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Posted to github@arrow.apache.org by "tustvold (via GitHub)" <gi...@apache.org> on 2023/05/09 13:21:35 UTC
[GitHub] [arrow-datafusion] tustvold opened a new pull request, #6308: Parallel merge sort (#6162)
tustvold opened a new pull request, #6308:
URL: https://github.com/apache/arrow-datafusion/pull/6308
# Which issue does this PR close?
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Closes #6162
# Rationale for this change
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# What changes are included in this PR?
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# Are these changes tested?
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Will run benchmarks prior to merge
# Are there any user-facing changes?
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[GitHub] [arrow-datafusion] alamb commented on pull request #6308: Parallel merge sort (#6162)
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on PR #6308:
URL: https://github.com/apache/arrow-datafusion/pull/6308#issuecomment-1541042461
I plan to review this carefully tomorrow morning
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[GitHub] [arrow-datafusion] tustvold commented on pull request #6308: Parallel merge sort (#6162)
Posted by "tustvold (via GitHub)" <gi...@apache.org>.
tustvold commented on PR #6308:
URL: https://github.com/apache/arrow-datafusion/pull/6308#issuecomment-1542392911
It isn't a huge win, but I'll take it
```
sort utf8 low cardinality
time: [9.0271 ms 9.0396 ms 9.0527 ms]
change: [-11.727% -11.548% -11.370%] (p = 0.00 < 0.05)
Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
3 (3.00%) high mild
1 (1.00%) high severe
merge sorted utf8 high cardinality
time: [7.8055 ms 7.8186 ms 7.8341 ms]
change: [-3.5327% -3.0466% -2.5856%] (p = 0.00 < 0.05)
Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
2 (2.00%) high mild
2 (2.00%) high severe
sort merge utf8 high cardinality
time: [8.0414 ms 8.0505 ms 8.0599 ms]
change: [-2.5665% -2.3550% -2.1393%] (p = 0.00 < 0.05)
Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
2 (2.00%) high mild
sort utf8 high cardinality
time: [12.386 ms 12.413 ms 12.442 ms]
change: [-15.231% -14.371% -13.530%] (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
sort utf8 tuple time: [19.995 ms 20.037 ms 20.082 ms]
change: [-23.549% -23.240% -22.940%] (p = 0.00 < 0.05)
Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
1 (1.00%) high mild
3 (3.00%) high severe
sort mixed dictionary tuple
time: [21.851 ms 21.939 ms 22.033 ms]
change: [-13.963% -13.555% -13.128%] (p = 0.00 < 0.05)
Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
6 (6.00%) high mild
sort mixed tuple time: [19.054 ms 19.176 ms 19.307 ms]
change: [-13.179% -12.578% -11.928%] (p = 0.00 < 0.05)
Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
11 (11.00%) high mild
1 (1.00%) high severe
```
There is no change the merge benches and the benches for primitive arrays (as they don't use SortPreservingMerge)
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[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #6308: Parallel merge sort (#6162)
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on code in PR #6308:
URL: https://github.com/apache/arrow-datafusion/pull/6308#discussion_r1189868392
##########
datafusion/core/src/physical_plan/common.rs:
##########
@@ -180,6 +181,31 @@ pub(crate) fn spawn_execution(
})
}
+/// If running in a tokio context spawns the execution of `stream` to a separate task
+/// allowing it to execute in parallel with an intermediate buffer of size `buffer`
+pub(crate) fn spawn_buffered(
+ mut input: SendableRecordBatchStream,
+ buffer: usize,
+) -> SendableRecordBatchStream {
+ // Use tokio only if running from a tokio context (#2201)
Review Comment:
Nice
##########
datafusion/core/src/physical_plan/sorts/sort_preserving_merge.rs:
##########
@@ -181,29 +180,12 @@ impl ExecutionPlan for SortPreservingMergeExec {
result
}
_ => {
- // Use tokio only if running from a tokio context (#2201)
- let receivers = match tokio::runtime::Handle::try_current() {
- Ok(_) => (0..input_partitions)
- .map(|part_i| {
- let (sender, receiver) = mpsc::channel(1);
- let join_handle = spawn_execution(
- self.input.clone(),
- sender,
- part_i,
- context.clone(),
- );
-
- RecordBatchReceiverStream::create(
- &schema,
- receiver,
- join_handle,
- )
- })
- .collect(),
- Err(_) => (0..input_partitions)
- .map(|partition| self.input.execute(partition, context.clone()))
- .collect::<Result<_>>()?,
- };
+ let receivers = (0..input_partitions)
Review Comment:
This looks beautiful
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[GitHub] [arrow-datafusion] alamb commented on pull request #6308: Parallel merge sort (#6162)
Posted by "alamb (via GitHub)" <gi...@apache.org>.
alamb commented on PR #6308:
URL: https://github.com/apache/arrow-datafusion/pull/6308#issuecomment-1542416728
I think we should merge it
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[GitHub] [arrow-datafusion] tustvold merged pull request #6308: Parallel merge sort (#6162)
Posted by "tustvold (via GitHub)" <gi...@apache.org>.
tustvold merged PR #6308:
URL: https://github.com/apache/arrow-datafusion/pull/6308
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