
self.loser_tree_adjusted = false;
self.in_progress.push(...)
if self.in_progress.len() == self.batch_size {
return Poll::Ready(Some(self.build_record_batch()));
}
```
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[GitHub] [arrow-datafusion] alamb commented on pull request #4301: Use tournament loser tree for k-way sort-merging
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4301:
URL: https://github.com/apache/arrow-datafusion/pull/4301#issuecomment-1323839682
Thanks @richox @tustvold and @viirya -- this looks awesome. Let's wait to see if @richox would like to respond to comments.
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